Frost&Sullivan Report: Business Analytics

Report Title – size and position text box to center Report Title in the blue bar

25 January 2013

Stratecast Analysis by

Karl Whitelock

Stratecast Perspectives & Insight for Executives (SPIE)

Volume 13, Number 03

Mobile Customer On-Boarding: Telenet (Belgium) Minimizes Risk and Increases Opportunity through

Purpose-Built Analytics

SPIE #03, January 2013 © Stratecast | Frost & Sullivan, 2013 Page 2

Mobile Customer On-Boarding: Telenet (Belgium) Minimizes Risk and Increases Opportunity through Purpose-Built Analytics

Introduction1

The communications service provider (CSP) landscape continues to incorporate new business partners, new business models, and different ways to keep customers satisfied. Truly, the working parts of customer service offerings are gaining complexity. For example, growth of the ‘smart device’ market—smartphones, tablets, connected TVs, and machine-to-machine connections from multiple industries—continues to expand at a double-digit compound annual growth rate (CAGR)—and, in some cases, triple-digit. On one hand, complex services accessed by these smart devices create substantial financial risk for the CSP community with regard to the end-to-end service monetization and partner accountability functions; while, on the other hand, good customers using these services is a basis for additional revenue opportunity.

Financial risk can come from operations issues such as traditional revenue leakage between internal data process flows, or the lack of accountability from content delivery and usage for a growing number of CSP partners. Financial risk can also come from the lack of properly qualifying new customers during the acquisition process, or even from existing customers, as conditions change.

Financial opportunity comes from new customers with the point of sale as a key beginning point. This allows CSPs to maximize customer value with a combination of information collected at the point of sale, and then augmenting it with external demographic and usage data throughout the customer’s lifecycle.

Applying analytics to the revenue management and cost tracking sides of any CSP business has gained significant attention recently, even though CSPs have used analytics to fight certain customer-related problems for more than 10 years. Most importantly, ‘purpose-built analytics’—automated analytical solutions designed to address specific business problems—have shown CSPs that embrace such tools that not only can revenue flows be traced and accounted for, but operations costs can be controlled and managed effectively. This is especially important as the number of external partner sources for content contribution increase, and as complex service usage offers expand.

This report will explain the issues and differences associated with customer level and business operations risk analysis. It will show how purpose-built analytics, applied to the customer acquisition processes, not only reduces the number of problem customers a CSP may inadvertently take on, but explains how real-world customer acquisition savings can be realized. The report also explains how Telenet (Belgium), working extensively with the NetMind® platform from Agilis International, improved its customer validation process and, in so doing, increased customer value, beginning at the point of sale (POS).

1 In preparing this report, Stratecast conducted interviews with representatives of the following companies:

Telenet – Luc Verstraete, Director Billing, Payments and Credit Exposure

Agilis International – Richard Miller, EVP Business Development and Marketing

Agilis International – Judy Misbin, Director Marketing

Please note that the insights and opinions expressed in this assessment are those of Stratecast and have been developed through the Stratecast research and analysis process. These expressed insights and opinions do not necessarily reflect the views of the company executives interviewed.


What is CSP Financial Risk Analysis?

Shown in Figure 1, CSP financial risk management can be broadly categorized as customer activities and interactions between internal and external business processes. Generally, the customer side is associated with revenue generation while the partner interaction and business operations side is associated with cost. Analytics can be applied to any portion of these business functions to deliver predictive insight and to better understand current and past behavior. While not a new concept,

predictive insight today must now come at an increasingly faster pace and support larger data volumes. This means real-time enough for CSP support personnel to have the information they need to make effective decisions, and for customers to know where they stand.

For many regions, where mobile saturation is high, CSPs now take extra steps to retain customers, which can bring

on new problems if all parts involved are not properly managed. Real-time analysis of customer revenue functions such as on-boarding, usage analysis, measurement of a customer’s propensity for up-sell and cross-sell, churn, and bad debt, are now essential new business requirements.

Figure 1 – Customer and Operational Risk Analysis Using Real-Time Analytics

Source: Agilis International

Real-time analysis of customer revenue functions such as on-boarding, usage analysis, churn propensity, and bad debt analysis are now an essential new business requirement.


Customer-related financial risk and opportunity analysis, as shown by the top half of Figure 1, is tied to three functional areas associated with mitigating risk and maximizing opportunity including:

Pre-Acquisition Risk/Opportunity – Evaluation of potential customers applying for service.

