Increasing Retail Lending Portfolios: What The Board Needs to Know About Using Non-traditional Data to Find and Satisfy New Customers

June | 2017

Presented for:

What we will discuss

• Backdrop and methodology

• Consumer Finance: Trends/opportunities/challenges

• Analytical innovation tackles challenges

• Emerging tech tools energize lenders

• Takeaways

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Backdrop: Stagnant U.S. consumer credit market ready to revive

• Economic conditions improving, consumer sentiment rising

• President and Congress committed to reducing FI regulatory burden

• Interest rates expected to (needed to) rise

• FIs will compete for loans (customers) amid risk management and process challenges

• New data/analytics/IT emerge enabling lenders to better manage credit and operational risk

• And to process more efficiently

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Methodology: More than 6 months of research/analysis

• Analysis from thirty-three in-depth Aite Group discussions with and interviews of alternative lenders, solution vendors, and senior management at U.S. banks, credit unions, and finance companies that have substantial retail credit portfolios and significant risk management expertise.

• Responses of 20 executives to an Aite Group 2016 survey of the top 50 U.S. retail lending institutions with the largest consumer portfolio balances. Respondents are a mix of new and previous participants from Aite Group’s 2013 and 2011 surveys of top 50 U.S. lenders.

• Alternative lender and vendor information from a variety of sources, including discussions with and solution demonstrations from the lenders and/or the vendors themselves, company 10-Ks, financial reports, and client references as well as estimates based on Aite Group’s formal surveys and knowledge of the industry.

• Also incorporates results from government reports/industry surveys.

Source: Aite Group Survey of 20 credit executives from top 50 U.S. lenders, October 2015 to March 2016

Top 1 to 20 banks with largest

consumer and small-to-midsize

business portfolios

45%Top 21 to 40

banks with largest consumer and

small-to-midsize business portfolios

30%

Top 10 finance companies with

largest consumer credit portfolios

15%

Top 10 credit unions10%

Number of Executive Participants by U.S. Institution Type and Size of Credit Portfolio Balance (N=20)

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What we will discuss

• Backdrop and methodology

• Consumer Finance: Trends/opportunities/challenges

• Analytical innovation tackles challenges

• Emerging tech tools energize lenders

• Takeaways

5

First signs of real consumer finance portfolio growth appear

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Source: Aite Group analysis of data from Federal Reserve, Small Business Administration, and other industry sources

Home mortgages70%

Helocs4.5%

Small business4.7%

Auto finance8.5%

Credit cards7.6%

Student loans2.7% Other

1.9%

U.S. Retail Loan Balances by Loan Type, January 2017(N=US$13.0 trillion)

Auto finance and credit card balances track upward spurring overall growth—Helocs one to watch

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Source: Federal Reserve

$9.27 $8.70 $8.15 $7.84$8.77 $9.16 $9.01

$0.86$0.74

$0.67$0.67

$0.87$1.00 $1.15

$0.68$0.68

$0.59$0.54

$0.65$0.60 $0.76

$0.81$0.70

$0.75$0.81

$1.00$1.11 $1.26

2008 2010 2012 2013 2015 2016 e2018

Mortgages Credit cards Home equity lines of credit (Helocs) Auto loans

Comparison of Selected Balances in U.S. Retail Loan Portfolios, 2008 to e2018

(In US$ trillions)

Lenders and regulators agree: Heloc activity increasing

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Source: Aite Group analysis of data from Federal Reserve

2.5

1.4

0.70.8 0.8 0.9

1.6

1.1

0.6

0.3 0.4 0.3 0.3

0.7

2006 2008 2010 2012 2014 2015 e2018

Home Equity Applications and Loan Results, 2006 to e2018 (In millions)

Applications Loans originated

Key challenges continue to batter lenders

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• Regulation/deregulation uncertainties remain

• Consumer sentiment upswing is fragile• Geopolitical concerns abound

• Natural disasters, too

• Healthcare confusion

• Tax cuts: yeah or nay?

