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vendor finance partnerships. We understand how to customize vendor

financing solutions that work for equipment manufacturers, dealers and

distributors across North America. With $2.0 billion in capital behind us,

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June 2013Volume 1 Number 2

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FEATURES

The 12 Secrets of Commercial Credit Scoring. Part 2.When he calls his

report “confessions of a closet quant jock” you know that author Thomas Ware not only revels in the number which come with a key part of the finance market, you also know he’s prepared to reveal what he’s learned as well. The conclusion of his special report. »12

Small Ticket LeasesOften maligned as subprime, high-risk, and expensive, “C” credit leases, especially in the small ticket marketplace, are a necessary and important driver in the overall economic market place today. Find out how you can leverage it for profit. »19

YOUR BUSINESS: Every Little Thing Gonna Be All Right (and other lies). If you’re managing your own business, author and advisor Angela Armstrong has

some sage advice about leadership, money and the new role of cash. »26

TECH REPORT 2013: Not Your Father’s Lease—The Unique Requirements of Information Technology Leasing.The use of information technology for organizational success has been greatly facilitated by the availability of lease financing. From the earliest days of mainframes lease financing has served the economic ecosystem well. But information technology--as a subset of ‘high technology’--has also created some new challenges for lending and leasing organizations. »18

Be Careful What You Wish For--The Single System ModelAvid followers of the asset finance industry technology scene may have picked up some of the winds of change in both the marketing messages and product strategies from software providers. Here’s what you may need to keep a eye out for these days. »21

NEWSA round up of the industry’s most significant developments from the past month. »9

EVENTS: Find out where to go and what to see in 2013. »29

OBSERVATIONS: An Appraiser’s Tale —How Technology Lets Me Live Where I Want. »30

ASSOCIATION REPORT:Using your lease management system as a competitive advantage. CFLA member Roxana Safranek shows how you can use technology to gain the upper hand against competitors when customers have more options than ever before. You need your lease management system to do more. Here’s how. »5

ASSOCIATION REPORT:Good news from our neighbours. ELFA releases its monthly Leasing & Finance index for the US marketplace shows that overall new business volume was up 23 percent compared to the same time period last year. Plus, get a quick point-by-point insight into the IT Sector as part of our 2013 Tech Report.. »6

CANADIAN EQUIPMENT FINANCE | MAY 2013 | canadianequipmentfinance.com4

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0535_Spartan_Outline.indd 1 13-04-19 10:10 AM



By Roxana Safranek

The Equipment Leasing and Finance industry has become extremely

competitive due in part to: commoditization, consolidation, excess liquidity and intensified regulatory scrutiny. Due to this increasingly competitive landscape, businesses are looking for ways to set themselves apart from their competitors. The best, and maybe the easiest answer, is through the use of technology.

If you see your lease/loan management system as just the vehicle that processes your transactions, you are doing your business a big disservice. Companies need to be constantly thinking of ways they can use their system to execute at higher levels and offer products and services that entice businesses to work with them. The good news is your current lease/loan management system may already position you for this success. In many cases, it’s a matter of education and working with your application provider to configure your system for improved efficiencies and added functionality.

When reviewing your system, the first thing to consider is your system’s workflow. In today’s world of “immediacy”, streamlining and automating your processes is more important than ever. By implementing automatic workflows, you can automate specific tasks and define the data that is required at each stage of your processes. The ability to automate and track workflows gives you visibility into any bottle necks that may occur and ensures you always have accurate data at the right time. Automated workflows add efficiencies, reduce errors, facilitate communication and

provide important tracking and analytics. Implementing automated workflows into your system is the foundation for providing top-tier service to your clients.

Another important component to elevating your business is having the ability to provide your clients with

the specific data they need - when they need it and in the format they need it in. Configuring your system to provide your clients with the key data points and analytics they require, empowers them to perform at their highest levels which in turn leads to customer satisfaction and loyalty.

Another important component to elevating your business is providing your customers with tools/functionality that will make doing business easier. Some examples are: electronic signature capabilities, a partner portal that is easy to navigate and accessible 24 x 7, having a configurable dashboard that can be customized according to each client’s requirements, and supporting mobile devices - allowing your clients to do business from anywhere anytime.

In today’s competitive marketplace customers have more options than ever before. The businesses which are responsive to customers, anticipate their customers’ needs and tailor their business processes to best serve their clients, gain a clear competitive advantage. That’s why it’s critical for businesses to look to their lease/loan management systems to do more. It’s the best way to set your business apart from competitors and position yourself for future success.

aBout tHe autHor: Roxana Safranek is Director of Marketing for LeaseTeam, Inc. and is responsible for marketing, communication and business development. She is committed to sharing her knowledge to help others in the Leasing Industry implement strategies that will help them grow their business.

association rePort

40th Anniversary Commemorative EditionThe CFLA is very proud to be celebrating our 40th Anniversary in 2013, to mark the occasion Canadian Equipment Finance magazine is publishing a Special Edition which celebrates the history, accomplishments, companies and individuals who have made the association’s membership key contributors to the Canadian economy.

Published in August in both print and digital formats, the 40th Anniversary Edition will be given to all CFLA members and to more than 7,000 executives with finance and procurement roles in the equipment funding sector. This publication will be a keepsake for everyone in the industry and we are hoping you will demonstrate your support for the CFLA and for the industry.

Members and sponsors are invited to contribute to the editorial content of magazine, as individuals, companies and thought-leaders. To share your memories, thoughts or send comments about the CFLA and it’s history, send your notes to Amy Bostock at [email protected]

Thank you for supporting your association.David Powell, President & CEO, CFLA

CFLA Member Commentary

Using Your Lease Management System as a Competitive Advantage

CANADIAN EQUIPMENT FINANCE | jUNE 2013 | canadianequipmentfinance.com6

association rePort

The Equipment Leasing and Finance Association’s (ELFA) Monthly Leasing and Finance

Index (MLFI-25), which reports economic activity from 25 companies representing a cross section of the $725 billion equipment finance sector, showed their overall new business volume for April was $7.5 billion, up 23 percent compared to volume in April 2012. Month-over-month, new business volume was up 10 percent from March. Year to date, cumulative new business volume was up eight percent compared to 2012.

Receivables over 30 days were un-changed in April from the previous two months at 2.0 percent. They were down from 2.7 percent in the same period in 2012. Charge-offs were unchanged from March at the all-time low of 0.3 percent.

Credit approvals totaled 77.2 percent in April, down from 78.4 percent in March. Seventy-two percent of participating organizations reported submitting more transactions for approval during April, up 50 percent from the previous month.

Finally, total headcount for equipment finance companies was up three percent from the previous month, and was unchanged year over year.

Separately, the Equipment Leasing & Finance Foundation’s Monthly Confidence Index (MCI-EFI) for May is 56.7, an increase from the April index of 54.0, reflecting industry participants’ increasing optimism despite continuing concerns over the economy and the impact of federal policies on capital expenditures. .

ELFA President and CEO William G. Sutton, CAE, said: “Both performance indices—the MCI as an indicator of future optimism about the direction of the U.S. economy, and the MLFI-25’s growth trend in new business activity—provide solid evidence that the demand side of the capital investment equation continues to pick up as the broader

economy strengthens. It is our hope that this trend pushes into the second half of the year.”

Paul J. Menzel, President and CEO, Financial Pacific Leasing, LLC, said: “Over the last four years businesses of all sizes have pursued a defensive strategy of austerity by right sizing their balance sheets, maximizing operating efficiencies, and optimizing cash flow, all while top line revenue growth has remained weak. This has kept many borrowers and lessees on the sidelines despite historically low rates. The anemic revenue story may be coming to an end as businesses seem to be going on the offensive and investing for growth, as this month’s MLFI data reflects.”

About the ELFA’s MLFI-25: The MLFI-25 is the only index that reflects capex, or the volume of commercial equipment financed in the U.S. The MLFI-25 is released globally at 8 a.m. Eastern time from Washington, D.C., each month on the day before the U.S. Department of Commerce releases the durable goods report. The MLFI-25 is a financial indicator that complements the durable goods report and other economic indexes, including the Institute for Supply Management Index, which reports economic activity in the manufacturing sector. Together with the MLFI-25 these reports provide a complete view of the status of productive assets in the U.S. economy: equipment produced, acquired and financed.

The MLFI-25 is a time series that reflects two years of business activity for the 25 companies currently participating in the survey. The latest MLFI-25, including methodology and participants is available below and also at http://www.elfaonline.org/Research/MLFI/

The ELFA produces the MLFI-25 survey to help member organizations achieve competitive advantage by providing them with leading-edge research and benchmarking information

to support strategic business decision making.

The MLFI-25 is a barometer of the trends in U.S. capital equipment investment. Five components are included in the survey: new business volume (originations), aging of receivables, charge-offs, credit approval ratios, (approved vs. submitted) and headcount for the equipment finance business.

The MLFI-25 measures monthly commercial equipment lease and loan activity as reported by participating ELFA member equipment finance companies representing a cross section of the equipment finance sector, including small ticket, middle-market, large ticket, bank, captive and independent leasing and finance companies. Based on hard survey data, the responses mirror the economic activity of the broader equipment finance sector and current business conditions nationally.

[Part 2 of ELFA Report]Fact Sheet: Equipment Finance in the IT / Computer SectorEvery year U.S. businesses, nonprofits and government agencies spend in excess of $1.2 trillion in capital goods or fixed business investment (including software/excluding real estate). ◉ Of the $1.2 trillion spending for business fixed investment, 51 percent or approximately $628 billion is financed through various forms to acquire all kinds of equipment

◉ The commercial equipment finance sector is key to capital formation in the U.S. and abroad and plays a vital role in supporting the U.S. economy

◉ According to information from the Equipment Leasing and Finance Association (ELFA), in 2011:

◉ Computer mainframes and servers represented 3.8% of equipment financing new business volume reported by ELFA member companies,

ELFA REPORT: New business up 23 percent year-over-year


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Canadian Equipment Finance is a Lloydmedia, Inc publication. Lloydmedia also publishes Payments Business magazine, Canadian Treasurer

magazine, Direct Marketing magazine and Contact Management magazine.

