Identifying & Maintaining Great Financial AdvisorsThis webinar is intended for researchers & scholars. It should not be published or presented without permission from WCAI. Questions

KNOWLEDGE FOR ACTION

Identifying & Maintaining Great Financial Advisors

Data at a Glance:Observation Window: Jan. 2008 - Feb. 2016

Data are collected from a leader in the financial services industry and track ~174,000 financial advisors selling financial products:

• Transactional Data: Over 3 million individual sales transactions of financial products

• Activity Data: Over 17 million individual interactions between LFG and its advisors

• Opportunities Data: Over 2 million records of individual contract opportunities submitted by advisors

• 3rd Party Advisor Data: Marketing and financial services industry data profiling advisors and prospects

• Survey Data: Self-reported survey data on advisors

Submit your proposal by Monday, June 6th, 2016. Learn more at http://wcai.wharton.upenn.edu/research

Sponsored by Lincoln Financial Group

Presentation recording and slide deck will be made available via wcai.wharton.upenn.edu by Monday, May 23, 2016

WEBINAR WILL BEGIN SHORTLY


A WCAI Research OpportunitySponsored by Lincoln Financial Group

May 20th, 2016

Identifying & Maintaining Great Financial Advisors


Introductions

3TRANSFORMING BUSINESS THROUGH CUSTOMER DATA

Brandon KrakowskyResearch Director WCAI

Debbie ShapiroAssociate Research Director WCAI

Colleen O’NeillExecutive DirectorWCAI

Elea FeitSenior Fellow, WCAIAssistant Professor of Marketing, Drexel University

Anjna KumarChannel & Data Insights –Business IntelligenceLincoln Financial Group

Sandeep AjithManager, Sales Reporting ProjectsLincoln Financial Group

Michael BaldinoMarketing AnalystLincoln Financial Group

KNOWLEDGE FOR ACTION TRANSFORMING BUSINESS THROUGH CUSTOMER DATA 4

Lincoln Financial Group provides advice and solutions that help empower Americans to take charge of their financial futures with confidence and optimism.

NYSE:LNC

110 yearsFounded in 1905, Abraham Lincoln’s son,Robert Todd Lincoln, grants permission

to use his father’s likeness.

9,308current

employees

life, income, retirement,employee benefits, advice

Our core business areas focus on supporting, preserving and enhancing people’s lifestyles and

retirement outcomes.

More than

17 million peopletrust Lincoln for their retirement,insurance and wealth protection

needs

As of December 31, 2015


Lincoln Financial Products


Product offerings through Lincoln Wholesale Distribution

Life Insurance and Long Term Care (MoneyGuard)

Fixed and Variable Annuities

Defined Contribution (401k and 403b)


We’re looking forward to developing a predicted lifetime value model of our advisors, enabling us to view our advisors as assets and our sales / marketing initiatives as quantifiable investments in those advisors.

• Selection: developing a model that predicts an advisor’s future value and enables Lincoln to act on retaining the best advisors

• Segmentation: identifying the demographic, exchange, and psychographic variables that drive value in each of our advisor groups

• Prospect Targeting: developing a profile of our best advisors and leveraging it to target the most valuable advisors in our prospect pool

• Resource Allocation: maximizing the return of our advisor marketing / sales touchpoints

Areas of Interest:


A Few Operational Notes

This webinar is intended for researchers & scholars. It should not be published or presented without permission from WCAI.

