1. Understanding Credit Scoring Techniques and Best Practices FCFP Forum October 12-13, Atlantic City, NJ
Jan Rowland, Ph.D.
Leader, Data and Analytical Strategy
Rich Ferrera, CCE
Leader, Trade Credit Best Practices
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2. Agenda Challenges in today’s credit risk management discipline
How credit scoring can help
Overview of credit scoring
What is a credit score
Who uses credit scores
How are credit scores created
Credit scoring best practices
Credit Application Evaluation
Portfolio Management
Collections
Fraud Screening

3. In today’s fast-paced business environment, managing risk and improving cash flow are more challenging than ever before…
You are at greater risk from incurring potential bad debt due to bankruptcy and fraud
You need to increase cash flow at a time when economic pressure is causing companies to use you as a source of funding by paying you slower
You are under pressure to make your credit function more efficient without increased risk
You must comply with increased regulation, such as the Sarbanes-Oxley Act, which requires financial executives and credit practitioners to better understand risk in their portfolios
You need to do all of the above very well … while maximizing your company’s sales by approving all reasonable requests for credit!!!

4. Credit Application Evaluation
Businesses are seeking best practices for developing objective, accurate risk assessment systems that address key questions...
Business Need
Credit scoring can help
Credit Application Evaluation
How can we be sure we are efficiently and consistently delivering credit decisions across the entire organization that are consistent and comply with policies and drive revenue?
Quickly and more accurately assess risk among your new business applicants
Portfolio
Management
How can we consistently analyze risk exposure across the whole organization to protect the firm from an unforeseen major loss?
Easily identify changes in risk across your entire portfolio to minimize exposure and decrease costs

5. Credit scoring can help businesses answer these questions and maximize their company’s profitability by providing five critical benefits
Target Credit-Worthy Customer for Future Promotions
Increase Approval Rates
Decrease Bad Debt
Reduce Exposure to High Risk Accounts
5. Increase
Sales
1. Reduce
Risk
4. Increase
Consistency
2. Increase
Speed
Quickly Handle Obvious Approvals/Declines
Less Data is Required to Make Accurate Decisions
3. Increase
Efficiency
Ensure Equal, Objective Treatment of Each Applicant
Apply Consistent, Objective Decisions Across the Organization
Analysts Only Focus on Difficult Accounts
Increase Volume of Accounts Evaluated with Same Staff

6. Agenda Challenges in today’s credit risk management discipline
How credit scoring can help
Overview of credit scoring
What is a credit score
Who uses credit scores
How are credit scores created
Credit scoring best practices
Credit Application Evaluation
Portfolio Management
Collections
Fraud Screening

7. Credit scoring is a quantitative tool to assess the risk of lending money to a particular consumer or business
Consumer credit scores predict how you will pay your credit cards, utility bills, car loans, mortgage etc.
Business credit scores predict how a business will pay it’s trade credit, business loan, business card, lease, office utilities, legal services etc.
Results of a credit score provide guidance regarding:
Who will get credit
How much credit they should get
What pricing strategies should be extended to enhance profitability

8. Credit scores come in a variety of flavors
Credit scores come in a variety of flavors. When choosing a credit score for your company it is crucial to ensure the event the model is predicting clearly addresses your critical business needs
Delinquency Models predict the future payment performance of your business customers
Bankruptcy Models predict the likelihood of a business failing
Recovery Models are applied to customers you placed in collection. They predict the likelihood of recovery and provide an estimated collection amount
Fraud Models identify businesses that have a higher likelihood of being fraudulent

9. Agenda Challenges in today’s credit risk management discipline
How credit scoring can help
Overview of credit scoring
What is a credit score
Who uses credit scores
How are credit scores created
Credit scoring best practices
Credit Application Evaluation
Portfolio Management
Collections
Fraud Screening

10. One out of three businesses are currently using credit scoring to help manage their receivable portfolio
36% of the 329 businesses surveyed have integrated credit scoring into their risk management practices
These businesses tend to have more than $1 billion in sales and over 7,500 active accounts
92% of businesses surveyed use credit scoring for new account evaluation and 88% review existing customers
Another 42% of businesses surveyed anticipate utilizing credit scoring within the next 5 years
8 out of 10 businesses currently using a credit scoring system report that the scoring system is meeting their expectations
Source: CRF Study. Credit Scoring: The Future of Decisioning in the A/R Process, 2003