Visit us online at www.canadianequipment� nance.com

Fantastic publication-looks

spectacular--Jamie Born,

PayNet

Received your inaugural edition of Canadian

Equipment Finance. � e issue looks well done

and packed with valuable information on the industry.

Congratulations on a successful launch

Bill Phelan, PayNet IncI was pleased to receive your premier issue. I am hosting

a meeting aof a Lessor study group, similar to a dealer 20

group in Toronto next month and I would like to give the

members a copy of your magazine.Doug Moore

SommervilleAuto LtdI found the Premier issue awaiting my arrival at the o� ce today. I must

say it looks terri� c!David Chaiton, Torkin Manes

� anks for sending your kicko� publication. Arrived today. Greatly appreciated.

Well done !!David Hill, Dominion

Leasing Software

Love the magazine!!! Good job Steve!!! Already has some

great feedback!Rob Birnie,

Verus Valuations

Wanted to let you know that it looks great and

content is of value.Congrats!!!

J. Anthony Zambon, PayNet Inc

� e magazine looks great. Very professional - and

nice, clean lookYash Mody, Orchid Leasing

Congratulations on your � rst

issue!Amy Vogt, Equipment Leasing & Financing

Association

COMMENTS ON THE PREMIER ISSUE.


association rePort

down from 4.4% in 2010. ◉ PCs and workstations represented 6.0% of equipment financing new business volume reported by ELFA member companies, down from 6.9% in 2010.

◉ POS, banking systems and ATMs represented 0.2% of equipment financing new business volume reported by ELFA member companies, up from 0.1% in 2010.

◉ Software represented 4.8% of equipment financing new business volume reported by ELFA member companies, down slightly from 4.9% in 2010.

◉ Computer networking equipment represented 2.4% of equipment financing new business volume reported by ELFA member companies, down from 3.8% in 2010.

◉ Computer storage equipment represented 0.7% of equipment financing new business volume reported by ELFA member companies, up from 0.4% in 2010

◉ Other computer equipment

represented 4.2% of equipment financing new business volume reported by ELFA member companies, up from 2.7% in 2010.

◉ According to the 2012 “What’s Hot/What’s Not” Equipment Leasing Trends Survey released by the Independent Equipment Company in cooperation with the ELFA

◉ The high-tech/computer industry continues to operate on very low margins yet has a very large secondary market so volume is important.

◉ Over the past year, the high-tech/computer market has been status quo in terms of equipment finance industry preference.

About the ELFAThe Equipment Leasing and Finance As-sociation (ELFA) is the trade association that represents companies in the $628 billion equipment finance sector, which includes financial services companies and manufacturers engaged in financing capital goods. ELFA members are the

driving force behind the growth in the commercial equipment finance market and contribute to capital formation in the U.S. and abroad. Its over 550 members include independent and captive leasing and finance companies, banks, financial services corporations, broker/packagers and investment banks, as well as manu-facturers and service providers. ELFA has been equipping business for success for more than 50 years. For more informa-tion, please visit www.elfaonline.org.

ELFA is the premier source for statistics and analyses concerning the equipment finance sector in the United States.

ELFA believes that information and education about available options regarding investment in equipment are important to all businesses. ELFA offers resources, including types of finance products, a loan/lease comparison, a glossary of terms, an analysis to help determine suitable financing options and topical bylined articles available for reprint free of charge.


CoActiv Capital partners rebranded as element financial (usa)Toronto--Element Financial Corporation, one of North America’s leading independent equipment finance companies, has commenced rebranding the operations of the recently acquired CoActiv Capital Partners under Element’s North American identity. Effective immediately, the legal name of CoActiv Capital Partners, Inc. has been changed to Element Financial Corp. doing business as Element Financial (USA). In conjunction with the rebranding, Element Financial (USA) has launched its new website at www.elementcorp.com.

“For the past several months, we have been working to integrate our operations to enable us to quickly deliver the benefits of this cross-border alliance to customers in both Canada and the United States,” said Don Campbell, CEO of Element Financial (USA). “I’m very excited that our employees and customers are already finding ways to use this broader market presence to build deeper, stronger and more profitable relationships.

“With a well-established US origination and servicing platform as an integral part of our offering, Element now has the geographic reach, funding capacity, processing systems and leadership resources to support the vendor financing needs of equipment manufacturers, dealers and distributors across a broad range of industries throughout North America,” said Bradley Nullmeyer, President of Element Financial Corporation.

Element Financial Corporation completed its acquisition of CoActiv Capital Partners from Marubeni America Corporation and Marubeni Corporation in December 2012.

With total assets of approximately $1.5 billion, Element Financial Corporation is one of North America’s leading independent equipment finance companies. Element specializes in designing and implementing private-label sales-aid finance programs for equipment manufacturers across North America.

news digest

8 For breaking news and in depth news features, visit our website at www.canadianequipmentfinance.com

TORONTO--Element Financial Corporation and GE Capital have agreed to a definitive asset purchase whereby Element acquires GE Capital’s Canadian fleet portfolio and the two companies form a strategic alliance to deliver comprehensive vehicle fleet financing and management services to cross-border customers in Canada and the United States.

Under the terms of the Agreement, Element will acquire GE Capital’s existing Canadian fleet portfolio for consideration of C$570 million (the “Acquisition Transaction”) subject to adjustments, along with the GE Capital Canada fleet operational resources required to service this portfolio. These Canadian operations will be combined with TLS Fleet Management, Element’s existing fleet management business.

In addition to serving the domestic Canadian fleet industry, the combined entity operating under the Element Fleet Management brand will serve Canadian customers under a Strategic Alliance Agreement (the “Strategic Alliance”) between Element and GE Capital Fleet Services. Through the long-term Strategic Alliance, the two companies will jointly pursue Canada/US cross-border fleet management opportunities.

“This alliance with GE Capital Fleet Services enables Element Fleet to bring more comprehensive fleet management technologies and solutions to our existing customers

at the same time that it expands our addressable client base by giving us the capacity to deliver fleet management services to customers with needs on both sides of the Canada/US border,” said Steven K. Hudson, Element’s Chairman and Chief Executive Officer.

“This strategic alliance creates significant advantages for our GE Capital Fleet Services customers operating fleets in Canada,” said Kristi Webb, President and CEO of GE Capital Fleet Services. “Our customers will enjoy a broader range of services, more geographic coverage and more feet on the ground in rapidly growing Canadian markets, and diversified capital funding sources to support their fleet needs.”

Kathy Lee, President and CEO of GE Capital Canada, said: “We are pleased to announce this alliance with Element Fleet Management and we would like to take this opportunity to acknowledge the employees’ great work in serving GE Capital Canadian Fleet customers for so many years. This alliance will give our customers the benefit of access to the services and network of one of the most respected fleet management companies in Canada.”

The Agreement provides for customary closing conditions, including approval under the Competition Act (Canada). Subject to the satisfaction of such conditions, the Acquisition Transaction is expected to close on or about June 28, 2013.

GE Capital, Element Financial establish strategic cross border fleet services alliance


news digest

MISSISSAUGA--GE Capital’s Commercial Distribution Finance (CDF) business is adding resources to support Canadian manufacturers and dealers of agricultural equipment. Through increased credit capacity and an expanded, experienced sales force, CDF plans to significantly grow its presence in this important sector of the economy.

CDF works with manufacturers and distributors to create inventory finance programs that enable dealers to stock a broad selection of products. Inventory financing,

also known as floorplan financing, is an important element of a successful manufacturer-dealer business model. Manufacturers and distributors can benefit from enhanced product flow and increased sales opportunities, while dealers can obtain improved terms and credit availability.

CDF currently has 30 agri-cultural equipment manufac-turer customers who supply more than 200 active dealers across the country. Overall, CDF has relationships with 500 manufacturers and 4,500 dealers nationwide in a variety of sectors, including lawn and

garden, motorsports, recre-ational vehicles and marine products.

“We have more than 30 years’ experience in the agri-cultural equipment industry so we understand its unique financial requirements,” said Howard Shiebler, president and CEO of CDF in Canada. “With our Canadian focus, North American alignment and global capabilities, we can help manufacturers develop specialized financial solu-tions tailored to their dealers’ needs.”

Kevin Crellin has joined CDF as the lead agricultural sales manager in Western

Canada. Crellin had been with Western Financial Group and its Agrifinance division since 1993, most recently as vice president of sales and marketing. He graduated with honours with a Bachelor of Commerce degree from the University of Manitoba.

Scott Ferguson, based in Milton, ON, will serve as sales manager in Ontario and Quebec. He is a veteran in agribusiness finance, having previously worked with John Deere Credit, De Lage Landen and Agco Finance. Ferguson holds a Bachelor of Arts degree in economics from Concordia University.

GE Capital adds dEdiCatEd tEam to Expand Canadian aGriCultural EquipmEnt FinanCinG

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news digest

Canadian CommErCial lEndinG risEs in First quartErBy John Tilak, Reuters

TORONTO--Commercial borrowing by small and medium-sized businesses in Canada climbed in the first quarter, driven by robust domestic and global demand, a PayNet survey showed on Wednesday.

PayNet, which tracks commercial financing for millions of North American small and medium-sized businesses, said its Canadian Business Lending Index rose to 194, the highest level since it was created in 2005.

The index rose 4 percent in the first quarter from the fourth quarter and was up 29 percent year-over-year.

“The demand for our goods and

services, and our resources is definitely fueling the increase in investment by Canadian businesses,” Anthony Zambon, director of PayNet Canada, said.