Questions about our research program or for press inquiries:

[email protected]

To get access to the data, research teams must submit a proposal to WCAI and the sponsor for approval. More details at the end of this presentation.


mailto:[email protected]


Data Background



Data Background

10

• Data are collected from Lincoln Financial Group, a company that is largely known for selling life insurance, annuities, and other financial products

TRANSFORMING BUSINESS THROUGH CUSTOMER DATA


Data Background

11


• Financial advisors are observed selling these products for LFG over an eight-year period



Data Background

12



• Each transaction is an individual payment on a single contract for a single financial product



Data Background

13



• Each transaction is an individual payment on a single contract for a single financial product

• Transactions include lump sum payments and periodic payments



Data Background

14

• Each contract is tied to a single financial product


ContractProduct


Data Background

15


• There are one or more transactions tied to a single contract


Transaction

Transaction

Transaction

ContractProduct


Data Background

16


• There are one or more transactions tied to a single contract

• Each transaction is tied to a single financial advisor


Transaction

Transaction

Transaction

ContractProduct

Advisor A

Advisor A

Advisor B


A Single Financial Advisor in the Data


Ben is a financial advisor who works in Ventura County in California, and sells financial products for Lincoln Financial Group



18

Ben sells one of his clients a variable annuity and creates a contract specifically for that product


Variable Annuity Contract



19

Ben’s client makes an initial lump sum payment to LFG for $47,000





20

One month later, he makes a second lump sum payment of $3,900





21

For every month after that, Ben’s client adds to his variable annuity by making a periodic payment of $100 …





22

For every month after that, Ben’s client adds to his variable annuity by making a periodic payment of $100 …

… We can see that every payment made to LFG on the client’s variable annuity is linked to the contract




We can also see that each individual payment is linked to the financial advisor Ben




Ben Ben Ben Ben Ben Ben Ben Ben


Additionally, LFG might send Ben an anonymous financial advisor survey to learn more about him and his portfolio …






Additionally, LFG might send Ben an anonymous financial advisor survey to learn more about him and his portfolio …

… This can also be linked directly to Ben






A Single Financial Advisor “Team” in the Data

26

Sometimes, Ben works with another advisor, Rocco, in the same office …


Note: Advisor “teams” are inferred from the data



27

Sometimes, Ben works with another advisor, Rocco, in the same office …

... This means they work as part of a team on a single contract and product





28

Taking our previous example of the variable annuity, we can see that each individual payment is linked to either Ben or Rocco across the contract …



Ben Rocco Rocco Rocco Rocco Rocco Rocco Rocco




29

Taking our previous example of the variable annuity, we can see that each individual payment is linked to either Ben or Rocco across the contract …

... And we can assume that individual financial advisors are compensated a percentage of the payments they process



Ben Rocco Rocco Rocco Rocco Rocco Rocco Rocco




30

So we can see all contracts that are linked to Ben within the observation window …


Contract BContract A

Ben




31

So we can see all contracts that are linked to Ben within the observation window …

... And the contracts shared with other advisors on his team


Contract C

RoccoBen

Contract BContract A



Activities

Transactions

3rd Party Advisor Data

Self-Reported Survey Data

Financial Advisors

Products

Opportunities

Data Structure


Activities

Transactions



Financial Advisors

Products

Opportunities

Data Structure


Products

34

We observe 6 different groups of LFG products being sold as part of the individual transactions within our observation window

• These include:– (VA) Variable Annuities– (LIFE) Life Insurance– (FA) Fixed Annuities– (MG) MoneyGuard (Long-term care insurance)– (EB) Executive Benefits– RPS Small Market (Retirement Plan Services)



Products


• Product groups are divided into 24 different financial products

Product Group Product

More info on LFG products: https://www.lfg.com

https://www.lfg.com


Number of Contracts by Product Group

TRANSFORMING BUSINESS THROUGH CUSTOMER DATA 36


Number of Contracts by Product Group


Over 550K contracts are for variable annuities


Number of Products Sold by Each Advisor


# of Products Sold


# of Products Sold



Over 117K advisors are selling products from a single product group


# of Products Sold


2 advisors are selling products from all 6 product groups


Over 117K advisors are selling products from a single product group


Activities

Transactions



Financial Advisors

Products

Opportunities

Data Structure


Transactions

42

The dataset includes over 3 million individual transactions of LFG financial products from Jan. 2008 to Feb. 2016