• Nonbank competitors raise borrowers expectations

What we will discuss

• Backdrop and methodology

• Consumer Finance: Trends/opportunities/challenges

• Analytical innovation tackles challenges

• Emerging tech tools energize lenders

• Takeaways

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Trended data, alternative data: What’s the difference?

• Began with lender-led initiatives to improve financial inclusion of unbanked and underscored consumers

• Bureaus began leveraging other forms of reported consumer data, pioneering the use of trended credit data

• Traditional credit data plus payments/ tradeline data, trended over a number of months delivers better predictions of consumer propensity to pay

• And paved the way for validation and inclusion in credit scores and decisions of other forms of personal financial data (ex. telephone, utility bills, rent payments)

• AKA—Alternative data

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Trended credit data + alternative data=new analytics

Lenders believe: Financial account and transaction data improves credit decisions

12

0%

4%

21%

42%

33%

Not at all likely

Not so likely

Somewhat likely

Very likely

Extremely likely

Q. In this competitive lending environment, do you believe alternative data sources, like financial account and transaction data, are likely to

improve your ability to make better credit and lending decisions? (n=160)

Source: February 2016 poll of 256 attendees of an American Banker, Yodlee, and Aite Group Webinar

Lenders on board: Alternative data usage and use cases on the rise

What kinds of data?

No plans to use17%

Other 14%

Transaction 31%

Social media 38%

Q. What forms of non-traditional data are you exploring? (N=20)

What’s it used for?

14

8 8

65

2

Marketing Underwriting Underwritingemergingsegments

Fraud Collections Other

Q. For which purposes are you using or would you use nontraditional data? (n=15)

Source: Aite Group survey of 20 credit executives from top 50 U.S. lenders, October 2015 to March 2016 Source: Aite Group survey of 20 credit executives from top 50 U.S. lenders, October 2015 to March 2016

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Note: Social media data used only for marketing due to credit risk management concerns

What are key drivers for alternative data adoption?

• Financial inclusion

• New borrower discovery/acquisition

• Credit and operational risk management

• Portfolio profitability

• Competitive positioning

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As alternative data and scores are increasingly deployed in the decision process, lenders must remain credit-risk vigilant—so far, so good

69%

45%33% 31%

8% 8%

25%

50%

46%62%

68%56%

2011 2012 2013 2014 2015 2016

Percentage of Banks With Examiners Reporting Declined or Unchanged Credit Risk in Credit Card Portfolios From 2011 to 2016

Risk unchanged

Risk declined

15

Sources: OCC Survey of Credit Underwriting Practices 2016 and Aite Group

Alternative data: Lenders increase usage to facilitate greater inclusion and streamline existing decision processing

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• Profitability is critical to lenders

• Innovations pay dividends

• Can reduce processing costs and

• Simplify customer-facing credit processes

Nowhere is this more important than in home mortgage (and Heloc) processing

Source: Aite Group

Mortgage processing: Plenty of opportunity to streamline and make borrowers happy

• Prequalification• Product selection• Application

completion• Loan registration• Rate lock• Loan submission• Property appraisal• Compliance

documents

Pricing, delivery, and processing decisions made (includes good faith estimates)

• Credit report and models

• Verifications: ID, employment, liquid assets

• Credit policies• Appraisal

evaluation• Decision• Commitment

issuance

Credit, property, loan approval decisions made

• Mortgage insurance underwriting

• Commitment condition compliance

• Survey, title, insurance, etc. ordering

• All document preparations • Closing instructions• Signatures• Funding authorization

• Post-closing document tracking

• Servicing system setup

• Loan package audit (underwriting)

• Shipping• Investor pool

placement

Vendor services ordered and mortgage insurance decision made (includes RESPA)

Investor placement, servicing rights, and decisions made

ApplicationPost-closing and

deliveryPre-closing and closingUnderwriting

Average FI cost/time to originate a home mortgage? More than $7000. /45 days

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Anticipating results, lenders increase data and analytics spend

35%

17%

35%

24%

30%

22%

30%

24%

2016 (N=20)

