Measuring & Managing Credit Portfolio Risk 1 · 2004-07-15 · Measuring & Managing Credit Portfolio Risk: ... • Understanding and managing total risk exposure within your existing

Equipment Leasing Association 2003 Annual Convention1

New Sources of Information to Effectively Manage Your Small Ticket Lease Portfolios

Measuring & Managing Credit Portfolio Risk: The Impact on Your Earnings


Profitable Portfolio Management Begins with Quality Data You can Trust


Everyday, You Make Decisions That Greatly Impact Your Business…

• Understanding and managing total risk exposure within your existing customer portfolio

• Identifying and aggressively collecting on high-risk accounts

• Benefiting from regular assessment of the risk of all your customers

• Using your credit resources more efficiently to save money

The success of your business decisions depends on the type of information and the quality of the information driving them

The decisions you make are only as good as the data they are based on

• 240 business addresses will change• 150 business telephone numbers

will change or be disconnected • 112 directorship (CEO, CFO, etc.)

changes will occur• 20 corporations will fail • 12 new businesses will open their

doors• 4 companies will change their

names

…and the Data You Base Your Decisions on is Constantly Changing. In the Next 60 Minutes …


Strategic decisions on portfolio management start with confidence in your data

• Whether the Lessee is correctly identified• Is Mike’s Bike Shop really ABC Co. D/B/A Mike’s Bike Shop Inc?

• Whether the payment data belongs to that business

• Was it really Mike’s Bike Shop that paid the XYZ bank loan on time?

• Whether the Lessee is part of a larger corporate family

• Is Mike’s Bike Shop actually a subsidiary of Mike’s Transportation Int’l?


ABC, Inc123 Elm St.Bethlehem, PA 18025(SIC) 5411-02Chuck Smith, President

Multiple Unmatched Pieces of Data

Chuck’s Mini-MartP.O. Box 111Bethlehem, PA 18055(SIC) 5411-02Chuck Smith, President610 882-7600

2

Charles Smith123 Elm St.Bethlehem, PA 18025(SIC) 5541-99215 882-7600

3

1D&B D-U-N-S Number:12-345-6780ABC, Inc+ Chuck’s Mini-MartP.O. Box 111Bethlehem, PA 18055123 Elm St.Bethlehem, PA 18025(SICs) 5411 0202, 5541 9901Charles Smith, President610 882-7600

Complete Single Business

1

Entity Matching ensures that a single, accurate picture of each business entity is received


Corporate Linkage is critical to view the entire corporate family with no limit in depth or breadth

Fictional example


Understanding your portfolio is critical to profitable small ticket leasing.

When You Measure and Benchmark Your Portfolio By …

Risk ProfileRisk Profile

Profit ProfileProfit Profile

Collection ProfileCollection Profile

Adjust your credit policy by identifying the good and bad segments within your portfolio


Gain a market advantage by identifying which segments are the most profitable and price accordingly


Improve your collection efficiency with knowledge based account prioritization

You Will Gain the Ability To …


Augmenting Quality Commercial Information with Consumer Information as well as Your Own Performance Information Enhances Your Small Ticket Portfolio Risk Assessment and Collections Capabilities

Commercial Data

ConsumerData

New Best Demonstrated Practices

Small Ticket Collections Actions

Financial Performance

Data

Portfolio Modeling Applications


Predictive models that use a wide range of data deliver the most accurate small business

risk assessment

• A Suite of ModelsModels driven by Commercial Only, Consumer Only and Blended dataThe appropriate model is selected based on the data availableSelection logic consists of the absence or presence of derogatory information on the principals’ consumer bureauEnables 100% resolution of all your portfolio decisions

• More Data is BetterAugmenting commercial information with consumer information on the small business principal owners provides the best predictive risk assessment for your entire portfolioAll models are optimized for whatever data is available

The suite of models driven by commercial data and/or consumer data provide superior separation of good and bad accounts.


Portfolio segmentation in addition to predictive scores and performance data identify good and bad segments within the portfolio

• Industry Standard Segmentation is driven by:ScoreCurrent BalanceDelinquency

• Custom Segmentation includes additional internal performance data such as:

Origination Source: Vendor, Program, Broker etc.Equipment TypeTime in BusinessSales RegionCredit AnalystOther variables important for your specific risk policy needs

Two Types of Segmentation are Available

Internal data layered on a score augments ability to identify risk.


