The document discusses credit vetting and debt management strategies aimed at maximizing profitability while managing debts effectively. It emphasizes the importance of reporting, prediction, and prevention in debt management processes and highlights the need for automated and flexible systems for scorecard development. Key strategies include optimizing collection techniques, improving cash flow, and enhancing customer retention through effective communication and tailored approaches.

1. Credit Vetting & Debt Management İnci Akalp

2. Outline Profitability vs. Debt Management Debt Management Processes Scorecard Development Prevention Strategies for the Bad Debt Collection & Recovery of Bad Debt

3. Profitability is the main aim of a firm… If we have only profitable customers (nearly %80 of population), then we will have the same cumulative profit. To maximize the total profit, we should know the reasons of loss.

4. Managing debts will … Maximize profit by increasing the recovery of cash collected Improve cash flow by ensuring earlier recovery of debt Reduces costs through the collection techniques Increase customer retention through communication with debtor” which consists of … automated decisions and strategies appropriate collection techniques optimized automatic actions

5. Debt Management includes … Batch Reports Ad-hoc Reports Predictive Models Strategies Reporting What happened? Risk Dashboard Periodic Reports Analyzing Why did it happen? Predicting What will happen? Taking Action What should we do? Collection Recovery of Bad Debt Scorecards Fraud Model Cause analysis

6. A good Debt Management needs … An automated but also flexible reporting system ,that gives a chance to us, quick development of new reports or small changes for old ones Periodically fine-tuned or re-developed scorecards , models with simple implementation Simple, actionable and also applicable prevention, collection and recovery strategies.

7. Scorecard Development Target definition Data collection quality, relevance, size of the data up-to-date and evolving data asset missing values( imputation-SAS , scoring-KXEN) Sampling time maturity balancing the ratio Choosing the best variables/model robust simple non-correlated Segment-based models (if it is needed) Validation Deciding the score cut off accept/reject ratio Profitability Monitoring TTD population Dashboard Fine-tunings Re-development

8. Scorecards vs. Customer Life Time SM Tools Suggestions Experian NBSM Experian ProbSM Fair Isaac Debt Manager Fair Isaac Triad e.g. Acquisition Nursery 0-12 months Existing 12+ months Customer Life Time Scorecards Application Scorecard AS+ Policy Rules Behavior Scorecard

9. Prediction implies Prevention … Customer Side Not offer up-sell/cross-sell campaigns Risk profile based campaigns time limitation ( especially for commercials ) Limit the number of accounts per customer Sales Network Side Charging a fee from seller when Bad Debt occurs

10. Our delinquent customer will be delinquent … Collection plan SMS time decision Collection Calls predictive calling target system ( amount ) Direct Mailing Response Analysis best time/channel/customer Pre-legal settlement offers Recovery plan Maximize recovery amount Minimize costs Lawyers monitoring their performances monthly targets

11. Summary Debt Management -> Maximize profit & reduce costs Debt Management = Reporting + Prediction + Prevention + Collection Data is very important for the Scorecard development. External data (Credit Bureau) Real-time vetting Credit Vetting = Scorecards +Policy Rules Solutions for Bad Debt = Prevention + Collection + Recovery Optimization of cost/revenue/time Customer level relationship Champion/Challenger Strategies

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