“The data shows small- and medium-sized businesses are resilient and continuing to invest, with the prospect of supporting economic growth in the near future.”

Small- and mid-sized businesses have been stepping up investment in the construction of plants and commercial buildings and in machinery and equipment, he added.

The advance marked the 10th consecutive quarter of growth since the index bottomed out in 2010, and the seventh straight double-digit advance on a year-over-year basis.

The PayNet data, which tracks lending across sectors including manufacturing, retail and transportation, showed that commercial loan growth in Canada outstripped growth in the United States.

“The U.S. was been wallowing,”

Zambon said. “The growth trend of investment by U.S. private companies is slowing. The U.S. small business lending index has fallen for the third month in a row.”

The commercial lenders include independent finance companies, big banks and nonbank players such as machinery makers, whose loans and leases to customers are secured against the equipment sold.

PayNet’s Canadian unit collects data on more than 700,000 loan contracts worth more than US$47 billion.

Other data from PayNet showed higher loan delinquencies.

Moderate loan delinquencies - defined as those being late by 30 days or more - rose to 1.35 percent of total loans in March from 0.80 percent in December. It was the highest rate in about a year.

Severe loans in arrears - those behind more than 90 days -climbed to 0.38 percent in March, from 0.29 percent in December.


By Thomas Ware

P reviously, in Part 1, the first six “secrets” were covered. Developing a game winning

credit scoring strategy means that you have to believe in the inherent merits of credit scoring and define what you want it to predict. As you make your choices, remember that good data is at the heart of credit scoring. Finally, a more accurate assessment of a borrower’s historical patterns and successfully melding both the art and the science of a scoring model are keys to providing additional lift to your credit decisioning process. In Part 2 we cover secrets #7-12, including how scoring can have a significant impact on a lender’s bottom line.

#7 - “Slice and Dice”Considering how variables will affect different segments of an applicant population is important for a number of reasons. Transportation equipment borrowers are different than medical equipment borrowers, who are different than office equipment borrowers. “One size” can fit all, but not nearly as well as a more focused custom product will. While historically a lack of sufficient data to slice into segments, and/or a lack of willingness to invest in building

multiple different scorecards or models has led to a “one size fits all approach,” neither of those constraints exist today. And segmentation is by no means limited to equipment types. It can mean new borrowers vs. old borrowers, or small borrowers vs. big borrowers, or borrowers in one segment of an industry vs. another (e.g. for-hire truckers vs. private fleets) – the list of possible segmentations is long, and largely dictated by the market segment being modeled. An experienced modeler will know the most common segmentations, but this is another area where having an experienced credit professional working with the modeler will produce the best results by far.

Another way of thinking of this, from the mathematical side, is that while the mathematics, generally multivariate regression, is brilliant at simultaneously evaluating tens of thousands of transactions and coming up with optimal weights for each variable, it doesn’t have an ability to do segmentation on its own – it won’t give back an answer saying “variable X is very predictive for borrowers located in Western provinces, but not for borrowers in Eastern ones” – unless the modeler asks that question by testing that segmentation. In this example, without the segmentation, the mathematics would simply say “this variable is fairly predictive, but not very predictive” because the majority

of applicants are located in Eastern provinces – and the potential predictive lift would be lost. While such a geographic distinction may at first sound silly, an experienced equipment lender might know to look at such a distinction because the variable might primarily impact borrowers involved with natural resources.

#8 – Beware the “Tyranny of the Majority” (or “Trust, but Verify”)Scoring works on probabilities – “What will work the greatest percent of the time?” But the modeler must also strive to prevent the “Tyranny of the Majority” by which I mean situations where a model variable works for the large majority of cases, but where it really causes trouble for a significant minority. A classic example is a model variable that is the sum of days past due now, for all of a borrower’s accounts. Overall, it’s a very predictive variable, but there’s a problem: this variable, as constructed, is subtly biased against large borrowers. For example, a borrower with 50 accounts that are on average five days past due is going to have a total of 250 days past due, which in general (and therefore in the model) is a very bad thing. It’s not hard to solve this problem, but it must be recognized in order to be solved. An easy solution here would be to redefine the variable as the sum, for each of a borrower’s accounts, of the number of

Confessions of a Closet Quant Jock

Feature rePort


days now past due minus ten (or some such number) which prevents a large number of insignificant delinquencies from adding up to a large delinquency number.

The key point though, is that while models do work overall and on average better than other decisioning methods, the modeler should not stop there. It is possible to create an even better model by making sure that the model is handling even the less common situations (“outliers”) as well as possible. This can be done in two ways. The first is “top down” statistically, by performing segmentation analysis, guided by the question: “are there some borrowers or situations where this variable could create a biased result?” The second is “bottom up” by looking at how the model scores a wide range of individual deals and making sure that there aren’t cases where the model is doing something that doesn’t make sense, because common sense should never be ignored. Models should be based on the intersection of that which is statistically sound, and that which also makes sense.

#9 – Test the Score & Decide How to Use ItWarren Buffet, the “Oracle of Omaha,” famously warned fellow investors to “beware of geeks bearing formulas” while railing against complex derivative securities which he called “financial weapons of mass destruction.” In some senses he is right; models, if used improperly, can produce terrible results. A perfect example of this is ground zero of the recent recession, the residential mortgage crisis in the U.S. At its core what went wrong is that lenders used scoring models and the associated historical default rates based on owner-occupied, 20% down, income verified, fixed rate, level payment mortgages – to “predict” default rates on investor-owned, no-money-down, interest-only, step payment, “liar loans.” Were the disastrous results that followed the fault of the models? Not in the least. The models were perfectly good for what they were built on and built for, and the fault lies with those who sold the idea that they could be used in such a radically

different situation.So using a model to predict behavior

in the type of situation it was built for is critical. But beyond that initial broad requirement there are a number of questions to answer and decisions that need to be made, ranging from fundamental ones down to very specific details of usage that the user will probably want to change over time. Does the score really work? And up to what dollar amount? Does it work for all business segments? Do I trust it enough to do auto-approvals? And/or auto-declines? What should the score cut-offs be? Do I want to reduce losses or increase approvals, or both? How great are the benefits we expect to see? Are we really confident that all the necessary testing has been done and that it’s time to start using the score?

While all these questions need to be answered before using the score, the fundamental analyses on which the answers are based are not difficult to perform and the results are quite accurate. Indeed, there is a strong argument to begin here – test a score that looks promising and see what it can do for you. The benefits of scoring are so great that it is really a strategic mistake not to at least do the tests.

There are two main analyses. The first is the retro analysis, calculating what the score would have been on deals your institution booked in the past and determining what the eventual bad rates were for different scores. This analysis can be done for different lines of business, for different borrower exposure amounts, for new vs. repeat customers, etc. This tells you what to expect from the score. The graph below is a typical, actual example. In this case, of the 3,003 deals that scored 701 or higher, only 26 went bad, while at the other extreme, of the 529 deals that scored 580 or lower, 301 went bad.

The second key analysis is comparing current credit decisioning practice to the scores given by the model. Given the retro analysis example above, one would hope that the credit analysts are approving all the deals that score above 680 (since their bad rate is 0.9%-2.7%) and that they’re declining all the deals that

score 600 or below (since their bad rate is 40%-57%). Without the benefit of having the score, however, it is virtually certain that the analysts are approving some very low-scoring deals and declining some very high-scoring deals.

Using this differential, current credit decisioning practice versus how one would decision deals if the score were available, it is easy to calculate a “swap set” – the deals that will now be approved that would have been declined, that are swapped for deals that would have been approved that will now be declined. The swap set generally produces two major types of benefits. First is a reduction in credit losses. There is no reason why credit losses “have” to be what they are, and avoiding them has a direct impact on the bottom line. Second is an increase in approvals. Feedback on the credit granting process is usually asymmetric – one clearly sees the deals that were approved that shouldn’t have been, but few people see the good deals that were declined, and their number can be large. Depending on institutional objectives, score cut-offs can be set so that all the benefit is shifted either to reducing losses or increasing approvals, but most institutions prefer to split the benefit more evenly.

When actually implementing a score for the first time it makes sense to go slowly and examine the swap set deals carefully. Moreover, while one can and should primarily use the bad rates found in the retro analysis to set score cut-offs, it is also useful to see where the differences are by score and transaction amount. Identifying where the score’s recommendations deviate from current practice helps in determining the cut-offs and the maximum transaction amount for auto-decisioning. This can be done by mapping out recent applications on a graph with the score on the Y-axis and transaction amount on the X-axis, and showing each application as either an “A” for approval or “D” for decline, as follows:

In the hypothetical example above, the lender’s current practice for applications under $200,000 is generally to decline those scoring below 640 and approve those scoring over 680. There are two exceptions in each direction to

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this general rule, and a circle is drawn around them in the diagram above. In cases where I’ve actually done analyses like these, upon careful review the low-scoring approvals almost always turn out to be mistakes, and the person who approved them wishes they hadn’t. That said, this is also an opportunity to verify that these aren’t part of some special segment of business where approving lower scoring credits might be okay such as deals that are full vendor recourse. Or, are these borrowers doctors with seven-figure incomes? The high-scoring declines, on the other hand, are usually deals that have something wrong with them that is not credit-related per se, such as ineligible equipment types, environmental issues, geography or some inherent structural problem.

In the example above, the clear, general pattern of approving above 680 and declining under 640 holds true for transactions sizes up to about $200,000 at which point the pattern becomes less clear. So everything equal, with findings such as these, establishing a policy for applications under $200,000 of approving over 680 and declining under 640 would be a reasonable way to start. Over time, the grey-area, manual review band of 640-680 in this example can probably be narrowed, and the dollar amount up to which scores are used increased. Moreover, I’ve always thought it strange that an applicant who would automatically be declined for a small dollar amount might be approved for a much larger dollar amount. Except in unusual circumstances a passing credit score should be a requirement for large transactions, in addition to whatever other requirements might be appropriate for the amount.