Existing Customer Risk/Opportunity – Determination of a customer’s propensity to buy, propensity to pay, propensity to churn, and level of risk by way of subscriber or network fraud.

Bad Debt Risk – Customers that carry bad debt. What is their current propensity to pay? What is the overall risk analysis of the customer; e.g., do the financial positives outweigh the negatives, and therefore these customers are worth keeping even though they may carry some bad debt?

Operational risk, exemplified by the lower half of Figure 1, includes many traditional functions such as revenue leakage analysis from internal data streams, and the inconsistencies that potentially could come from external partner or supplier relationships. While operational risk analysis, along with customer risk analysis, is essential to any CSP, a detailed discussion of operational risk is beyond the scope of this report. It was the subject of a recent in-depth Stratecast market share analysis report titled: Global Communications Service Provider (CSP) Financial Assurance (Revenue Assurance, Fraud Management, and Cost/Margin Analysis) Market Forecast & Supplier Assessment; OSSCS 13-07 (October 2012).2

The nature of telecommunications fraud is transforming as CSPs now look at the entire customer lifecycle. By correlating data from multiple internal and external data sources, analytical tools such as the Agilis International NetMind solution can define a comprehensive risk index.3 This index allows CSPs to assess and evaluate both risk and opportunity at any stage of the CSP and customer relationship. It has proven to be invaluable to Telenet as it initially launched its new mobile service offers, and as it continues to bring on new customers today.

2 This Stratecast market share analysis and forecast report defines why the operations-based financial assurance functions of revenue leakage analysis, cost assurance, margin optimization, and fraud management are critically important today. It also profiles approximately 30 companies that provide some level of solution capability within this growing focus area, and projects a robust 12.8% CAGR for the global financial assurance market over the next five years. For more information on how to obtain this Stratecast report or any other Stratecast or Frost & Sullivan report, contact your account executive or email to [email protected].

3 Agilis International is a privately held company headquartered near Washington D.C., with global offices in South Africa, Malaysia and Belgium. It has more than 300 employees focused on developing and delivering telecom business analytics solutions specific to: cost and revenue assurance; customer risk and opportunity management; subscriber lifecycle management; traffic optimization, data warehousing and reporting; and dashboard solutions for the communications industry. It has a customer base of many CSPs headquartered throughout North America, Europe and Asia Pacific.

In its simplest form, CSP financial assurance (FA) is traditional revenue assurance (RA), including revenue leakage analysis, and financial fraud management. These functions are enhanced with today’s computing and analytical tools, to yield near real-time analysis of business and operations data whenever needed. Financial assurance also involves cost and margin analysis to improve revenue accountability as partner and supplier relationships expand, as business models evolve, and as customer revenue functions grow more complex.

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The Business Challenge Telenet Faced at Point of Sale

Preventel, the Belgian organization that helped identify bad payment behavior, ceased operations as Telenet was initiating the release of new service offerings that were going to increase the company’s exposure to potential bad debt and fraud.4 At this point, Telenet needed a means to help mitigate the risk of bringing on non-paying customers while conforming to all customer privacy legislation and the company’s general terms and conditions.5

Linking into internal and external customer-centric databases, as shown in Figure 2, the risk management solution Telenet initiated with Agilis International monitors, in real time, all new sales requests. This approach provides an immediate assessment for customer acceptance or refusal of service. In addition, based on in-depth analysis of a customer’s propensity scores, it allows Telenet to make modified service offers tailored to customers. One of the key drivers for this solution is Telenet’s on-going offer of a highly-subsidized mobile device for each subscribing customer.

Figure 2 – Telenet Pre-Acquisition Aliasing Process

Proprietary and ConfidentialSlide 2

Point of Sales/E-Sales

Existing customer database

Fraud

Bad Payer

1.Identification

1. Identification with customer data (name, address, DOB, ID number,…) to check if an existing customer. Uses the Aliasing function to recognize disguised customers (bad debt, fraud)

2. If applicant is recognized as an extising customer, the solution checks in other databases to see if they are a bad payer, fraudster,….

3. If applicant is not recognized as an existing customer, they are scored through an external database4. Upon completion of identification and scoring processes, if credit worthy, applicant’s Telenet products are activated

2.Good customer?

3.Scoring

4.Activation

Aliasing

External data source(s)

NetMind®

Source: Telenet

4 Preventel ceased operations in April 2010. It managed an external database of customers that failed to pay CSP bills. At closing, some of its customers included Base, Telenet, Proximus, KPN Belgium and Clearwire.