Score

Delinquency

Action

HighHighMedMedLowLow

CCB

Action

Auto DeclineManual ReviewManual Review

Auto Approve up to $100KAuto Approve up to $150K

ABCDE

Credit

Work OutDemand Letter

Reminder LetterNothingNothing

Collections

60+ 30-60

CAA EDC

<30 60+ 30-60 <30 60+ 30-60 <30

All Leases

Scores enhanced with internal performance data enable automated custom action codes to ensure consistent and effective treatment of accounts


Understanding the Risk/Reward trade-off facilitates strategy formulation

Most profitable

PRO

FIT

Charge off and loss

Marginal

Delinquent

Low B

alanceN

on-ProgramM

inimal Spread

RISK

One-Off Lessees

Since 20% of your customers generate 80% of your revenue, an accurate risk assessment of your portfolio is critical

Develop different strategies for the various segments of your portfolio based on the opportunity and risk each represents


The benefits gained by incorporating a Small Ticket Portfolio Solution into your account management process will improve your overall profitability

•Risk •Management

Helps manage portfoliosmore efficiently

Collection Management

Provides tools for prioritization and efficient resource assignment

Securitization

Provides consistent segmentation, reporting and performance tools

Syndications

Helps make knowledge based decisions on which portfolios to buy and sell

Regulatory Compliance

BASEL II: provides the tools to risk rate all small ticket portfolios

One solution can positively impact

multiple functional areas of your business


Additional Lending Information Adds a Critical New Dimension to Your Small Business

Decisioning


New Lending Repositories provide new data sources to evaluate portfolio risk

• Targeted Information– Data from financial institutions about long-term lending to small and

privately held businesses

• Detailed Data– Highly detailed term debt, (loan, lease, business card) payment

performance data stored in it’s own unique database

• Unique Analysis– A unique breakdown of your best and worst customer accounts, and

how those accounts match and compare to other repository participants who maintain accounts with those same customers.

• Strategies and Tactics– Detailed account level data provides critical information for effective

collection and portfolio management


Payment performance data is obtained through an exchange by member financial institutions

Credit Card Issuer A

Leasing Company E

National Bank F

Leasing Company C

Regional Bank B

Local Bank D

SBRI


With the data in the Repositories, you can increase effectiveness by understanding the total credit profile of your customer and taking appropriate collection action.

Poor credit risk

LINES OF CREDIT

Supply Manufacturing, IncDuns: 98-765-4321

Lender ID

Report Date

Total # ofPayments

# of TimesCurrent

Date Opened

Date Closed

Current Credit Line

CurrentBalance

Total Past Due

Your Account

05/03 6 4 09/02 $15,253 $0 $0

04/03 24 12 03/01 $125,500 $50,725 $10,725 05/03 28 16 01/01 $48,285 $18,527 $7,225

Historically has poor payment performance.

High past due debt.

May need to accelerate to Work Out Group


Demographics

Measures

Size of Relationship

Industry Geography Age of Customer

Size of Customer

4 Ranges: - 15 Sectors - 9 Regions 5 Ranges: 8 Ranges: - Major - 81 2-Digit SIC’s - 50 States - 0-3 Years - 1-4 Emp - Large - 1,006 4-Digit SIC’s - 4-6 Years - 5-9 Emp - Medium - 7-9 Years - 10-24 Emp - Small - 10+ Years - 25-49 Emp - 50-99 Emp - 100+ Emp

Dollar Size of Relationship Prior Performance- Total Balance Outstanding - Current Past Due amounts by

Payment Cycle Time - Current Balance Outstanding - Past Due Payments over a

period of time - Original Amounts or Current Credit Limits

Organizational Level Firm Level Site Level Account LevelLinking of all accounts

associated with acorporate family

Linking of all accountsassociated with a corporate

entity

Linking of all accountsassociated with aphysical location

Reviewing eachaccount as a unique

customer

Use Additional Risk Analysis Variables for a Deeper Dive into the Businesses and Accounts