There are additional considerations in setting cut-offs. What is the economic impact of a deal going bad? What is the impact of turning down a good deal? How important is speed? Is the credit staff stretched to keep up with the volume? A lender with strong collateral, high rates, and vendors who demand speed in exchange for deal flow should be willing to auto-approve more. A lender whose primary objective is to minimize losses may auto-decline low-scoring

credits, but then manually review any credit before approval. A reasonable way for a lender to get started is operating on a dry-run basis, using the score as more of a review rule, or simply as another factor for analysts to take into consideration.

Going from “review rule” use of a score to automated decisioning requires additional credit policy that limits the circumstances under which an automatic credit decision will be generated. Besides setting the cut-off scores for automatic approvals and/or declines, one should also put in place data sufficiency requirements. So for example, a borrower with a high credit of $3,000 or just six months of history probably shouldn’t be automatically approved for $100,000 for five years. One thing that scores today don’t do is measure “Capacity” since it would require infinitely more data to build a multivariate regression-based score that said a borrower was safe for $X but unsafe for $Y. Instead, most lenders use the “Comparable Credit” concept, and limit auto-approvals to some fraction or multiple of the borrower’s previous high credit.

Similarly, many lenders require at least a couple of years of history before granting an auto-approval, unless a study has been done validating the score’s predictive powers specifically for new

businesses. In practice, however, this is less of an issue than it seems because new businesses generally tend to get mediocre, mid-range scores that are below most auto-approval minimums. Finally, most lenders, at least at first, prefer to put “training wheels” on their auto-decisioning, by requiring manual reviews for any applicant that has, for example, ever been bankrupt, or 90 days past due, or that has any other characteristic broadly deemed as undesirable. Manual review rules like these are fine, and usually are moot because deals with such negative characteristics are quite unlikely to score high enough to be auto-approved. Moreover, if it turns out that the manual decision in these cases (or an identifiable segment of the cases) is the same as the auto-decision would have been without the review rule, then the review rule can be peeled back over time.

Although auto-decisioning has many benefits, it should not be assumed that a lender that is unwilling or unable to auto-decision cannot benefit from scoring. To the contrary, such lenders can use a score’s recommendation to help guide an analyst’s decision, and such collaboration can even be assured by adopting credit authorities that require an analyst to get a second signature to approve a low-scoring deal or decline a high-scoring one.

It is important, however, that everyone

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involved realize that if there is no change in the institution’s decisioning practices, no swap set, that the main benefits of scoring won’t be realized. Decision speed will be improved and processing costs should be lowered, but the biggest benefits, reduced losses and increased approvals, won’t be realized unless some credit decisions change.

Finally, it is important to understand that scores are built to “rank order risk” (e.g. a 600 is riskier than a 700), but not to predict specific default rates. Actual default rates change with the overall economic environment and other factors. As such it is important to recognize that while the recently observed default rates may provide a good estimate of what future actual default rates will be, it is only an estimate and “your mileage may vary.” In turn, this also means that default rates need to be monitored over time, and that score cut-offs will need to be adjusted based on those results. Lenders who failed to do this were probably not happy with resulting default rates during the recent recession, and may have incorrectly concluded that their score did not work, when in reality it did exactly what it was supposed to do, rank order risk.

This issue exists with all types of scores. A typical example showing default rates for static pool vintages from 2000 to 2009, each with 18 months of aging is below. To the extent that sufficient historical data is available to do an analysis similar to this from the start, it is useful to establish an historical range of default rates that have resulted from each score tier, and set expectations accordingly.

#10 – Implementation: Institutional Acceptance & “The Human Factor”There are two reasons why broad staff acceptance of scoring is important. The first is the basic need to have everyone in the organization pulling in the same direction – if senior management is going one way, while the front line staff is going the other, the results are never pretty.

Some employees are concerned that credit scoring will cost them their

jobs. The good news here is that I have never heard of this actually happening. Because the adoption of scoring is a gradual process, it will mean that there will be less future hiring, even if there is substantial volume growth (which quicker credit decisioning can create). Total credit headcount may gradually decline through natural attrition or transfers to other departments, but employees really shouldn’t be concerned about layoffs. Rather, scoring frees them up to focus on the more challenging borderline deals and on larger deals.

Other employees can be defensive, taking it as a matter of honor that they are “better” at adjudicating credit than the score, and go out of their way to try to prove it. This is most commonly an issue when presenting retro analyses that by their nature highlight that a large portion of the low-scoring deals went bad. The key here is for people not to take it personally – an automobile goes faster than even the fastest Olympic runner, and no one has a problem with that. It’s also true that there are also many areas where human expertise beats machines, particularly working with large complex credits.

The other reason why staff acceptance is important is less obvious. There is a real opportunity for synergy between Man and machine here: if they work well together they will produce an even better result. The scoring models I’ve built al-low users to “look inside” to see why the model is saying this applicant is good or bad, because then the credit analyst can better evaluate the model’s recommenda-tion on a particular application. Maybe the analyst will look at the key factors sited and say “hmmm, those are good points; I hadn’t focused on those” – or maybe the analyst will say “oh, that’s why the score is the way it is; I happen to have information that the model doesn’t have, so I know for a fact that this issue isn’t a problem, and should therefore discount the score on this application.” And this is actually a key point – in general when analysts look at the same information that the scoring model has, and reach a different conclusion than the model, they are usually wrong. But when the analyst has material “exogenous” information

that the model doesn’t have then the ana-lyst’s decision is more likely to be correct.

Finally, and most basically, credit analysts must understand the meaning of score values themselves. They need to know whether a score is predicting the probability of loss or of default (and if the latter, how is it defined). Most “Empirically Derived Statistically Sound” scores predict default, while many Expert Systems type scores predict loss; and some scores combine the two. The analyst also needs to know whether the score they see is presented on an absolute basis or on a relative basis (akin to “grading on a curve”). Scores that are calibrated and presented on an absolute basis have the advantage of consistency over time – a score of X today means the same thing as a score of X a year ago – and what bad rate has historically been associated with that score. Many such scores are further calibrated to make comparisons simpler by using a standard rule such as “20 points doubles the odds” meaning that if the good-to-bad odds are 10-to-1 at a score of 650, that a score of 670 means odds of 20-to-1.

The other common way that scores are calibrated and presented is on a relative basis, and this is usually done on a per-centile basis, on a scale of 1 to 100. The advantage of this method is that the ana-lyst can easily compare how a particular applicant compares to other companies. It has the disadvantage, however, that a score of X today does not mean the same thing as a score of X a year ago. In my opinion, the ideal way to present scores is both ways, showing the user both an ab-solute score and a relative score.

The bottom line is that widespread score education and understanding are critical to getting maximum meaning and benefit from scoring. Not only does this maximize the potential for real Man-machine synergy, producing a result bet-ter than either could do alone, but it also minimizes the risk of misunderstandings and sub-optimal decisions being made based on misconceptions. The combina-tion is key, and as Desmond Morton, the Canadian historian wrote “A cautious people learns from its past, a sensible people can face the future. Canadians, on the whole, are both.”

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#11 – Score Management is an On-going Process, Not a One-time EventTime is an important dimension to cred-it scoring in a variety of ways. No mat-ter how much analysis and education is done upfront, real trust still takes time to grow. Typically a lender will start using a score without any auto-decisioning, and then move to auto-decisioning just a small portion of their deals. In many ways this first step is the toughest, and the portion of deals auto-decisioned may be only 5%. But this should be thought of as a Normandy Beach, a real accom-plishment that though initially small in its absolute magnitude, laid the founda-tion for much more widespread success thereafter. Once auto-decisioning is ac-tually started it tends to grow rapidly, as people see additional classes of applica-tions that clearly can be auto-decisioned (e.g. good but not excellent credits, somewhat larger deals, other market seg-ments, etc.) Before long 15%, then 30%, then 50% will be auto-decisioned. And the percentage will continue to grow, though more slowly, as the remaining deals are tougher to auto-decision (and the toughest to gain consensus on for auto-decisioning).

Growing the auto-decisioning percent-age over time is an important activity, but, as noted earlier, just as important is monitoring score performance over time. Is the score performing as expected? Do high-scoring deals have low bad rates and low-scoring deals have high bad rates? Are the bad rates for each score category what they were expected to be? The analysis done prior to adopting the score is important, insightful and useful, but it’s never 100% the same as actually using the score.

First is the problem of “Reject Inference” – how does one really know what the performance of deals that weren’t approved and booked would really have been? PayNet has conducted some interesting research in this area, and because we have the data from essentially all the major lenders in many equipment categories, we’ve been able to calculate what the actual bad rates were on deals declined by one lender, but then approved

by another lender. The results have been very reassuring as they were consistent with the bad rates predicted by the score. But even this approach isn’t quite absolute “proof” in that not all declines are subsequently approved somewhere else, and there is presumably some bias to which applicants are eventually approved vs. not.

Theoretical nuances aside, the real issue to be concerned with is change in the underlying lending business. At the extreme, for example, a lender that used to do only direct business that now does only broker business, cannot expect to have the same bad rates for a given score that it saw in the retro analysis. Similarly, a captive lender going into non-captive lending, or indeed any change in the positive or negative selection tendencies of the applicant population coming through the door will affect performance. A lender now charging high interest rates and advertising E-Z credit will have higher bad rates for a given absolute score than one with low rates and tight credit.