5 Founded in 1996, Telenet is a major provider of broadband cable systems in Belgium. Telenet provides cable television, high speed internet and telecom services, primarily to residential customers, with coverage to approximately 60% of the national population of Belgium. Under the brand name Telenet for Business, the company also provides services for companies in both Belgium and Luxembourg. Telenet has been listed on the Euronext Brussels stock exchange since October 2005, under the symbol TNET. It is now a quadruple-play provider with the addition of Telenet Mobile as a full mobile virtual network operator (MVNO). It serves approximately 2.2 million subs and 4.6 million RGUs, with a monthly ARPU of approximately €41.5.


A number of factors contribute to the acceptance of an applicant, including the ability to determine, based on previous history, if the customer is attempting to commit fraud via a number of means. Examples include:

Subscription Fraud – Fraud by bypassing offer conditions.

Handset Acquisition Fraud – Determining if the applicant is an organized fraudster attempting to acquire a subsidized high-end handset.

Dealer Fraud – Monitoring of sales numbers for accurate reporting is essential due to commissions paid to dealers for handset sales and data plan offers.

Identity Fraud – Using a secure order entry tool to catch any false identity tries for both business and residential applicants.

Customer Identification – Recognizing customers through various data inputs including name, address, and personal credit-important details.

Bad Debt Recognition – Identifying customers with existing bad debt, and making determinations based on a variety of financial factors. This category was most concerning to Telenet, as its service offers include an advanced mobile device for €1, with a long-term service commitment.

Multiple Activation Fraud – Recognizing individuals or companies that may attempt multiple service activations within a brief period.

Shown in the center of Figure 2 above, the Aliasing engine is one of the pre-activation detection engines of the Agilis International NetMindPOS point of sale solution. The NetMindPOS Aliasing engine utilizes business analytics to review new service orders, comparing them against a Positive Aliasing Database (PAD) to prevent fraudulent subscribers and previous bad debt customers from signing up for a new service undetected. The Aliasing engine performs an alias match of applicant information against the PAD by using algorithms such as fuzzy logic, Soundex and percent word match to detect returning bad debt and fraudulent customers.6

The PAD is created using data provided by Telenet and external data sources. It includes information on past fraudulent subscribers, bad debt customers, stolen devices, vouchers, and previous good customers. Service orders are run through the PAD on a continual basis or as a batch operation. When service applicants are identified as potential fraudulent subscribers or returning bad debt customers, the system can issue an alert and or activate an internal trigger, such as an immediate analyst review or point of sale order hold. Good customers trigger an equally immediate response with the CRM system, and agents are notified that a new or returning good customer should receive special treatment and be shown an offer that recognizes his/her value.

Telenet further extended the use of the solution by using the analytics in the NetMind platform to target offers to preferable customers in its outbound marketing campaigns.

6 Soundex is a phonetic algorithm for indexing names by sound as pronounced in English.


Results from Telenet’s Business Trial and Beyond

Telenet worked with Agilis International to establish a proof of concept tied to the business objectives it had stated for identifying and mitigating financial risk from various forms of potential customer on-boarding fraud. The solution was deployed in two months, and operated as a proof of concept (POC) for approximately three months thereafter. It remained operational for several additional months while process issues with the permanent solution were resolved.

The permanent solution has been in operation for more than three years. Shown in Figure 3 are the key business results after the first eight months of operation. They include:

Recognition that approximately three percent of all prospects posed a high financial risk, with 76 percent of them identified as bad payers, 21 percent of them identified as having existing bad debt, and less than one percent of them identified as previous fraud customers.

In certain situations, based on in-depth analysis of a customer’s payment profile, modified service offers were given.

The cost savings that came from identifying the high financial risk prospects resulted in approximately €600 per customer, based on the internal cost to provision a customer in and out of the network, the cost to chase bad debt, the cost due to lost handsets, and the cost for credit scoring fees.

Figure 3 – Telenet Business Results through 8 Months of Operation

Source: Telenet Proprietary and ConfidentialSlide 3

Results of Implementation Immediate Savings

Agilis business model flexibility

Agilis provided an extended POC

Utilized basic Aliasing capability

Extended the POC during deployment of full solution

Identified 1.5% of applicants as returning bad customers

Prevented ~ €600 loss for each

Lost Handsets

Credit scoring fees

Provisioning costs

Reduced Usage Fraud from same

Production system increased the yield to 3.0%

Total NetMind®POS savings in first 6 months was € 6.5 million

Production system identified 3% of Prospects who posed High Risk

The 3% represented 4 specific risk types


Telenet explained to Stratecast that the total savings during the first six months of operation was in excess of €6.5 million. Continued savings have resulted since the solution was implemented, and the solution continues to be a significant part of the Telenet customer on-boarding process.