Customer


Payment Comparisons by Like Businesses – Determine Best and Worst Accounts

$29,660$119,302$3,344,126$686,819$540,756$2,672$493,319$6,301Charge Off

$100$25,288$0$159,085$13,281$0$0$0Past Due Cycle 5

$130,514$3,165$0$12,677$918,666$0$0$0Past Due Cycle 4

$27,800$3,462$0$13,770$117,499$0$0$0Past Due Cycle 3

$33,481$3,498$106$14,075$248,642$4,360$26,394$18,310Past Due Cycle 2

$50,243$3,503$890$14,649$463,384$7,030$346,146$46,374Past Due Cycle 1

$243,525$38,916$21,035$214,256$1,774,928$11,390$485,883$65,044Total Past Due

$182,340$3,555$20,519$16,341$4,405,715$14,439$2,652,948$271,320Total Current

2487148964Number of Business

SlowSlowCurrentSlowSlowCurrentCurrentCurrentPayment Manner

SBRIMy Accts


Strategic Uses of Data

• Effectively manage your portfolio to maximize profitability

–Segment the portfolio into actionable buckets

–Increase marketing focus on good segments

–Exit relationships or risk base price on weaker segments

–Prioritize collections efforts


Reaping the Benefits of BASEL II Compliance in Small Ticket Portfolios

Peg Maloney, Managing Director Financial Services D&B


Data

StressTesting

Validation Documentation

Oversight Governance

Models

FunctionalIndependence

Reporting Disclosure

UseandTest

Demonstrated Compliance

Pillar III

Pillar II

Pillar I

The foundation of Basel II compliance is the ability to calculate Pillar 1 Expected Loss. Quality data and accurate predictive models are critical to this calculation.


• Pillar 1- Internal Ratings Based (IRB)- Advanced–Risk Assessment Criteria

• Probability of Default …. PD• Exposure at Default…..EAD• Loss Given Default…..LGD• Lifetime Expected Loss….EL

Quality data and empirically derived portfolio models are the foundation for Probability of Default calculations


PD x EAD x LGD = EL

PD: Probability of DefaultCommon definition of default

• >90 Days past due (ever) or loss / bankruptcy• Validate the SBRPS model on lessor's 90 day accounts

• Substandard Asset, Write-off, RestructureModel driven:

•Empirically developed Fair, Isaac score All assets assigned rating based on model score

•Ability to risk rate all small ticket leasesApplies to all credit transactions

•100% resolution based on commercial and consumer dataOutput expressed as a percentage based on count

•Calculation


PD x EAD x LGD = EL

EAD: Exposure at Default

LGD: Loss Given Default Model driven based on historic data

Data organized around various segmentation strategiesExposure

Vintage year

Equipment

Other correlating factors

• Requires tool to segment leases by any data elements

Output of model expressed in percentage terms


Expected Loss: EL

• PD x EAD x LGD = EL• Trend and segmentation analysis performed

• Scores are accessible throughout the Enterprise on individual transactions as well as on a portfolio basis

• Scores and analysis can be used in ongoing account management and decisioning


Profitable Portfolio Management Begins with Quality Data You can Trust

5

Equipment Leasing Association 2003 Annual Convention

Everyday, You Make Decisions That Greatly Impact Your Business…

• Understanding and managing total risk exposure within your existing customer portfolio

• Identifying and aggressively collecting on high-risk accounts

• Benefiting from regular assessment of the risk of all your customers

• Using your credit resources more efficiently to save money

The success of your business decisions depends on the type of information and the quality of the information driving them

The decisions you make are only as good as the data they are based on

• 240 business addresses will change• 150 business telephone numbers

will change or be disconnected • 112 directorship (CEO, CFO, etc.)

changes will occur• 20 corporations will fail • 12 new businesses will open their

doors• 4 companies will change their

names

…and the Data You Base Your Decisions on is Constantly Changing. In the Next 60 Minutes …

6


Strategic decisions on portfolio management start with confidence in your data

• Whether the Lessee is correctly identified• Is Mike’s Bike Shop really ABC Co. D/B/A Mike’s Bike Shop Inc?

• Whether the payment data belongs to that business

• Was it really Mike’s Bike Shop that paid the XYZ bank loan on time?

• Whether the Lessee is part of a larger corporate family

• Is Mike’s Bike Shop actually a subsidiary of Mike’s Transportation Int’l?

7


ABC, Inc123 Elm St.Bethlehem, PA 18025(SIC) 5411-02Chuck Smith, President

Multiple Unmatched Pieces of Data

Chuck’s Mini-MartP.O. Box 111Bethlehem, PA 18055(SIC) 5411-02Chuck Smith, President610 882-7600

2

Charles Smith123 Elm St.Bethlehem, PA 18025(SIC) 5541-99215 882-7600

3

1D&B D-U-N-S Number:12-345-6780ABC, Inc+ Chuck’s Mini-MartP.O. Box 111Bethlehem, PA 18055123 Elm St.Bethlehem, PA 18025(SICs) 5411 0202, 5541 9901Charles Smith, President610 882-7600

Complete Single Business

1

Entity Matching ensures that a single, accurate picture of each business entity is received

8


Corporate Linkage is critical to view the entire corporate family with no limit in depth or breadth

Fictional example

9


Understanding your portfolio is critical to profitable small ticket leasing.