2013 (n=18)

2016 (N=20)

2013 (n=17)

An

aly

tics

Data

managem

ent

Q. What best describes your [2013 or 2016] consumer credit IT budget for each segment below?

Substantive increase from prior year(10% or more in enhancementsor new technology additions)

Modest increase from prior year(less than 10% in enhancementsor new technology additions)

Sources: Aite Group survey of 20 credit executives from top 50 U.S. lenders, October 2015 to March 2016; Aite Group survey of 20 credit executives from top 50 U.S. lenders, February to June 2013

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Solid increase in acceptance of vendor platforms

33%

40%

28%

40%

2014-2016

2016-2018

Q. What is the likelihood that a new lending solution delivered in a hosted, Software as a Service (SaaS), or

hybrid environment would be approved by your institution? (N=20)

Likely Very likely

Sources: Aite Group survey of 20 credit executives from top 50 U.S. lenders, October 2015 to March 2016; Aite Group survey of 20 credit executives from top 50 U.S. lenders, February to June 2013

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What we will discuss

• Backdrop and methodology

• Consumer Finance: Trends/opportunities/challenges

• Analytical innovation tackles challenges

• Emerging tech tools energize lenders

• Takeaways

20

Vendors: Turning data into actionable information

Firm Tool (s) name/users Product description(s)

Equifax 1. Ignite Direct/analysts

2. Ignite Marketplace/ business executives

1. Enables analysts to self-serve by accessing Equifax’s data, attributes, and analytical tools for use in modelling/scoring

2. New offering that presents a self-serve opportunity with online delivery of “apps” that can provide visual insight in answer to specific business-related questions

Experian 1. Analytical Sandbox/ analysts 1. A data-and-analytics-as-a-service solution leveraging Experian’s data repository and providing external clients with an analytics/modeling environment

FICO 1. Analytic Modeler/ analysts 1. Analysts create and deploy custom analytic models via code incorporated into decision strategies and applications managed within the analytics as part of a FICO platform for building models/decision applications

TransUnion 1. Prama Insights/analysts and business executives

1. A self-service tool with benchmarking insights delivered in real-time; allowsclients to access underlying data assets and apply advanced analytics to improve and operationalize credit decisions and offers pre-built attributes

Source: Vendors

• Four vendors’ lender-facing tools have a strong user base yet are still in the early stages of product development and distribution. All focus on lenders’ need to self-serve and tap into new IT that supports credit risk management and inclusion.

VENDORS

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How the Equifax Ignite Direct and Ignite Marketplace environment works

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Accessing data to make critical decisions is 30% faster for Experian Analytical Sandbox users

Bureau engaged for pricing

23

Component Architecture of FICO’s Decision Management Suite

FICO Decision Management Suite

FICO Origination Solutions

FICO® DMP Streaming

FICO® Visual Insights Studio

DECIDEANALYZE

FICO® Application Studio

FICO® Customer Communication Services

FICO® Strategy Director

FICO

®

An

alytic M

od

eler

TextA

nalyze

r

R

FICO

®Id

en

tity R

eso

lutio

n

Engin

e

De

cision

Tree/Score

Card

Pro

FICO® Data Orchestrator

Mo

de

l Exe

cuto

r

FICO®

Decision Modeler

FICO® DMN Modeler

FICO® Decision Central

Tableau for FICO®

Social & IoT Customer Response Hadoop RDBMS Batch Operational Bureau

FICO® Big Data Analyzer

OPTIMIZE

FICO®

Optimization Modeler

FICO® Decision Optimizer

Applied Optimization Solutions

FICO® Decision Management Platform

FICO® Origination Manager

FICO® Origination Manager Essentials

24

TransUnion Prama Insights Revolving Credit Dashboard

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New and notable: Two vendors focus on consumers’ roles in financial inclusion

• Beginning to make their mark in U.S. credit through uniquely different uses of consumer education, alternative data, and lender partners willing to take some credit risk are:

• eCredable: Using true recurring payments to construct a proxy credit score--accepted by financial institutions willing to provide responsible rates