11. Agenda Challenges in today’s credit risk management discipline
How credit scoring can help
Overview of credit scoring
What is a credit score
Who uses credit scores
How are credit scores created
Credit scoring best practices
Credit Application Evaluation
Portfolio Management
Collections
Fraud Screening

12. Credit scores are just one component of a comprehensive scoring system that can help you manage risk among your new and existing accounts 3 2 1
Higher
Risk
Decline or Cash Terms
Commercial Bureau Information
Application for Credit
Automated Scoring
Consumer Bureau Information
Application Processing
Business Decision Rules
Medium Risk
Analyst Review
Low
Immediate Approval
Decision Rules
Information
Scores
Technology

13. INFORMATION: The most predictive scorecards are designed to utilize the widest range of information
Payment experiences provide an accurate picture of how a company is paying a wide variety of financial obligations
Public record information (Suits, liens, judgments, bankruptcies and UCC filings) could affect a company’s ability to pay and survive
Financial information provides an understanding of the financial strength of a business and it’s ability pay on time
Firmographic information identifies higher risk business segments
Without D&B’s Global Data Collection you can take on unnecessary risk with customers and experience process inefficiencies
Having limited payment experiences provides skewed or incomplete payment behavior leading you to over or under extend credit
Missing historical derogatory information excludes insight to management experience and past failures
Viewing incomplete public records and legal suits makes it harder to foresee future bad debt and possible insolvency
Excluding private company financial information hinders the decision process by eliminating critical cash flow and profitability information
Sourcing from multiple data providers results in a loss of efficiency with many file formats and inconsistent cross-border data

14. Business Demographics
INFORMATION: Hundreds of data variables are analyzed to determine the credit scoring model variables; here are some commonly used ones
Financial
Credit
Business Demographics
Receivables
Payables
Cash
Dividends
Current Liabilities
Current Assets
Working Capital
Net Worth
Payment History
Trade Experiences
Bank Loans
Secured Financing
Public Filings
Previous Bankruptcy
Trends
Condition Assessment
Line of Business
Size (employee, sales)
Years in Business
Business History
Suits, Liens, Judgments
HQ/Branch/Single Loc.
Location
Special Events

15. Compounding Effects of Multiple Negative Factors
INFORMATION: The precise combination of the key business and principal owner characteristics provide the most accurate assessment of risk
Probability Of Delinquent Payment
26.3%
30%
25%
11.7%
20%
7.3%
Business History
15%
Region
4.6%
10%
Industry
Negative Experiences 5%
0.7%
Payment Index 0%
Compounding Effects of Multiple Negative Factors

16. Very likely to pay on time
SCORES: Simply put, credit scoring is the process of using historical outcomes to predict future outcomes
A proven, effective risk evaluation tool to condense hundreds of attributes about the business and/or business owner into one easy to interpret score, that estimates a company’s future performance
Business and Business Owner Characteristics (Variables)
Risk Assessment
Historical Outcome
95 / 100
= ‘A’
Very likely to pay on time 95
Predictive Models rely on Statistics which utilize “Probabilities” which apply to groups -- you must judge score performance on a large sample, not on an individual business

17. SCORES: There are various approaches for creating the optimal combination of business attributes
Rules Based vs. Statistical methodologies
Standard vs. Custom scores
Commercial vs. Small Business scores

18. SCORES: The most common Credit Scoring methodologies are
Expert / Judgmental / Rules Based
Rules and weights are set by the user based on their experience
Complete flexibility setting up decision criteria
Automates your current policies & procedures, but does not improve accuracy of assessment
Statistical
Utilizes multivariate statistical techniques to find significant correlations between business attributes and delinquency or failure
Weights derived mathematically based on the relative importance of each business attribute
Typically results in most accurate assessment of risk

19. SCORES: While Custom Scoring Models are an option, most businesses begin their risk assessment with a statistically-based, generic commercial model
Standard Scoring Models
Sample and outcome selected from business bureau universe (does not use your data)
Predicts likelihood of a business paying any financial obligation on time
Performance can be validated on own portfolio
No Up-front investment is required
Custom Scoring Models
Most predictive solution
Combines information from a user’s customer base with bureau data
Predicts likelihood of a business paying you on time
Objective of model can be tailored to fit specific business goals
Requires a representative sample of user’s experience