When You Measure and Benchmark Your Portfolio By …

Risk ProfileRisk Profile

Profit ProfileProfit Profile

Collection ProfileCollection Profile





Improve your collection efficiency with knowledge based account prioritization

You Will Gain the Ability To …

10


Augmenting Quality Commercial Information with Consumer Information as well as Your Own Performance Information Enhances Your Small Ticket Portfolio Risk Assessment and Collections Capabilities

Commercial Data

ConsumerData

New Best Demonstrated Practices

Small Ticket Collections Actions

Financial Performance

Data

Portfolio Modeling Applications

11


Predictive models that use a wide range of data deliver the most accurate small business

risk assessment

• A Suite of ModelsModels driven by Commercial Only, Consumer Only and Blended dataThe appropriate model is selected based on the data availableSelection logic consists of the absence or presence of derogatory information on the principals’ consumer bureauEnables 100% resolution of all your portfolio decisions

• More Data is BetterAugmenting commercial information with consumer information on the small business principal owners provides the best predictive risk assessment for your entire portfolioAll models are optimized for whatever data is available

The suite of models driven by commercial data and/or consumer data provide superior separation of good and bad accounts.

12


Portfolio segmentation in addition to predictive scores and performance data identify good and bad segments within the portfolio

• Industry Standard Segmentation is driven by:ScoreCurrent BalanceDelinquency

• Custom Segmentation includes additional internal performance data such as:

Origination Source: Vendor, Program, Broker etc.Equipment TypeTime in BusinessSales RegionCredit AnalystOther variables important for your specific risk policy needs

Two Types of Segmentation are Available

Internal data layered on a score augments ability to identify risk.

13


Score

Delinquency

Action

HighHighMedMedLowLow

CCB

Action

Auto DeclineManual ReviewManual Review

Auto Approve up to $100KAuto Approve up to $150K

ABCDE

Credit

Work OutDemand Letter

Reminder LetterNothingNothing

Collections

60+ 30-60

CAA EDC

<30 60+ 30-60 <30 60+ 30-60 <30

All Leases

Scores enhanced with internal performance data enable automated custom action codes to ensure consistent and effective treatment of accounts

14


Understanding the Risk/Reward trade-off facilitates strategy formulation

Most profitable

PRO

FIT

Charge off and loss

Marginal

Delinquent

Low B

alanceN

on-ProgramM

inimal Spread

RISK

One-Off Lessees

Since 20% of your customers generate 80% of your revenue, an accurate risk assessment of your portfolio is critical

Develop different strategies for the various segments of your portfolio based on the opportunity and risk each represents

15


The benefits gained by incorporating a Small Ticket Portfolio Solution into your account management process will improve your overall profitability

•Risk •Management

Helps manage portfoliosmore efficiently

Collection Management

Provides tools for prioritization and efficient resource assignment

Securitization

Provides consistent segmentation, reporting and performance tools

Syndications

Helps make knowledge based decisions on which portfolios to buy and sell

Regulatory Compliance

BASEL II: provides the tools to risk rate all small ticket portfolios

One solution can positively impact

multiple functional areas of your business

16


Additional Lending Information Adds a Critical New Dimension to Your Small Business

Decisioning

17


New Lending Repositories provide new data sources to evaluate portfolio risk

• Targeted Information– Data from financial institutions about long-term lending to small and

privately held businesses

• Detailed Data– Highly detailed term debt, (loan, lease, business card) payment

performance data stored in it’s own unique database

• Unique Analysis– A unique breakdown of your best and worst customer accounts, and

how those accounts match and compare to other repository participants who maintain accounts with those same customers.

• Strategies and Tactics– Detailed account level data provides critical information for effective

collection and portfolio management

18


Payment performance data is obtained through an exchange by member financial institutions

Credit Card Issuer A

Leasing Company E

National Bank F

Leasing Company C

Regional Bank B

Local Bank D

SBRI

19


With the data in the Repositories, you can increase effectiveness by understanding the total credit profile of your customer and taking appropriate collection action.

Poor credit risk

LINES OF CREDIT

Supply Manufacturing, IncDuns: 98-765-4321

Lender ID

Report Date

Total # ofPayments

# of TimesCurrent

Date Opened

Date Closed

Current Credit Line

CurrentBalance

Total Past Due

Your Account

05/03 6 4 09/02 $15,253 $0 $0

04/03 24 12 03/01 $125,500 $50,725 $10,725 05/03 28 16 01/01 $48,285 $18,527 $7,225

Historically has poor payment performance.