Scoring also enables credit manage-ment to quantify the quality of applica-tions being submitted, on an absolute basis, as well as on a relative basis, over time. For example vendors can be evalu-ated by the average credit score of deals they submit, and by the average score of deals they book – and if the average score of the deals a vendor books is signifi-cantly less than the average score of deals approved for that vendor, then it is quite likely that the vendor is negatively select-ing, i.e. only booking with you the deals that no one else approved. And knowing the average credit score, a profitability estimate for each vendor (or salesperson) can be calculated without waiting for the default to occur, and the unprofitable vendors better managed, given higher rates, ultimatums, or cut-off. Simi-larly, management can now confidently evaluate securitizations, syndications and portfolio acquisitions, to determine whether there is any bias toward higher or lower credit quality selection, and re-act accordingly.

Overall portfolio monitoring by score is important because even if an appropri-ate minimum credit score is set, and the scoring model is working exactly as it is

supposed to, the quality of the applicant population will affect the lender’s overall average portfolio quality. In the sim-plistic example below, both lenders have set 650 as their cut-off, approving (and booking) everything over and declining everything under. Yet the lender with the stronger applicant pool has a much bet-ter portfolio, with an average score of 680 compared to an average of just 660 for the lender with the weak applicant pool:

Other macro analyses are possible and worthwhile as well. One bank, for example, looked at the distribution of credit scores that were coming from ap-plicants who worked with loan officers in branches. What they found was an ab-normally high number of applicants that scored just high enough to be approved, and an abnormally low number of appli-cants that scored just under the cut-off. Upon investigation they found that the loan officers were “gaming” the system for marginal applicants, doing things like opening a checking account on the spot so the applicant could qualify as an “ex-isting” bank customer. Armed with this information from monitoring, their credit policy was changed to prohibit rescor-ing (i.e. if the applicant did not qualify with the data initially entered, then they couldn’t qualify for an automated ap-proval by changing the data).

Another area to monitor is decision overrides, and the reason for the over-rides. Even if policy says that deals scor-ing below 600 should be declined, there will probably be some that get through on appeal. It is therefore very useful to develop a set of override codes for each type of override to distinguish between those that are essentially for sales con-siderations, versus those that are based on important information not within the scope of the scoring model (e.g. a start-up that just got $100mm of venture capital funding), versus those where the risk of default is high, but for collateral reasons the risk of actual loss is very low. Us-ing these codes does two things. First, it makes it clear how much business is be-ing done on an exception basis. Second, it makes it possible in the future to calcu-late what the actual bad (and loss) rates are on these deals. And in every case I

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tecH rePort

By Glenn Miller

Leasing is as old as recorded human history, showing up in legal documents all over the

Ancient Near East. Land leases in ancient Mesopotamia might include technology of the day (e.g. agricultural implements) and tools of the day (e.g., oxen for farming), or might be simply leasing of meeting halls for fraternal organizations in ancient Palestine. There were contractual penalties for ‘damaged returns’ (e.g. the “Ox” laws in the Laws of Hammurabi) and ‘index-based’ leases in ancient Egypt.

But even though the basic principles of leasing have remained the same, leasing organizations have often had to adapt leasing structures to different types of underlying assets. Long-term leases of airplanes look very different from short-term leases of laptop computers. Short-term leases of luxury automobiles (with vibrant secondary markets and strong collateral values) look very different from long-term leases of enterprise software (with virtually no secondary market nor collateral value). For example, a Macquarie lease of a large $2M IBM mainframe may only involve 25 serial numbers in one physical location, whereas a lease of $2M of PC’s may contain 25 hundred serial numbers in 100 physical locations--a different management task alltogether.

The use of information technology for organizational success has been greatly facilitated by the availability of lease financing. From the earliest days of mainframes (in which leasing was used primarily as a source of capital), to the current days of distributed assets (in which leasing is used mostly for asset and risk management), lease financing has

served the economic ecosystem well. But information technology--as a subset of ‘high technology’--has also created some new challenges for lending and leasing organizations.

Realities of Information Technology TodayIT assets are still ‘assets’ --they are still enablers of economic production--but their usage, rate of innovation, and IT market dynamics reveal significant differences from other traditional assets. Six differences are especially relevant to understanding their uniqueness in a leasing context:

one. There is a growing dependence on Information Technology (IT) for organizational viability and success. The days when a telephone order entry operator could reasonably respond with “the system is down--can you call back later?” are long gone, and web users will abandon an inactive web catalog page in less than 5 seconds. Demands for “high availability” and “fault-tolerant” systems have increased dramatically in the last 5 years. The reliability requirements of these assets are on par with that of phone systems--absolutely essential to business survival, and matched by very few other types of assets.

two. Not only are organizations as a whole becoming more dependent on IT, but each business function within an organization is becoming more IT-dependent. IT has become pervasive in design, planning, sales, marketing, production and service delivery. This can easily be seen from a sampling of the major categories of business software today: CRM (customer relationship management), ERP (enterprise resource planning), SCM (supply chain

management), robotics and control equipment, service and call center systems, remote monitoring services, technician hand-held units, and GRC (governance, risk, and compliance management software).

tHree. Not only are IT assets such as PCs and laptops being deployed into more business functions, but IT-technologies are increasingly being embedded into other assets. It almost seems like there is an Intel chip or an ARM processor in almost every other kind of asset nowadays, and that there is an Apple iPad application for interacting with all of those assets! IT technologies--increasingly miniaturized--are present in the countless RFID tags, smart-labels, POS extensions, geo-tracking networks, sensors, medical equipment, automobiles, store fixtures, and even clothing. This can make the technology components difficult to return, replace, or even access in some cases. Macquarie faces the challenge almost daily of learning how to isolate and evaluate the IT component of any asset it is asked to lease.

Four. Although most product manufacturers like to innovate within their product lines (for customer and business reasons), the rate of change in the IT area seems to be one of the highest in history. One need only look at Intel CPU release timetables (new variants of chips come out every quarter, and major refreshes every 18 months). Smartphone vendors offer new versions of their phones every quarter, and PC manufacturers refresh their product lines every 12-18 months. The drop in resale value of a laptop computer bought yesterday and sold a day later is almost as bad as that of a new automobile driven off the lot! This makes obsolescence risk

Not Your Father’s Lease - The Unique Requirements of Information Technology Leasing


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skyrocket. Five. Changes in the

technology industry can radically affect secondary markets for assets. Buying a competitor and then shutting them down is a tool very much in use today, and the IT industry is not exempt from such tactics. We have notable cases every year of where a dominant market player will buy a vibrant start-up and silence them though ‘integration’. [“M&A” is sometimes known as “Murder and Acquiescence” for such reasons.] Some firms with excellent customer successes are bought for their intellectual property, and the products become ‘less supported’ than those of the acquiring firm.

six. Some of the systems undergoing the most rapid change are those which are end-user systems (eg, smart phones, PCs, laptops, tablets). How the user interacts with these systems is undergoing rapid change. In the computer industry, we historically moved from paper-tape to punched-cards, then to keyboards, and then to keyboards and mice. We have supplemented keyboard-plus-mouse with stylus-input, then added finger-touch and recently added ‘multi-touch’ and gestures. We have had voice interactions for about a decade, and vision (eg, eyeball tracking, motion recognition) technologies are in the market today. Some technologies acquired today will not be able to support the ways users need to interact with the system tomorrow. Forecasting these changes are very difficult and so business practices must be vigilant about emerging technologies. For example, at Macquarie,

our iPhone leasing program in Europe is radically different from our more traditional Dell/HP/IBM server leases in Canada or our basic medical IT leasing structures in the US--largely due to the volatility of the smartphone/tablet market.

Implications These somewhat unique factors about IT systems and assets have important implications for how they are used, managed, and replaced.

◉ IT assets are distributed widely, geographically and politically, requiring a lot of ‘touch’. Most office workers today require constant access to a desktop system, occasional access to a laptop system, and frequent access to a mobile device (eg, smartphone or tablet). To inventory and replace these systems requires significant management investment and migration labor, often exercised over wide distances and at many locations. Global geography is another complicating factor, due to geo-political factors such as legal, tax, export, FEX/currency, and supply restrictions. And, organizationally speaking, there are always pockets of resistance to corporate centralization and standardization policies--business units might prefer one brand over another, or require a faster refresh than that allowed by HQ.

◉ IT assets need refreshing faster (2-3 years) than ‘book’ depreciation timelines (3-5-7 yrs). It is common for laptops to have 18-24 month refresh cycles and desktops to have 3-4 year cycles. Equipment that is critical to new business


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initiatives, however, may be refreshed at any time earlier--since it is seen as strategic to business competitiveness. In standard accounting for depreciation, this can create significant challenges to managing the financial profiles of a business. And--consequently--for leasing structures that depend on depreciation values, this challenge can also be very real.

◉ IT assets often contain sensitive data. Information technology is about ‘information’, and much of this information must be protected in various ways. Customer data, intellectual property, insider financial information, and even employee PII (personally identifiable information) must be controlled. In many cases, regulatory requirements are very strict and penalties for a security breach or negligence can be catastrophic. And, as computer capabilities continue to increase, more and more critical data is processed and stored on these assets. Mishandling of the asset may involve mishandling of the data--with significant operational and legal risk. Clients have virtually forced Macquarie to develop full-blown , enterprise-class capabilities in this area--just to be able to help mitigate this risk when assets are returned.

◉ Changing business requirements may require unplanned refreshes of a large number of IT assets. Obsolescence risk is not just about age or technology being current--it can be created by external forces. In the healthcare field,

the mandating of hard disk encryption requirements for medical privacy forced many to upgrade equipment early, as did bank regulation that restricted screen viewing angles on teller workstations did earlier. Software vendors can create their own forced refreshes, by only offering ‘new features’ on newer equipment, or by increasing the cost of support contracts on older technology.Investment risk for IT assets is often

higher than for non-IT (or ‘less-IT’) assets, and requires expert knowledge of this market (ie, not just a spreadsheet extrapolation!). Many of the above factors are relevant in each IT leasing arrangement, and risk mitigation is a major business imperative for firms who wish to serve their clients in this area.

