using "big data" in the netherlands for troubled borrowers

John Taylor Principal, Experian Global Consultancy Practice, N.A.

April 2014

U.S. Mortgage Crisis Lessons for Mortgage Pre-Delinquency

“Conventional wisdom”

The conventional view serves to protect us from the painful job of thinking. “ ” – John Kenneth Galbraith

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3 © 2012 Experian Information Solutions, Inc. All rights reserved. Experian Public.

Historic Warning Signs U.S. Mortgage Crisis

U.S. Real GDP Growth

Historic Warning Signs: Default Indicators Through The Crisis

The United States financial system and mortgage crisis resulted in a severe recession which resulted in severe negative GDP growth eroding almost 9 million jobs and persistent high unemployment that peaked above 10%. Two phases – Slowdown Volatility and the Panic Phase were “pre-cursors” to unfolding events. The crisis was caused by a number of factors including an unsustainable housing boom evidenced by accelerating home prices – a leading indicator to peaks in mortgage loan delinquency and real household net worth

U.S. Unemployment Rate

Source: Bureau of Labor Statistics

U.S. Delinquency Rate – Single-Family Mortgage U.S. Real Home Prices

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The market boom in housing had signs of weak underpinnings…

► Collective actions of banks, consumers, and government resulted in more risk than was quantified

● Unsustainable home price appreciation

● Borrower debt to income overload

● Mortgage “Cash-out” for living expenses ended

● Customer segmentation overlooked

Risk models that factor in micro-geographic (zip + 2) current-loan-to-value localized effects of increasing distress sales

Borrower characteristics segmentation needed

Geographic effects of home price devaluation analytics needed

Historic Warning Signs: Mortgage Crisis Impact on Risk Management

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Government & Industry Response U.S. Mortgage Crisis


Government & Industry Response: Various HARP Borrower Assistance

Home Affordable Foreclosure

Home Affordable 2nd Lean

Home Affordable Unemployment

Program

(HAMP) Home Affordable Modification

Program

Borrowers not able to afford monthly mortgage

payments due to a financial hardship

Unemployed borrower assistance program

Assistance for borrowers already having permanent refinancing under HARP

Borrower alternatives to settle debt – possible relocation assistance

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2.7 million families benefit from HARP…


Government & Industry Response: HARP Mortgage Modification Results

Redefault rates for borrowers receiving a HAMP modification average 26% through April 30, 2013. These rates are somewhat consistent by geography at a total level, however in micro-geography analysis there is evidence of widely varying default rates based on home devaluation contagion effects. Redefaulting HARP borrowers exhibit three attributes important to pre-collections segmentation and prudent lending – High Debt-to-Income, Increasing Loan-to-Value and High Risk Borrower Credit Worthiness are unique to redefaulting borrowers. Customer segmentation is critical!

Cum Redefaulted HAMP Permanent Mods – 4/30/13

26% total redefault rate

Regional Redefaulted HAMP Permanent Mods – 4/30/13

Source: “Rising Redefault of HAMP Mortgage Modification Hurt Homeowners, Communities and Taxpayers”, SIGTARP, July 24, 2013 9


Mortgage Pre-Delinquency Implications U.S. Mortgage Crisis

Bottom up default models

Micro-geographic analysis of home price depreciation

Segment and monitor current-loan-to-value (CLTV) and migration of CLTV

Segment borrower ability-to-pay and debt-to-income

Build “pro-active” pre-delinquency strategies

Connect across the bank

Connect the dots… Segment customers using Custom Risk Models, CLTV, Debt-To-Income, micro-geography analysis and external data such as Experian’s MosaicTM life-stage segments to improve performance and efficiency of pre-delinquency efforts.

Historic Warning Signs: Pre-Delinquency Strategy Segmentation

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Custom loan-level probability of default (PD) estimate models are a key ingredient to a proactive pre-delinquency strategies

► Greater accuracy in prediction with more granular data

► Credit Bureau Attributes for individual borrower credit behavior

► Aggregated Credit Statistics (ACS) to account for micro-geographic drivers of default behavior representing contagion effects

● Local home market data (sold/list price ratio, distressed-sale prices etcetera)

● Local area credit variables (# foreclosures, pending distress sales recent delinquent etcetera)

● Local neighborhood indicators of stability such as change in wealth indicators

► Combined-current-loan-to-value (CCLTV) is a measure of all observed current mortgage secured balances for all properties owned by a consumer

Mortgage Pre-Delinquency Implications: Alternative PD Models

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Mortgage Pre-Delinquency Implications: Loan Level Default Models

Custom Probability of Default (PD) models account for unique risk factors. Experian has demonstrated the use of micro-level aggregated geographic variables and borrower credit attributes and CCLTV result in highly predictive models which can be used in segmentation of Pre-Delinquency Customer Treatment

Base Model – Includes CCLTV

Base + Premier Credit AttributesSM

Base + Premiers Credit Attributes + *ACS

Receiver Operator Characteristics Curves (ROC)

Source: “Home equity indicators with new credit data methods for improved mortgage risk analytics”, Straka, J., Robida C. and Sklarz, M., Experian Decision Analytics White Paper, 2012 p. 5.