20. SCORES: Finally, you will want to map the optimal score to the types of businesses in your portfolio
Commercial Risk Scores
Scores driven purely by information about the business (commercial data)
Most often used for risk assessment of small to medium size businesses
Small Business Risk Scores
Scores driven by information about the business (commercial data) and business owner (consumer data)
Most often used for risk assessment on micro-businesses (emerging businesses using consumer credit) and small businesses (for example, less than 10 employees or decisions under $100,000)
Well suited for companies willing to adopt consumer credit legal requirements

21. SCORES: Regardless of which approach you select the final scorecard will be comprised of points assigned to attributes of a characteristics. The accumulation of points determines the ultimate score.
CHARACTERISTIC
ATTRIBUTES
SCORE
Ownership
Owns Facility 40
Leases Office Space 25
11+yrs 50
6-10yrs
3-5yrs 35
0-2 yrs 20
<6mo 15
6 – 12
13- 24
13 – 24
Time as owner
Time since most
recent delinquency
<10% 10
10 – 49% 20
50 – 79% 30
80% & Up 40
10+
-40
5 – 9
-10
1 - 5 15
170
% Good trades
# of public records
Total
High Risk
Low Risk
200

22. SCORES: As an illustration, here’s a business that has a higher risk of delinquency vs. one that has a lower risk of delinquency
Restaurant business established in 2005
Management has history of previous bankruptcy
Payments are typically 60+ days past terms
There are suits filed against this firm
Leases office space
Manufacturing business established in 1979
There is no history of management involved with previous bankruptcy or other negative experiences
Payments are typically paid within terms
There is no evidence of suits, liens or judgments
Owns facility
Higher Risk Business
Lower Risk Business
Please note this is for illustration and that the final determination of risk level is based on the combination of data variables.

23. SCORES: The credit score is then used to distinguish good accounts from bad ones and to set approval and decline cutoffs that meet your risk and sales objectives
…you’ll have a delinquency rate of only 6%...
Approve accounts that score a 71 and above, which is 30% of your new applications…
…and you’ll identify & screen out up to 93% of bad accounts.
Risk Class
Score Percentile
% of Bads Identified 1
91-100
2-4%
97-99% 2
71-100
30%
4-6%
88-93% 3
31-100
70%
8-9%
57-62% 4
11-100
90%
11-13%
26-34% 5
1-100
100%
13-17% 0%
% of Accounts
Delinquency Rate
10%
Cordell

24. % of Bad Accounts Expected
DECISION RULES: Credit professionals can maximize the impact of credit scores by combining their decision rules with credit scores to drive credit decisions
Decision
Rules
Credit
Decision
Scoring
Percentile Ranking
% of Accounts
% of Bad Accounts Expected
Net Worth
Credit
Credit Line
91-100
10% 1%
$1M+ $1<$1M
Approve Approve
Up to $20,000 Up to $10,000
31-90
60%
28%
Up to $10,000 Up to $5,000
11-30
20%
27% _
Analyst Review
1-10
44%
Approve
Pre-Pay Only
The most efficient way to use scoring is to develop a Decision Matrix. A decision matrix is a table or set of rules which provides your credit staff with rules for different credit situations. Essentially, it is the core of your credit policy, and is based upon your specific portfolio of accounts and your unique business needs.
Scoring is used to establish the cutoff points (cutoff scores or “score ranges”) for each different credit rule (decision) in the decision matrix. Cutoff scores divide your customer portfolio into risk segments. (In this example, any applicant with a score above the cutoff score of 30 will be automatically approved, and their credit line will be determined by their net worth. Any applicant at or below the cutoff score of 30 will be automatically turned over for review or rejected.)
Cutoff scores help you reduce the number of accounts sent to your analysts in their credit decision process by automatically accepting/rejecting the majority of their applicants.