• RevolutionCredit: Leveraging behavioral science, primary financial data, and gamified personal financial actions to identify customers that will perform better than their credit score indicates

• These are new retail credit tools Aite Group believes most likely to be mission-successful as 2017 rolls into 2018 and beyond

26

Consumers self-serve and eCredable verifies/reports/scores: Partners lend

27

For Lenders and consumers: Time to play the RevolutionCredit game(s)

28

What we will discuss

• Backdrop and methodology

• Consumer Finance: Trends/opportunities/challenges

• Analytical innovation tackles challenges

• Emerging tech tools energize lenders

• Takeaways

29

Takeaways: Consumer, real-estate related loans poised to grow

• Using trended and alternative data to improve current models facilitates approval of more good loans without harm to overall portfolio quality

•Think CRA if your bank is not on board with alternative data/scores

•And speed up, simplify all loan processes—reduces costs and makes borrowers happy

• Remember that credit risk mitigation matters; U.S. lenders cannot afford another retail credit crisis.

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Please take a few minutes to fill out the Aite Group survey in your folders.

Thank you!

Aite Group is a global research and advisory firm deliveringcomprehensive, actionable advice on business, technology,and regulatory issues and their impact on the financial servicesindustry. With expertise in banking, payments, insurance,wealth management, and the capital markets, we guidefinancial institutions, technology providers, and consultingfirms worldwide. We partner with our clients, revealing theirblind spots and delivering insights to make their businessessmarter and stronger.

Visit us on the Web and connect with us on Twitter andLinkedIn.

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Appendix: Tech tools descriptions and reference lenders’ comments

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How the Equifax Ignite Direct and Ignite Marketplace environment works

33

This slide illustrates two client-facing modules from Equifax Ignite Direct and Ignite Marketplace. It is an open platform with tools for both off-the-shelf and custom tailored projects, which can be client-driven. Cloudera Hadoop is the data storage platform, and clients are supported by business intelligence tools—notably Spotfire and Tableau. Browser-based and hosted, the environment delivers decisions in both real-time and batch, depending on product sets or volumes.

WHAT DO LENDERS SAY?Lenders like the volumes of accessible data—both what can be tested and received. There were also positive comments about the flexibility of Equifax in supporting lender access to its different analytical tools and the speed of delivery of results and models. Overall, clients feel that Equifax internal staff are an important resource in their work

Accessing data to make critical decisions is 30% faster for Experian Analytical Sandbox users

Bureau engaged for pricing

34

Experian Analytical Sandbox was developed by Experian’s DataLabs and is delivered for client use in a hosted secure Software-as-a-Service (SaaS) described as a data-and-analytics-as-a service solution that leverages a data repository. It provides external clients with a self-serve, analytics/modeling environment, and enables clients to include their internal performance data.

One lender challenge when developing their own scores/models/attributes, whether internally or otherwise that Experian specifically tackled is the length of time needed to take scores from concept to production.One of the many stumbling blocks has been the time necessary to access data before analysis can begin and strategies can be implemented. This chart shows where Analytical Sandbox has been able to help lender clients shave months off of the process.

WHAT DO LENDERS SAY?Lender clients of Analytical Sandbox speak to the amount of data and pay special notice to the attributes available for use. In fact, some users mention that they have been able to reduce costs because their institution no longer needed to purchase attributes for internal use. They also say that having perpetual access to the full line of attributes and scores makes it easier to test and learn how newly developed items will perform. Clients also speak of easy access and fast and uncomplicated usage