*ACS data used within PD model limits adverse action in the U.S. but not segmentation purposes

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As much as 23% lift in rank ordering “bad” loans (90+DPD)


Mortgage Pre-Delinquency Implications: Strategic Approaches

Custom PD model and Combined-Current-Loan-to-Value can be used to monitor key risk segments. Implementing specific treatment strategies to assist borrowers with alternative refinance options and to determine if outreach designation is “proactive” or “reactive” will minimize operating expense and enhance customer satisfaction

Low

High

High Experian Debt-to-Income InsightsTM Low

65%+ <20%

Borrower Probability of Default (PD)

“Watch Segment” Subprime Risk Score <620 High DTI >50% Lower Income generally

“High Value Segment” Prime Risk Score >700 Lower DTI <20% High Income or Low Debt

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“Middle Risk” Near Prime/Pime Score 660+ Medium DTI 20% to 30% Middle to upper income



Absent robust information from customer multi-product ownership, using Mosaic FinergyTM segments provides a window to identifying distressed borrower segments. Experian custom default models can be developed using marketing segments can result in a strong tool to use to identify pre-collection segmentation treatment groups

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Portfolio customer segmentation strategies assists in determining which customer segments warrant proactive pre-collections and which customers should receive reactive pre-collections based on likelihood the consumer will need bank assistance.

DTI InsightsTM

Should we contact this mortgage customer for pre-collections?

Segment “High Value”

Mortgage Loan Portfolio

Treatment Strategy

High Home Price Devaluation or wealth decrease geography

Source: “Home equity indicators with new credit data methods for improved mortgage risk analytics”, Straka, J., Robida C. and Sklarz, M., Experian Decision Analytics White Paper, 2012 p. 5.

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Mortgage Pre-Delinquency Implications: Home Equity Triage Scenario

Experian’s PowerCurveTM Customer Management platform is used to design and execute account and customer lifecycle strategies including pre-collections treatment strategies for all consumer banking products

DTI

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Colle

ctio

ns F

low

Up to 10 different scorecards

Collection Action Parameters

Block codes and charge-off reason code settings

Assignment and routing of Segment Triage Strategies

Places delinquent accounts in action paths enabling

collection strategy sequencing

Sets unique account payment plan and settlement options

Enables outsourcing and debt sale decision actions

PowercurveTM customizable pre-collections module administers segmented treatment strategies



Experian’s PowerCurveTM Customer Management pre-collections strategy module is user defined and managed to allow bank risk management staff flexibility to deploy new strategies quickly and easily

DTI

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PowercurveTM enables easy deployment unique treatment strategies such as for very low and high risk segments



Account view

Account action

Credit card Opened six years ago

Balance $900

Limit: $5,000 Good

Home Equity Loan Opened four years ago

Balance $10,000

Limit: $75,000 Current “High Value Segment”

Good

Checking account Opened eight years ago

Balance $10,800

Direct Deposit Active Online Banking $100k Savings OD Protection Active

Good

Offer new limit – $1,500

No action

Debt recovery

Optimal Treatment

- No Active Marketing - No Limit Change

NO Proactive Pre-Collection Intervention and “Watch” utilization for signs of distress with no immediate line decrease

Overall customer view: GOOD

Secured home equity loan customer in “High Value Segment”. Resides in geography with high home price depreciation, exhibits no borrower distress signs and has high liquid net worth. No pre-delinquent contact or HEL decrease DTI

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Mortgage Pre-Delinquency Implications: 1st Mortgage Triage Scenario

Account view

Account action

1st Mortgage Loan Opened two years ago – no other banking products

Balance $120,000 110% CCLTV

Current “Middle Risk”

Good?

Kids and Careers MOSAIC Segment F20 – New Homemakers

Age: 30-40 Young Children Lower Risk Rising Wealth

Not a risky segment but borrower specific conditions

Good?


No action

Debt recovery

Optimal Treatment

May be homeowner that took on too much and could benefit from refinance to lower payments Outreach with mail proactive pre-collection effort

Overall customer view: ??????

1st mortgage customer in “Middle Risk” segment. Customer is in geography with high home price depreciation and has a higher CCLTV and custom risk score which may signal trouble. Initiate immediate pre-delinquency mail outreach

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Mortgage Pre-Delinquency Implications: 1st Mortgage Triage Scenario

Account view

Account action

Credit card Opened three years ago

Balance $1,200

Limit: $1,200 Paying minimum only P+22% APR

Good?

1st Mortgage Loan Opened two years ago

Balance $125,000 90% CCLTV

Current “Watch Segment” Good?

Checking account Opened three years ago

Balance – $70

Two NSF and Direct Deposit ceased for three pay periods

Bad


No action

Debt recovery

Optimal Treatment

Review for Limit Decrease, No Marketing

Initiate proactive pre-collection outbound call with letter to determine if unemployed and possibly modify debt obligation

Overall customer view: BAD

1st mortgage customer in “Watch Segment”. Customer is in geography with high home price depreciation and exhibiting signs of distress in both segmented and actual customer behavior. Initiate immediate pre-delinquency outreach DTI

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Historic Warning Signs: Summary of Pre-Delinquency Strategy

Leverage customer segments... by focusing on borrower credit attributes and micro-geographic aggregates and Mosaic customer life-stage profiles

Develop custom scores... By including various borrower specific data such as (CCLTV), (ACS) and borrower attributes to increase predictive power up to 20% or more

Develop customer watch segments... by using PD scores, “back-end” DTI and micro-geographic characteristics

Work effectively across your bank... by aligning proactive/reactive pre-collection strategies to treatments that lower operating expense by 5%+, improve collection efficiency and results by 5-10% while improving customer satisfaction

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using "big data" in the netherlands for troubled borrowers

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