Transactions

43


• Transactions are payments on financial contracts for individual financial products, like variable annuities and life insurance



Transactions

44






Transactions

45




• We observe ~174,000 financial advisors processing transactions on more than 1.2 million different contracts



Transactions

46




• We observe ~174,000 financial advisors processing transactions on more than 1.2 million different contracts

• It can be assumed that individual financial advisors are compensated a percentage of the payments they process



Transactions

47

Some of what’s included in a single transaction

• Financial contract:– Unique identifier– Product name and description– Start date of coverage

Note: Some contracts started before the observation window

• Financial advisor:– Unique identifier– Advisor county and state

• Customer:– Name

Note: This is hashed to de-identify the customer

• Details of the sale:– Transaction date– Payment amount

Note: This is the amount paid to LFG, not the advisor



Number of Contracts Per Single Advisor


# of Contracts

Note: These include ALL contracts, including those that were “reversed” or returned


# of Contracts




Over 56K advisors are working on a single contract throughout the entire observation window


# of Contracts




14 advisors are connected to 1,000-10,000 contracts

Over 56K advisors are working on a single contract throughout the entire observation window


Total Number of Contracts Per Team Size


# of Advisors per Team







Over 1.1 million contracts are associated with advisors who work alone






Over 127k contracts are associated with teams of 2 advisors








There is a single contract associated with 10 different advisors

Over 127k contracts are associated with teams of 2 advisors


Average Number of Contracts Per Team Size


Note: Advisor “teams” are inferred from the data# of Advisors per Team


Average Number of Contracts Per Team Size


Note: Advisor “teams” are inferred from the data# of Advisors per Team

An average of 5 contracts for a team of 6 advisors


Transactions: Data Snapshot


Makes initial paymentMakes 2nd payment

Makes recurring payments

Advisor linked to transaction


QUESTIONS



Activities

Transactions



Financial Advisors

Products

Opportunities

Data Structure


Activities

60

The dataset includes over 17 million individual interactions between LFG and its advisors from Jan. 2008 to Feb. 2016



Activities



• Internal activities– E-mail communications– Sales calls– Snail mail activities– Literature orders


Activities




• External activities– Face to face sales meetings


Activities




• External activities– Face to face sales meetings

• “Hypothetical” activities– Communications for client prospects and potential contracts


Activity Types



Activity Types


Most activities are internal sales calls and e-mail communications


Activities

66

Some of what’s included in a single activity

• Financial advisor:– Unique identifier

• Financial product:– Relevant product line and name

• Details of the interaction:– Interaction date– Type and Description

e.g. Internal Sales Call (Internal Activity), One on One (External Activity)



Number of Activities vs. Number of Contracts for Advisors



Number of Activities vs. Number of Contracts for Advisors


Advisors who have more interactions with LFG have more contracts


Activities: Data Snapshot


Receives sales call from LFG rep

Has one on one meeting with LFG rep


Activities

Transactions



Financial Advisors

Products

Opportunities

Data Structure


Opportunities

71

The dataset includes over 2 million records of new contract requests submitted by advisors to LFG



Opportunities

72


• Some opportunities become contracts – This means we’ll eventually see transactions



Opportunities

73


• Some opportunities become contracts – This means we’ll eventually see transactions

• Other opportunities never become contracts– They may have been withdrawn or the policy applicant may have been

declined by LFG



Opportunities

74

Some of what’s included in a single opportunity


• Financial product:– Relevant product line and name

• Details of the opportunity:– Date of submission– Pending Status

e.g. Open, Closed, Declined



Number of Opportunities vs. Number of Contracts for Advisors



Number of Opportunities vs. Number of Contracts for Advisors


Small number of advisors who submit a lot of opportunities


Opportunities: Data Snapshot


Submits the contract request to LFG


QUESTIONS



Activities

Transactions



Financial Advisors

Products

Opportunities

Data Structure


3rd Party Financial Advisor Data

80

The dataset includes 3rd party marketing and financial services industry data, profiling over 300,000 individual financial advisors