Component Architecture of FICO’s Decision Management Suite

FICO Decision Management Suite

FICO Origination Solutions

FICO® DMP Streaming

FICO® Visual Insights Studio

DECIDEANALYZE

FICO® Application Studio

FICO® Customer Communication Services

FICO® Strategy Director

FICO

®

An

alytic M

od

eler

TextA

nalyze

r

R

FICO

®Id

en

tity R

eso

lutio

n

Engin

e

De

cision

Tree/Score

Card

Pro

FICO® Data Orchestrator

Mo

de

l Exe

cuto

r

FICO®

Decision Modeler

FICO® DMN Modeler

FICO® Decision Central

Tableau for FICO®

Social & IoT Customer Response Hadoop RDBMS Batch Operational Bureau

FICO® Big Data Analyzer

OPTIMIZE

FICO®

Optimization Modeler

FICO® Decision Optimizer

Applied Optimization Solutions

FICO® Decision Management Platform

FICO® Origination Manager

FICO® Origination Manager Essentials

35

FICO Analytic Modeler enables lender-clients to create and quickly deploy custom analytic models via code that can be implemented in the Origination Manager Decision Module. This allows the models to be incorporated into broader decisioning strategies and applications managed within the analytics as part of a platform for building both models and decision applications. This chart details the components of the Decision Management suite and the positioning of the Analytic Modeler (and other mechanisms) as the foundation of the company’s origination solution.WHAT DO LENDERS SAY?Some lender clients have long-term (more than 10 years) experience with the modelling programs and see Analytic Modeler as user-friendly and not complicated, while requiring limited coding and still providing extensive, needed functionality. Some use the tools primarily to transfer from custom to internal models and note that refreshing and controlling scores with Analytic Modeler brings quicker time to validation and to market. Users also indicate that the reject inference feature for unbooked loans, reports specific to adverse action, and the primary origination focus are key to their solution choice.

TransUnion Prama Insights Revolving Credit Dashboard

36

Prama is an analytical solutions suite built on top of the full depersonalized national credit file with over 350 billion rows of detailed trade line data on over 200 million consumers. Users can access trended data, and other external data sources, including alternative data. One of the primary use cases is the ability of clients to benchmark against the industry and peers offering real-time intelligence into performance and market trends and enabling more informed and quicker decision-making. Prama can change the dynamics of how credit risk managers work with analysts.

The dashboard-based scalable platform has visualizations that change in real time as filters are applied. Users see variations in market conditions across products, geographies, and credit tiers. Data, charts, graphs, and related summary tables are easily exported and shared internally. As just one example, this chart shows the revolving credit dashboard with an at-a-glance heat map displaying number of accounts and also acting as a filter to narrow data by state or region.

WHAT DO LENDERS SAY? Lenders are very positive and straightforward with their assessments of Prama. One lender described it as akin to a democratization of information—the belief that every FI in the credit market should have access to the same risk information. This focus is especially important to FIs endeavoring to benchmark capital, credit, and fraud risk. Topping the most-important-to-my-bank-list for many lenders is Prama’s off-the-shelf delivery (no need for customization or to get in line for prioritization). Also appreciated is the full (100%) data population usage, especially for attributes, discipline of data definition, self-service access, and the quality interface and graphical report presentations.

Consumers self-serve and eCredable verifies/reports/scores: Partners lend

37

So how does eCredable work? The subscription-based service allows consumers to take control of their credit by providing a platform to automatically or manually enter account payments, which builds a credit report and generates a score (known as the AMP Credit Score, which stands for “all my payments”) that lender partners will accept in their loan origination process.

The intent behind the AMP score is that its construction makes it a viable proxy for a traditional credit score. Consumers with reports and scores are able to apply for offers in the eCredable marketplace. Lender partners can download data for adjudication. The chart illustrates the business model.

For Lenders and consumers: Time to play the RevolutionCredit game(s)

38

RevolutionCredit’s solutions offer a behavioral analytics ecosystem for real-time credit decisions and consumer engagement with SaaS delivery of results to the lenders’ decision engine. The data points are complementary to existing risk scoring approaches: Clients typically leverage RevolutionCredit insights alongside a consumer’s traditional score(s), alternative data, and CRM/on-us data.

The company believes that its tools are creating a new class of core credit data based on real-time insight on consumer levels of aptitude, engagement, and mobility; this insight allows lenders to better segment consumers based on their credit potential, and the engagements nudge consumers toward better financial decisions and actions.