Consequences for Lessors and LendersTo serve this somewhat complex and ever-changing market, lenders must have the ability to provide their clients with IT-focused services, and provide these in a way which complements their other offerings. These IT-focused services are a direct consequence of the importance and pervasiveness of IT assets: ◉ Customer Lifecycle costs for IT assets (e.g., logistics, support, migration labor) are greater than invoice costs --clients need help with basic Asset Management.

◉ Faster refresh requirements (2-3 years) require equity-based leasing due to invoice costs--clients need Operating

Lease structures. ◉ Unplanned refreshes require easy-out leases--clients need flexible structures.

◉ Data security risk is very high--clients need lessors with strong capabilities in data destruction compliance processes.

◉ Traditional asset lessors may need a partnership with an IT-specific lessor--clients need to manage capital centrally and with a select group of preferred vendors.

ConclusionMarket demand for IT asset leasing is growing, and traditional lenders/lessors will face both opportunities and threats in addressing this complex market for their clients.

In some cases, traditional lenders may decide to grow their own expertise and capabilities in this area, but many will choose to develop alignments and relationships with IT-specific lessors. In the fast-paced world of information technology, it is often easier, less-expensive, and shortest-time-to-quality to take the latter approach.

In all cases, though, the requirements will change again and change often--and the company that decides to ‘go where the customer need is going’ will create processes and relationships to allow them to help their clients with those future needs.

about the author: Glenn Miller is VP of Technology of Macquarie Equipment Finance. He brings over 30 years in the technology industry and the unique perspective of an executive who has served in both CFO and CIO roles during his career. Macquarie’s Strategic Advisory Services (SAS) provides complimentary consulting services to help customers more cost effectively manage their technology assets throughout their lifecycles.

Information Technology Solutions

ADD Capital Corp.MarkhaM address:500 Cochrane Dr., Unit 2Markham, ON L3R 8E2Bill Patterson ([email protected])905 940-2151, ext 235

Burlington address;5045 South Service Road, Suite 102Burlington, ON L7L 5Y7Dave Ralph ([email protected])905 631-8001, ext 400

Common Sense Leasing • New Brokers Welcome • Reasonable solution to A credit declines


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By Mike Cumbry

Avid followers of the asset finance industry technology scene may

have picked up some of the winds of change in both the marketing messages and product strategies from industry software providers. There is a blurring of the lines between what is considered “front-end” and “back-end”. The “new” concept of the full life cycle “single system” is getting more airplay as a way to transition from a slow-to-react, legacy-driven technology laggard to a better, faster, and cheaper technology-driven market leader.

There is little argument that the technology and software available to the asset finance industry is a quantum leap in technical and functional depth from that of yesteryear.

It is arguable that the full life cycle “single system” is new; it is also arguable a single system is indeed better, faster, and cheaper.

Be careful what you wish for.In a past life my partners and I

bought into the concept of a full life cycle single system. Since all of my company’s resource and effort was focused on the front end system we had been marketing for many years, we licensed our source code to another vendor who intended to use our data model and code base to add all of the accounting, asset management and portfolio management functions to an already mature CRM,

origination and credit system.We hoped that the ability to leverage years

of development would make the project easier, quicker and less costly – our own iteration of better, faster, cheaper. To hedge our bet, we convinced a market leading pricing software firm to license us their accounting engine to be the driver behind many of the new functions to be added. We even had a customer or two, who were already using our front end system, ready to test and deploy the new full life cycle single system. Sound like a winner? I thought so.

The next two years taught me some hard lessons and made me question if what I and many others I talk to were “wishing” for even made any sense from both a technical and business perspective.

To quote a brilliant guy with white bushy hair, time is relative. Unfortunately, so is the need for change. Some processes need to be able to change or evolve quickly. Others - not so much.

For example, the origination processes that support your sales team may change, literally, from day to day as your market and channels evolve and react to economic changes and competitive forces.

Speaking from experience, that need for change has required my company to make enhancements to our software regularly. We typically release a major new version of our origination software on a yearly basis.

Accounting and portfolio management processes may need to change as well, but nowhere near as often. To quote a client: “Cash application has been done the same way since Caesar”. This may be a bit of an exaggeration, but compared to originations, accounting and portfolio management processes are static.

Enhancements are changes the software company makes to their code base. This requires change to and management of the code itself, testing of that code, and deployment of updated code to their customer base.

Typically larger customers have processes and procedures in place requiring they test changes internally prior to deployment. Often it requires regression testing (test what was there before) by both the software company and the customer. This whole process and the

Be Careful What You Wish For - A Discussion of the Single System Model


Feature rePort

resources required to make it succeed is the biggest reason it is common that customers choose to delay or forego upgrading their software. Accepting and testing releases costs time and money, and they do so only when it is believed that the changes will add value for their business.

Testing overhead is also a driver for software companies managing their releases and they only do so when there is a material pooling of accumulated enhancements that will add value for their customer base.

Herein lies the conflict between a full life cycle “single system” and realization of better, faster, cheaper. Faster and cheaper is likely not the case for the reasons explained above; if faster and cheaper

are harder to attain, better is a tough argument to win.

Be careful what you wish for.

So - back to my foray into the creation of my full life cycle “single system” in a past life. My vendor licensees were given my complete code base, and 2 years later they had finished many of the augmentations that brought the back end functions into the system.

During that time, we released two major versions of our software with significant enhancements and provided them with numerous code drops of the changes. But the management of our changes along with all of the new functions they were adding as well to the same code base became a logistic nightmare

and extended not only their timelines but their costs as well. They had to postpone many of the enhancements we had made to the code base in favor of their own changes. The customers who had originally signed on to test and deploy the final solution and who had been receiving our front end upgrades the entire time were hesitant to deploy a full life cycle single system that did not have several of the enhancements they were already using in the front end system they had in production. Coupled with the economic changes that were just beginning at that time and the cost overruns the entire project crashed and burned.

Sometimes wisdom comes with a heavy price.

Here are the lessons I’ve learned in that experience and several others I’ve had since that point. Maybe they’re obvious. They weren’t to me and I’ve been doing this a long time. ◉ The larger your code base, the more difficult it is to manage and deploy especially if many sections of the code base are shared between functions or objects.

◉ The above problem is magnified significantly if sections of the code base will change much more rapidly than other sections, which is the reality of a full life cycle “single system” finance system or any other system that combines many diverse purposes.

◉ Customers become very annoyed when seemingly simple changes they want made in one part of the system must be delayed to wait for changes being made in another section of

the code for a completely different purpose (or have to be made in other areas because they impacted by the initial change).

◉ No one likes testing software any more than they have to.

◉ Changes to single code base “full life cycle” systems require considerably more testing by everyone.

◉ All of the problems listed above are exacerbated when using object oriented programming common to most full life cycle “single systems” marketed today.

◉ Most of the benefits of a full life cycle “single system” come from a shared or integrated data model and not from a shared code base.

◉ Users of a full life cycle “single system” spend most of their time in modules related to their specific tasks; they are, in effect, using the single system like a point solution.I guess I could summarize

everything I have said above with the simple statement “More is not always better”. The more functions any sys-tem encompasses, the more difficult it is to make changes to that system and ensure that the changes being made do not have adverse impacts on other areas of the system.

Often this is such an onerous requirement that the number of changes being made are greatly reduced. In today’s economic environment, is that a good thing?

Be careful what you wish for.

about the author: Mike Cumby, Constellation Financing Systems, [email protected]. Mike has over 20 years of IT and senior management experience, developing and architecting software solutions currently in everyday use throughout the financial services industry.

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Feature rePort

know of, the score overrides done for sales considerations had very high bad rates, which credit management could then point to in their efforts to reduce the number of such approvals in the future.

Finally, and most impor-tantly, all good things must someday come to an end, and scoring models are no excep-tion. Models generally last two to five years, and know-ing when it is time to retire a model – when it just isn’t as predictive as it used to be - is one of the main purposes of monitoring. The good news is that the existing model doesn’t need to be completely discarded. Rather, it be-comes the base from which the next generation model is developed. If the business hasn’t changed significantly, and if there are no new data sources offering the potential for increased lift, then creat-ing the “new” model is really just a matter of updating and re-optimizing the old model based on newer data, and pos-sibly looking for a few new variables to add additional lift.

#12 – Never Lose Sight of the “Big Picture”Building a high quality credit scoring model is a lot of work, and even if the decision has been made to buy rather than build, there is still significant work that needs to be done gaining internal acceptance, setting credit policies and parameters for scoring, and monitoring the results. It is therefore important not to lose sight of the big picture, why you’re scoring in the first place. The list of benefits is so long it would be unbeliev-able, if each one of them weren’t so clearly verifiable: ◉ More Approvals

◉ Fewer Losses ◉ Reduced Overhead ◉ Much Faster Credit Deci-sions (which improves the closing rate, and increases bookings)

◉ Greater Customer Satisfac-tion (at least of the custom-ers you want)

◉ Increased Management Control

◉ Greater Flexibility (e.g. “tightening” or “loosening” overall credit standards overnight)

◉ Improved Consistency (so one analyst isn’t declining a deal that another would approve)

◉ Better Quality (i.e. fewer mistakes)

◉ Infinite Scalability (if ap-plication volume doubles, you can’t double the staff instantly)

◉ Improved Operating Infor-mation (e.g. quality of each vendor’s applications vs. bookings)

◉ Improved Overall Trans-parency (of total portfolio credit quality)

◉ Improved Predictability (of future portfolio per-formance, based on score vintages)

◉ Improved Funding Costs and Access to Funding (based on the above)Indeed, the only “bad news”

is that the benefits of scoring are so great that scoring is becoming non-optional. The innovators within a particular market will see a real benefit by adopting scoring, but the advantage doesn’t last forever as more competitors adopt scoring. Over time the mar-ket prices and expectations change to the point where those that use scoring earn just a “normal” return, while those that still don’t use scor-ing are operating at a costly disadvantage.