81


• The data is compiled from general direct-marketing industry data and state regulatory data filings




82



• It provides additional background and demographic information about financial advisors selling products for LFG




83



• It provides additional background and demographic information about financial advisors selling products for LFG

• It also profiles financial advisors who are not selling products for LFG– These are considered “prospects”





The 3rd party data profiles financial advisors selling products for LFG …

Advisors SellingLFG Products

3rd PartyFinancial Advisor Data




The 3rd party data profiles financial advisors selling products for LFG …

… It also profiles prospects

Advisors SellingLFG Products

3rd PartyFinancial Advisor Data

AdvisorProspects



86

Some of what’s included for a single financial advisor

• Advisor– Primary county and metropolitan area– Age, gender, & marital status– Income and net worth– Preferred sales channel– Date became registered as an advisor– Number of states registered in

• Broker-Dealer Firm– Type of firm

e.g. Bank, Wire, Regional, Independent– Products offered

e.g. Municipal Securities, Mutual Funds, Private Equity Funds

• And many other variables …


Note: 3rd party marketing data points include general direct-marketing preferences, not LFG specific


Marketing Data: Number of Advisors by Income


Note: Some 3rd party marketing data is self-reported, so data point values may be unknown for some advisors


Marketing Data: Number of Advisors by Income


Note: The income is unknown for some of the advisors

Note: Some 3rd party marketing data is self-reported, so data point values may be unknown for some advisors


Financial Services Industry Data: Number of Advisors Registered by Number of States/Territories


# of Sates


Financial Services Industry Data: Number of Advisors Registered by Number of States/Territories


# of Sates

Many advisors registered in a single state


3rd Party Financial Advisor Data: Data Snapshot


Self-reported Income Self-reported preferred DM channel

Data from direct-marketing industry …

Note: 3rd party marketing data points include general direct-marketing preferences, not LFG specific


3rd Party Financial Advisor Data: Data Snapshot


Data from direct-marketing industry …

… and data from the financial services industry

Other financial products offered

Self-reported Income Self-reported preferred DM channel

Number of states registered in


Activities

Transactions



Financial Advisors

Products

Opportunities

Data Structure



94

The dataset includes survey responses from 8 different surveys sent by LFG to advisors who sell its products and prospects who currently do not




95

The dataset includes survey responses from 8 different surveys sent by LFG to advisors who sell its products and prospects who currently do not

• Surveys capture information about advisors and LFG itself:– Identify trends in the financial product market– Measure preference for new LFG product concepts– Gauge familiarity and perceptions of the LFG brand– Evaluate effectiveness of LFG marketing initiatives




96

Some of what’s included in a single survey submission


• Survey responses:– Answers to over 30 single choice and multiple choice questions– Free-text responses– Additional demographic information

• Details of the submission:– Date of submission



What is the average size of an individual client portfolio that you manage?

Example of Survey Question with Responses



Self-Reported Survey Data: Data Snapshot


Single Choice Question Example:Which of the following best describes your current job?


Self-Reported Survey Data: Data Snapshot


Single Choice Question Example:Which of the following best describes your current job?

Single Choice & Free-Text Question Example:Do you work as a sole practitioner, as part of a team, or other?


QUESTIONS



Possible Research Areas


• Selection: developing a model that predicts an advisor’s future value and enables Lincoln to act on retaining the best advisors– What components are needed to predict lifetime value (PLTV) of an advisor?– How can we develop sound customer attrition rate methodologies amongst our product

offerings– Are there product focused conclusions we can make to inform our retention strategies?

• Segmentation: identifying the demographic, exchange, and psychographic variables that drive value in each of our advisor groups– What would these segments look like? – What variables would be coupled with PLTV to develop segments?