Agilis International NetMind Solution

Agilis International explained to Stratecast that its NetMind platform is a revenue assurance and fraud management system capable of managing the risk and opportunity points in the entire customer life cycle for landline, fixed, mobile, IPTV, DTH, GSM/CDMA/LTE, broadband, and next generation networks. It can handle all types of technology, and adapts rapidly to evolving CSP business models. Shown in Figure 4, the NetMind customer analytics coverage addresses all business needs relating to customer identification, propensity scoring, and usage.

Figure 4 – Agilis International NetMind Customer Analytics Coverage

Source: Agilis International

Agilis International further explained that NetMind eliminates the risk and maximizes the opportunity inherent in each phase of the subscriber management process:

During the pre-acquisition process, before incurring the cost of installation.

Through the acquisition process, including strong validation of customer identification.

During the early subscription period, where the vulnerability to fraud is highest.

Proprietary and ConfidentialSlide 4

With Advanced Analytics & Work Flow Management

During Each Stage of the Subscriber Lifecycle

For All Services Offered on the Network

Across Multiple Network Types

Operational

Dashboard

Financial

Reporting

Voice

Multimedia

Downloads

Data

Services

E-Wallet

SMS

GSM/CDMA/LTE

IPTV

Wire-line

Broadband

Case Management


Continuing into the long-term relationship, with vigilant attention to changes that indicate opportunities for up-sell/cross-sell, churn, or potential abuse of network services.

Agilis also noted that the industry cost savings from all customers that use its pre-authorization Aliasing engine exceed $1000 (€770) per customer. Agilis further stated that there are significant business imperatives for engaging in a financial risk analysis process for the developed world, where subscriber growth is relatively stable. This means aggressively managing the new customer on-boarding process to retain good customers and to grow revenue.

Within emerging markets, Agilis believes that billions of customers with little or no credit information require a new approach to the on-boarding process. What was typically done for postpaid customers in the developed world, and what is now done (virtually nothing) for prepaid customers of traditional voice and data access services, won’t suffice. Growing market complexity from more transactions and more complex service offers, often accessed through smart devices, implies more opportunities, more risk, and a more complex infrastructure.


Karl M. Whitelock

Director Global OSS BSS Strategy

Stratecast | Frost & Sullivan

[email protected]

Stratecast The Last Word

Several months ago, Stratecast stated that reducing the level of revenue “leakage” from the flow of data between a CSP’s systems and through its business processes (traditional revenue assurance), along with stopping the intentional exploitation of these weaknesses by certain individuals (operations fraud), were operations functions that would grow in significance over the coming months. While still true, there is much more to keep in mind from a customer-level perspective.

As smart devices proliferate with customers in both developed and growing markets, complex service offers grow and partner relationships expand to meet the needs of these services. In this environment it is now imperative that CSPs minimize their risk from new service applicants and from the potential financial risk caused by existing customers. In addition, it is critical for them to recognize opportunities to better meet customer expectations as a means for growing revenue. Enter the world of real-time purpose-built analytics—automated analytical solutions designed to address specific business problems. Customer analytics solutions are geared to deliver predictive insight to CSP customer support teams in order to make effective decisions. This is especially important when working with new service applicants, gauging the financial risk that can come at any time from existing customers, and in providing service offers that are more closely aligned with customer needs when they arise—the business opportunity side that is now emerging.

While the role of financial risk management has many facets, keeping financial risk in check for any CSP is critical for long-term business success. Customer-associated fraud is on the rise because the ways in which to commit fraud are increasing, as the number of partners, authorized dealers and suppliers a CSP must engage with increases. Real-time analysis of customer revenue functions, including on-boarding, usage analysis, churn propensity and bad debt analysis, is critical for long-term viability of service offers that involve partner participation. Opportunities to capture customer attention, through new revenue-bearing service offers, are increasing for the same reasons.

Stratecast believes that real-time purpose-built analytics will make a difference with CSPs that must now keep track, from every business angle, of not just customer usage transactions but data interaction with a rapidly growing list of partners, authorized dealers, and suppliers. Financial risk management is an essential business function that will grow as complex service offers continue to expand. Real-time analytical solutions, provided by companies such as Agilis International, will play an increasingly important role for CSPs in the months ahead, in dealing with financial risk analysis and capturing new business opportunity.

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