In general, the smaller the transaction and the larger and more homogeneous the ap-plicant population, the easier it is to develop scores, and the sooner that lending market will adopt scoring. Consum-ers are easier to score than businesses, so consumer lend-ing is about 25 years ahead of commercial lending. Though most consumers today have dozens of unsolicited credit card offers in the mail, 25 years ago getting a credit card required meeting with a loan officer at a bank, possibly dis-cussing career prospects and the loyalty and responsibility demonstrated by having a sav-ings account at the bank.

Today such a process is unthinkable in consumer lending, and that is where commercial lending is head-

ing. Virtually all deals under $25,000 are now scored, and increasingly deals in the $25,000 to $250,000 range are being scored as well. Within five years it is likely that the vast majority of transactions under $250,000 will be scored, just as home mortgages are. Several years ago the CEO of First Union said publicly that their ultimate objective was to score transactions up to $5mm. It will take some time to get there, but I’m sure that eventually we will.

about the author: Thomas Ware is PayNet’s Senior Vice President of Analytics & Product Development, and Managing Director of PayNet Analytical Services, which provides credit scores, probability of default and stress test models, strategic business reviews based on peer lender benchmarking, and published economic indices. He has almost 30 years of experience in small business lending working with commercial finance companies and banks, including as General Manager of a billion-dollar finance unit of Case/CNH Capital, and as Senior Vice President and Chief Credit Officer of a commercial lending subsidiary of American Express. He graduated with Distinction in Mathematical Economics from Dartmouth College and has an MBA from Harvard.

Continued from page 16


Funding

By Rev. Dr. K. Bill Dost

Often maligned as subprime, high risk and expensive, “C” credit leases, especially in the small ticket market place, are a necessary and important driver in the

overall economic market place today. While many may see this as a bold assertion the truth is that most simply do not want to be associated with the perceived stigma of an off-plan ‘risk’ portfolio, or being seen to offer an overly expensive rate for their financing product. The reality is that with good correlation between the two there is nothing to be ashamed of about offering, or accepting a “C” credit product. The fact is, it is precisely this sector of small ticket, “C” rate customers that are contributing to growing the economy faster than many of the “A” credit risk or blue chip companies.

One has to accept in most of the major western economies, it is the small businesses that far outweigh the larger ones when it comes to overall employees and revenues; as is often said it is the small business that is the backbone of the country. In Canada there are 2.4 million businesses registered with Canada Revenue Agency, half of which have 1 or more employees. Of the 1.2 million businesses that have employees, 75 per cent have less than 10 and 55 per cent have less than 4. The number of companies that have more than 100 employees across all of Canada is less than 25,000 (source: Key Small Business Statistics – July 2012 by Industry Canada). What this means then is most businesses in Canada are classified as small and this is where small ticket funders and “C” credit businesses spend most of their funding. It is these smaller turnover businesses, which typically eke out an existence, and struggle to raise the necessarily investment for their needed asset purchases. Purchases that would help them grow their businesses. It is also these businesses that USED to turn to their banks for support, support that since the credit crunch has largely dissipated or simply gone away as a result of unwillingness, or in some countries an inability, to support. Solutions are limited often coming down to providing credit card application for purchases below $10,000 to giving an outright no to the request. In often cruel twists of fate, some banks have been known to terminate existing credit lines or ask a client who may wish to borrow $25,000 and more to first secure the funds by way of another financial instrument at the bank, such as a GIC, prior to being offered a lend of the same amount. In essence, the customer is borrowing their own money from the bank at interest.

As a result the “C” space is in fact widening not narrowing.

Small Ticket Leases at “C” Credit Rates; Growing the Economy at a Grass Roots Level


Funding

There is a need for a suite of finance products into this arena, where the balance sheet is not the determining factor, and where the equipment required is not always of a pre-determined, or any, resale value. The customer concerned may not have significant years of credit traction or tangible multiples of security to offer, or may be undergoing change in their business. They may be a customer that maintains a constant demand for capital in their enterprise. None of these profiles are without risk, and this is where a specialist in the small ticket market and specifically the “C” credit market comes in.

Enter a specialist leasing company, or a leasing broker, who can understand the challenges of the customer and knows how to get the transaction done. In either case, the funder or broker, understands that the customer must be priced to their risk level, but at the same time they also understand that this customer is in essence Canada’s backbone and deserves help and support to grow. It is the duty of a funding source to ensure that customers in this small business segment receive the assistance they need. As these customers grow and succeed, then Canada and her economy will also continue to grow and succeed.

These are not the only place that a boutique rate is important; just common examples. One will find that higher rates in the small ticket sector will be found for numerous reasons, often it’s to top up wider funding requirements when a panel of A and B funders have been exhausted. This so called exposure issue, ensures that a customer is able to complete their entire financing project with an overall blended interest rate inside of their desired parameters, even if one funder ends up being more expensive. However, “C” funding can also be effective when a customer may be weak, the asset may be undesirable, the business simply may be new, or if the financing request itself is bespoke (think midterm skip payments, once a year payment forgiveness, rescheduling of leases, step and seasonal leases, funding of websites, mail servers and creation of apps for smart phones and the list goes on; mobile dance floors and AstroTurf anyone?). “C” rates, when effectively used should be a source of funds to catch the weird, the unique and the outside the box requests. They are of value when the deal requires story underwriting as opposed to balance sheet ratios and automated scoring. The important idea is those that work in these specialist fields bring a needed service to the marketplace. They are helping thΩe economy purchase equipment and assets that lead to growth. It’s a grass roots level, individual process, but for the customer, it helps to fund their business so if they have to pay a little more for that level of service they really do not mind. They are getting what they need which is the asset, the asset is going to grow their business, and the business is going to fund their life and lifestyle. Its

win-win all the way around. While many people may feel

there is a stigma around higher rate funding, I would argue the only stigma is in not being able to communicate clearly how important that funding is to the end user. Once the hurdle of understanding is surpassed I have personally never seen a deal turned away, everyone in the supply chain

understands it and is ready to close the deal and at the end of the day, the more deals that close, the better it is for all.

about the author: Rev. Dr. K. Bill Dost is the President of D&D Leasing in Canada, and the Managing Director of D&D Leasing UK Ltd. He is the incoming President of the Toronto Chapter of Entrepreneurs Organization, sits on the Asset Finance Directors for the Finance and Leasing Association (FLA), on the board of the Asset Finance Professionals Association and a Fellow of the Leasing Foundation. The D&D Leasing group of companies, now in their 13th year are “C” funding specialists and can be found at www.danddleasing.com

“The C space is widening not narrowing and there is a need for a suite of finance products in this area.”


your Business

By Angela Armstrong

It’s not that your Mom wanted to lie to you.

“You’ll grow up stronger, wait and see”. “Never mind, you can get another one”. “Tomorrow’s a new day”.

Your Mom, like mine, probably just wanted to teach a little resilience and deflect the painful moment.

Deflection is a uniquely human skill that’s responsible for our ridiculously persistent survival, despite pretty staggering odds against it. Humans’ frail physical envelopes and weirdly robust brains are the biggest evolutionary long shot Earth has ever taken.

The gamble pays off huge odds in the story of pre-historic human, when instead of cowering into starvation while avoiding six-inch shiny fangs lurking outside the cave, we stride confidently into our Homo Sapiens future by arming with a sharp stick.

The only thing propelling those humans forward in the face of likely predatory doom was their ability to filter memories of the bad stuff that happened previously. Scared humans don’t sally forth and conquer the world. So, nature brought us short memories. And, the ability to adapt to danger - by running like hell while carrying a big pointy stick.

Score: Fear 0 , Survival 1. There’s just one problem (other than Mom’s warning not to run with sharp pointy sticks).

REALITY. Humans that float six inches above reality in a cloud of foggy memory don’t see the ground clearly.

Hey, building in a flood plain might NOT be the smartest thing – even if there hasn’t been a flood in recorded memory. When someone says “that flooding was a 300 year record”, what

they’re REALLY saying is “holy cow, I never believed the water would get so deep”. (Well, it wasn’t called the dry plateau.)

Ability to deflect, plus ability to deny, equals one mean recipe for ruin.

And so it goes. Sadly for us, skills good for the survival of our species don’t translate well into prospects for the individual. Your enterprise on its own hunt for survival doesn’t go out intending to take one for the global business species. A little self-interest goes a long way on the bottom line.

But it’s not enough to want to survive. Having a pointy stick gives you a

(somewhat) defensible position against a hungry fanged beast– but what if the lurking danger’s a lightning strike? Laying flat might work, but might not occur to you if you’ve never experienced a thunderstorm. Expect the unexpected, and you might get by.

In the post-Enron decade, the ability to plan for the unexpected and unpredictable has moved all the way up into the C-Suite. The new role on the org chart is Enterprise Risk Management (ERM); a role that rarely existed as little as 10 years ago. Of course, conceptually it has always existed as a subset of say, finance or operations, but today it’s part of everyday conversation.

The annual report that used to be devoted to analysis and forward-looking statements now donates much more space to ERM. For a public company, ERM is a way to persuade investors that the company’s a safe bet, but all organizations should create room at the board room table for discussions on what might be waiting out there to take you out at the knees.

The irony is that even smaller businesses with best execution practices of risk evaluation, assessment and mitigation, won’t see every ravenous pack or lightning storm in the wilderness.

Worse, due to the deflection/denial gene, even horrible real-life experiences get fuzzy with time and distance.

Discussed endlessly since its publication in 2007, Nassim Taleb’s book ‘The Black Swan, The Impact of the Highly Improbable’ is a great starting point for business conversation. Managers who dialogue on whether a sharp stick, or laying flat, or both, are appropriate risk management strategies for their team, will have a massive head start over competitors when a highly improbable event occurs.