High past due debt.

May need to accelerate to Work Out Group

20


Demographics

Measures

Size of Relationship

Industry Geography Age of Customer

Size of Customer

4 Ranges: - 15 Sectors - 9 Regions 5 Ranges: 8 Ranges: - Major - 81 2-Digit SIC’s - 50 States - 0-3 Years - 1-4 Emp - Large - 1,006 4-Digit SIC’s - 4-6 Years - 5-9 Emp - Medium - 7-9 Years - 10-24 Emp - Small - 10+ Years - 25-49 Emp - 50-99 Emp - 100+ Emp

Dollar Size of Relationship Prior Performance- Total Balance Outstanding - Current Past Due amounts by

Payment Cycle Time - Current Balance Outstanding - Past Due Payments over a

period of time - Original Amounts or Current Credit Limits

Organizational Level Firm Level Site Level Account LevelLinking of all accounts

associated with acorporate family

Linking of all accountsassociated with a corporate

entity

Linking of all accountsassociated with aphysical location

Reviewing eachaccount as a unique

customer

Use Additional Risk Analysis Variables for a Deeper Dive into the Businesses and Accounts

Customer

21


Payment Comparisons by Like Businesses – Determine Best and Worst Accounts

$29,660$119,302$3,344,126$686,819$540,756$2,672$493,319$6,301Charge Off

$100$25,288$0$159,085$13,281$0$0$0Past Due Cycle 5

$130,514$3,165$0$12,677$918,666$0$0$0Past Due Cycle 4

$27,800$3,462$0$13,770$117,499$0$0$0Past Due Cycle 3

$33,481$3,498$106$14,075$248,642$4,360$26,394$18,310Past Due Cycle 2

$50,243$3,503$890$14,649$463,384$7,030$346,146$46,374Past Due Cycle 1

$243,525$38,916$21,035$214,256$1,774,928$11,390$485,883$65,044Total Past Due

$182,340$3,555$20,519$16,341$4,405,715$14,439$2,652,948$271,320Total Current

2487148964Number of Business

SlowSlowCurrentSlowSlowCurrentCurrentCurrentPayment Manner

SBRIMy Accts

22


Strategic Uses of Data

• Effectively manage your portfolio to maximize profitability

–Segment the portfolio into actionable buckets

–Increase marketing focus on good segments

–Exit relationships or risk base price on weaker segments

–Prioritize collections efforts

23


Reaping the Benefits of BASEL II Compliance in Small Ticket Portfolios

Peg Maloney, Managing Director Financial Services D&B

24


Data

StressTesting

Validation Documentation

Oversight Governance

Models

FunctionalIndependence

Reporting Disclosure

UseandTest

Demonstrated Compliance

Pillar III

Pillar II

Pillar I

The foundation of Basel II compliance is the ability to calculate Pillar 1 Expected Loss. Quality data and accurate predictive models are critical to this calculation.

25


• Pillar 1- Internal Ratings Based (IRB)- Advanced–Risk Assessment Criteria

• Probability of Default …. PD• Exposure at Default…..EAD• Loss Given Default…..LGD• Lifetime Expected Loss….EL

Quality data and empirically derived portfolio models are the foundation for Probability of Default calculations

26


PD x EAD x LGD = EL

PD: Probability of DefaultCommon definition of default

• >90 Days past due (ever) or loss / bankruptcy• Validate the SBRPS model on lessor's 90 day accounts

• Substandard Asset, Write-off, RestructureModel driven:

•Empirically developed Fair, Isaac score All assets assigned rating based on model score

•Ability to risk rate all small ticket leasesApplies to all credit transactions

•100% resolution based on commercial and consumer dataOutput expressed as a percentage based on count

•Calculation

27


PD x EAD x LGD = EL

EAD: Exposure at Default

LGD: Loss Given Default Model driven based on historic data

Data organized around various segmentation strategiesExposure

Vintage year

Equipment

Other correlating factors

• Requires tool to segment leases by any data elements

Output of model expressed in percentage terms

28


Expected Loss: EL

• PD x EAD x LGD = EL• Trend and segmentation analysis performed

• Scores are accessible throughout the Enterprise on individual transactions as well as on a portfolio basis

• Scores and analysis can be used in ongoing account management and decisioning

29

Documents

Measuring & Managing Credit Portfolio Risk 1 · 2004-07-15 · Measuring & Managing Credit Portfolio Risk: ... • Understanding and managing total risk exposure within your existing