25. Agenda Challenges in today’s credit risk management discipline
How credit scoring can help
Overview of credit scoring
What is a credit score
Who uses credit scores
How are credit scores created
Credit scoring best practices
Credit Application Evaluation
Portfolio Management
Collections
Fraud Screening

26. Credit Application Evaluation
Credit Scoring best practices enable businesses to efficiently protect themselves from higher risk customers
Prioritize Internal Efforts based on Collectibility
Optimize Use of Third party Agencies
Fraud Screening
Screen for Previous Fraud
Evaluate Potential for Future Fraud
Collections
Credit Application Evaluation
Automatic Approval/Decline
Set Credit Line
Price for Risk
Portfolio Analytics & Benchmarking
Account Management & Monitoring
Dynamically Update Credit Lines
Trigger Collections Activity on Delinquent Accounts
Portfolio Management

27. CREDIT APPLICATION EVALUATION: Scoring makes the credit process more efficient by segmenting accounts for automated approval, decline, special terms or requiring analyst review
Immediate Approval
Application Processing
Outside Information
Application
for
Credit
High Scores
Low Exposure
Targeted Markets
Business Decision Rules
Gray Area
Analyst Review
Automated
Scoring
Decline or Special Terms
Fraud Risk Score
Delinquency Score
Failure Score
Middle Scores
High Exposure
Review Criteria
By incorporating predictive scoring into your approval process, you can decrease the time to make a decision from days to minutes, so sales can respond immediately to customers. By automating credit decisions that are “obvious” -- for example, the obviously good or bad ones -- credit analysts are free to devote more time and attention to cases that need review (gray area).
Very Low Scores
“Knockout” Criteria

28. CREDIT APPLICATION EVALUATION: Let’s look at a best practice implemented by one business using a standard credit score in its new account risk management process
Situation: Client needed a system to replace a credit decision matrix that would:
Reduce lease application turnaround time from five (5) hours per application
Improve productivity by automatically approving lowest risk applicants and rejecting highest risk applicants
Solution: Client implements a generic commercial credit score which predicts the probability that an applicant will become severely delinquent within the next 12 months in their new applicant decision-making process
Results:
Client reduced lease application turnaround time from 5 hours to 1 hour 45 minutes
Client increased processing volume to more than 75,000 application per year without increasing staff
Client is able to automate 69% of their new applications, freeing up its analysts’ time to focus on the 31% of “gray area” cases

29. Scorecard Decision Overridden by Analyst 1 Out of 2 Times
CREDIT APPLICATION EVALUATION: In this example a manufacturing company reduced its delinquency from 1.8% to .8% with the integration of a custom credit scoring model
Automated Decisions
Manual Review
Approved
Declined
Scorecard Decision Overridden by Analyst 1 Out of 2 Times
.8% Delinquency
3.5% Delinquency
1.8% Delinquency

30. PORTFOLIO MANAGEMENT: Account management based on your internal data only, limits your ability to assign effective treatment strategies
With internal performance data you may treat all accounts
that are days delinquent the same
When they should be treated differently
Watch
Closely
Send to
Collection
Collect
Late
Fees
Investigate
Service
Issue
Increase Credit Line

31. (Based on Credit Score)
PORTFOLIO MANAGEMENT: Integrating external business scores into your account management strategy provides you with greater insight to more effectively manage your accounts
(Based on Credit Score)
Credit Risk
Your Aging
1-30
Days
31-60
61-90+
High
Medium
Low
Collect
Late
Fees
Investigate
Service
Issue
Send to
Collection
Increase Credit Line
Watch
Closely
* Sort Accounts by Past Due Amount Within Priority Group

32. Traditional Collections Treatment Credit Score Targeting
COLLECTIONS: Collections Treatment Strategy Based On Credit Scores Resulted in a 75% Improvement in Performance
75%
Improvement
Share of Balances 90 or
More Days Past Due
Traditional Collections Treatment
Credit Score Targeting

33. In summary, credit scores…
Predict future events based on historical occurrences
Are effective tools to evaluate high volumes of transactions to free analyst focus on higher exposure accounts
Provide effective tools for consistent, efficient and effective risk management evaluation of new and active accounts
Require four (4) essential components:
Timely, accurate information
State of the Art predictive scoring techniques and expertise
Actionable Business Rules
Automated Decisioning

34. The following guidelines will help you choose the scoring solution that best meets your needs…
Define your business application
Evaluate new applications – New Account Model
Account and portfolio management – Behavioral Model
Prioritize collection efforts – Recovery Score
Fraud detection – Fraud Score
Clearly state the event you would like to predict
Understand your target market or portfolio personality
Commercially credit active small to medium size business – Commercial Scorecards
Start up and very small businesses that also utilize personal credit to finance their business – Blended Scorecards

35. Understanding Predictive Scoring Techniques and Best Practices
Live demonstration of how credit scores are used in practical applications

36. Example Scorecard

37. Example Scorecard