The Black Swan’s central thesis is this: that regardless of expertise, planning or preparation, there is the possibility of an event far beyond our reckoning. These eventsa. Are unpredictableb. Carry a massive impactc. Are explained away after the fact

with an intent to make them seem more predictable than they actually are (the human deflect/deny gene at work)

The last one is the kicker. Reverse engineering the bad experience for the precursor ‘red flags’, doesn’t NECESSARILY prove that you’ll be able to predict it next time.

Every Little Thing is Gonna Be All Right (and other lies)


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For a local business owner I know, this year Taleb’s hypothesis of the Black Swan was an unhappy lesson in crisis management. Well experienced and mature, the large construction business went through a generational shift in management. The prior management had a policy – keep the availability on their margining facility at the bank higher than equivalent project holdbacks. The simple strategy helped ensure that if ever business receivables slowed down dramatically, they’d stay on side with their lender.

The new management team, having become used to a strong economy (good revenues and growth) let this policy lapse in favour of wrestling every penny out of the availability to support the strong ongoing demand for their services.

There hadn’t been a flood in their corporate memory.Then, the improbable. A wholesale turnover in a government

department, combined with significant technology shifts in the same department, laid waste to payables turnover. Six months in, the company, while boasting a huge work pipeline, was scrambling to re-finance assets to meet cash flow needs in the business. This is the moment when some unlucky businesses end up selling at a painful earnings multiples discount.

This company was lucky – they stayed afloat – but not without doing a lot of bailing. Going forward, it will be critical for them to work at not explaining away the causes (too much confidence, not enough rainy day planning) and lose their vigilance on external events that could affect them.. It’s the vigilance that will save the day.

An unpredictable event, like a 300 year flood, is, well, unpredictable. The longer it’s been (think Ice Age), or the more sudden the literal or virtual environment changes (think global financial economic links, age and demographic shifts, disruptive technology innovations), the more impossible it is to predict or prepare for it. It’s literally out of our collective memory.

No amount of modelling can tell us whether we have enough facts to do a thorough analysis. Remember, there was a day when doctors didn’t know about germs – they predicted causal factors without having all the information available. There were some very strange remedies prescribed which seem ridiculously primitive to us now. Like current scientists predicting geological events, their success rates were subject to sudden and

dramatic Black Swans themselves.Prediction is the art of evaluating the possible. If you are

brave enough to admit the impossible, then, and only then, are you beginning to really dig into risk management success.

It’s difficult for business managers to resolve ALL known risks, and ludicrous to imply that they should then also tackle the unknown ones.

Instead – why not take a page from Darwin’s book: that it’s not the strongest of the species that survive, but those that are most adaptable.

Building a corporate culture around risk management MUST include the ability to execute; fluidly - adapting to changing circumstances by doing a few key things. A great adaptive business model includes:a. Empowering teams to think on their feetb. Transparent measurement and feedback loops c. Commitment to business survival, rather than perpetuating

a static model of the businessd. Facilitating a culture of honesty, communication and

accountability e. Analyzing crises deep and far back enough in time to gather

as much data as possible and identify real underlying, rather than surface situational, causal factors

f. Add to this adaptability a Continuous Improvement process, where your business tracks repeat problems and uses that valuable data to deal with them BEFORE they become fanged ferociousness. Information doesn’t make us perfect, but helps us align better to deal with the known challenges, freeing up business resources to respond when the improbable rears its own fanged snout.

Prevention is worth a pound of cure , although it sure helps to know what the potential illness might be. There are going to be times that you have to cure on the fly. And now, we’re back to resilience, just like Mom taught you.

So, now you know – everything little thing MIGHT be all right, but it might NOT too. And that’s ok, cause you’ll adapt.

After all, tomorrow is another big, unpredictable, day.

about the author: Angela Armstrong is president of Prime Capital Consulting, and an expert on telling the whole financial truth. She loves being an entrepreneur, and watching her clients experience success. For 25 years her team has helped business owners leap tall financial hurdles in a single bound by putting the money they need in arms reach.


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events

WHERE TO GO. WHAT TO SEE.Find out more about the conferences, exhibitions, seminars and meetings in your industry

June 19-20 ACT CanadaCardware 2013: Payment InsightsNiagara Falls, ONwww.actcda.com

June 26-28NBPCAAnnual Congress-The Power of PrepaidNational Harbor, MDwww.nbpca.com

August TBA CAIRP / Annual Conference 2013Banff, ABwww.cairp.ca

September 9-11Equipment Leasing and Finance AssociationLease and Accountants Finance ConferenceAustin , TXwww.elfaonline.org

September 9-10Equipment Leasing and Finance AssociationOperations and Technology Conference Austin, TX www.elfaonline.org

September 12-14National Equipment Finance AssociationFunding SymposiumNashville , TNwww.nefassociation.org

September 15-17IFO Canada3rd Annual Canadian Financial Operations SymposiumToronto, ONwww.financialops.org/canada2013

September 24-26 Celero SolutionsCanadian Financial Technology ConferenceRegina, SKwww.celero.ca

September 25 2nd Women in Payments Symposium & Payments Business Magazine Awards Night Toronto, ONwww.womeninpayments.ca

September 18-20 Canadian Finance & Leasing AssociationConference 2013Halifax, NSwww.cfla-acfl.ca

October 6-9 RIMS CanadaHorizons--Annual ConferenceVictoria, BC www.rimscanadaconference.ca

October 20-22 American Bankers AssociationABA Annual Convention, Business Expo & Directors’ Forum 2013 New Orleans, LA www.aba.com

October 20-22Equipment Leasing & Finance Asssociation 52nd Annual ConventionOrlando, Flwww.elfaonline.org

October 20-23 SourcemediaATM, Debit & Prepaid Forum 2013Las Vegas, NVwww.sourcemedia.com

October 23-24Airline Information Inc6th Airline and Travel Payments Summit & Co-Brand Conference 2012 London, UK www.aiglobal.org

October TBA Everlink Client ConferenceCONNECTIONS 2013Toronto, ONwww.everlink.ca

November TBA Smart Cards in Government Conference 2013Smart Card AllianceWashington, DC www.smartcardalliance.org

November (TBA) TMAC Toronto Chapter7th Annual Networking EventToronto, ONwww.tmac-Toronto.ca

November 5-7 BAIBAI Retail Delivery Conference 2013Denver, CO www.BAI.org

November 6-8Association for Governmental Leasing & Finance2013 Annual ConferenceBoca Raton , FLwww.aglf.org

November 13-17Commercial Finance Association69th Annual ConventionLos Angeles , CAwww.cfa.com

November 19-21ComexposiumCARTES & Identification Exhibition 2013Paris, FRwww.cartes.com


oBservations

By Rob Birnie

Where would we be without technology? I know where I would be -- driving around the muddy

backroads of Northern Alberta searching for the last few units needed to complete a fleet appraisal.

Last month Verus Valuations was engaged to perform a fleet appraisal on more than 100 pieces of construction equipment that was deployed throughout North Eastern Alberta. Colby, the field operations manager and my personal chauffer for the assignment, mapped out a route that would allow us to find each of the units as quickly as possible. He explained that the equipment would be in numerous locations between Edmonton and north of Fort Mac with some equipment on the Saskatchewan border. I tried my best to remain optimistic, but I admit that I was skeptical that Colby was going to be able to coordinate inspections of the entire scattered rental fleet. In our experience, there isn’t always a clear communication channel between the equipment operators,

site foreman, equipment renter’s management teams and equipment owners. As appraisers we often hold our breath in anticipation when waiting for the answer to the simple question, “exactly where is this specific machine at the moment?” We have a running joke in our office that fleet appraisal frequently involves hanging out the window of vehicles snapping photos of equipment as they hurtle down the freeway at 110 clicks.

We often take technology for granted and “miss out” on using all of the available features in our day-to-day lives. In recent years, significant developments have been made with respect to fitment of reporting and monitoring systems to heavy equipment. Much of this technology relates to engine and fuel management systems, however modern equipment location services systems provide tremendous benefits when it comes to fleet management to fleet managers. Global Positioning System (GPS) technology has come a long way. Back in the 1980s when GPS was introduced to the mainstream marine industry (in the dark ages when LORAN and dead reckoning were the only

navigation options out there), GPS was used simply to display location. Even today, most day-to-day use of GPS is simply to tell you where you are, but the technology is capable of being integrated into systems that do so much more. Modern fleet management systems monitor and report engine hours and equipment faults, but with integrated GPS technology, they provide one additional bit of information that is always so critical to a field appraiser – the current location of the machine!

As we headed toward one job site, Colby contacted the equipment operator to confirm the location of a machine and was told that it was being loaded onto a trailer at a Fort McMurray job site. After getting off the phone, Colby plugged his laptop into his cellular phone and pulled up his fleet management software. The information being transmitted from the machine, a Cat 624 loader, reported that the unit was actually heading south on Highway 861 right towards us. A quick call to the truck driver moving the machine allowed us to coordinate an inspection of the machine at the Heart Lake store and gas station. Without technology, we would have driven past each other without a second thought.

This assignment turned out to be 3 long days and 2700 kms with the help of technology. Without these systems, I would likely have taken up permanent residency in northern Alberta. We’ve deployed GPS asset management tools in our own organization and I’m sure you have as well. The next time you misplace your phone, give the “Find My Phone” app a try! It really works – but don’t ask me how I know!

about the author: Rob Birnie is a Certified Machinery and Equipment Appraiser (CMEA), Master Marine Surveyor (MMS), Senior Business Analyst (SBA) and an active member of the Vancouver Board of Trade. Rob has applied his hands-on experience in mechanical and marine repairs and more than 19 years of insurance damage appraisal, valuation and loss settlement experience to create and direct Verus Valuations.

An Appraiser's Tale:How Technology Lets Me Live Where I want

© 2013 General Electric Capital Corporation. All rights reserved. 13CDN115

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