• Resource Allocation: maximizing the return of our advisor marketing / sales touchpoints– How does geographic and temporal factors influence an individual advisor’s performance?– What marketing and sales activities generate the most value?– Are there product focused conclusions to inform our cross sell strategies?

• Prospect Targeting: developing a profile of our best advisors and leveraging it to target the most valuable advisors in our prospect pool– Are there product focused conclusions we can make to inform our prospecting strategies?


Possible Research Areas


• Selection: developing a model that predicts an advisor’s future value and enables Lincoln to act on retaining the best advisors– What components are needed to predict lifetime value (PLTV) of an advisor?– How can we develop sound customer attrition rate methodologies amongst our product

offerings– Are there product focused conclusions we can make to inform our retention strategies?

• Segmentation: identifying the demographic, exchange, and psychographic variables that drive value in each of our advisor groups– What would these segments look like? – What variables would be coupled with PLTV to develop segments?

• Resource Allocation: maximizing the return of our advisor marketing / sales touchpoints– How does geographic and temporal factors influence an individual advisor’s performance?– What marketing and sales activities generate the most value?– Are there product focused conclusions to inform our cross sell strategies?

• Prospect Targeting: developing a profile of our best advisors and leveraging it to target the most valuable advisors in our prospect pool– Are there product focused conclusions we can make to inform our prospecting strategies?

Something else not on this list!


Proposal Format

103

Proposals should be in PDF format, no more than 2,000 words, and include the following information:• Title• Author(s) name, title, affiliation and e-mail address: Please designate a corresponding

author.• Summary information: a single slide that visually summarizes team & project.• Abstract• Introduction: Describe expected contribution(s), covering both the academic and practical

aspects. Please keep it concise, and cite relevant work as necessary to explain your academic contribution. There is no need to include a lengthy literature review.

• Detailed project proposal: Please include enough detail that we can assess the feasibility & merit of the proposed approach. For example, modeling projects should include at least a sketch of the model. In addition, include a rough estimate of how long the project will take. Also include the business relevance of your research and the impact for the sponsor as well.

• Data Needs: Bulleted list of data required or requested for analysis not explicitly mentioned during this webinar. While we can’t guarantee the inclusion of these items, we are happy to investigate the availability.

• Biographies: Include up to a paragraph-long biography highlighting what each team member will contribute to the project.



Proposal Submission Process

104

• Read more about the proposal format and Submit Proposals here:http://wcai.wharton.upenn.edu/for-researchers/get-the-data/

No later than Monday, June 6th, 2016, at Midnight US Eastern

– Proposals will only be accepted online

– A single PDF combining the written portion and the single slide

• Proposals will be evaluated both on academic contribution and potential to significantly improve the data sponsor’s practice by the proposal review committee:

Eric Bradlow (WCAI), Pete Fader (WCAI), Elea Feit (Drexel University),Andrew Petersen (Penn State)

and representatives from Lincoln Financial Group

• Contact [email protected], if you have questions prior to submitting your proposal.


http://wcai.wharton.upenn.edu/for-researchers/get-the-data/

mailto:[email protected]


Other WCAI Opportunities for Researchers

105

If you registered for this webinar, you will receive regular announcements regarding:

• Upcoming Research Opportunities:

- Marketing Optimization & Personalized Treatment Solutions for Customers of a Multinational Bank

- Predicting & Preventing Cyber-Attacks in the Financial Services Industry

Also find us at:

• SSRN Research Paper series: http://www.ssrn.com/link/Wharton-Cust-Analytics-Initiative-RES.html

• Sign up for updates: http://wcai.wharton.upenn.edu/newsletter/


http://www.ssrn.com/link/Wharton-Cust-Analytics-Initiative-RES.html

http://wcai.wharton.upenn.edu/newsletter/


Documents

Identifying & Maintaining Great Financial AdvisorsThis webinar is intended for researchers & scholars. It should not be published or presented without permission from WCAI. Questions