Tomas Denemark

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Tomas Denemark

  1. 1. CREDIT SCORING  It is better to count than to guessTomáš DenemarkKIEV, September 2012 www.arbes.com
  2. 2. Content Credit Scoring as a key element of the Credit Granting Process Credit Scoring Introduction Judgmental vs. Statistical Decision Statistical Scoring Methodology … Credit and behavioural scoring are some of Credit Scoring Typology the most important forecasting techniques used in the retail and consumer finance area… Credit Scoring Data Sources …. With the connections being made between scoring for default and scoring for targeting Credit Scoring Risks potential sales, the scoring techniques will Conclusion clearly be used to forecast the sales of products as well as the profit a company will make in the future…. Source: A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers - Lyn C. Thomas* - Department of Business Studies, University of Edinburgh,Page 2
  3. 3. Retail Consumer Credit Lending Process Application Pre-scoring Internal Verification data collection calculation decision Additional Credit Bureau Public Bureau Credit scoring documents data collection data collection collection Continue Reject Credit Risk Credit Risk premium Final credit strategy agreement calculation decision decision signature Manual tasks Engine tasks Disburse Credit account money order opening CombinationPage 3
  4. 4. Micro Finance Credit Lending Process Detailed Pre-scoring and Public & Non-Credit product Interest of Application product internal Financial data promotion potential debtor form description decision collectionCredit Bureau Risk Premium Credit Final loan data files Data entry Credit scoring and collateral committee and decision Collection calculation loan analysis Client signatureClient approval Paperwork Disburse finance Regular follow Behavioural and collateralannouncement finalization funds up credit scoring authorization On-time Late payments Credit Bureau Soft Collection Late Collection collection procedure score procedure procedurePage 4
  5. 5. Credit Scoring Introduction Credit scoring is a statistical-based technology that quantifies credit risk Primary goal is to rank individuals, distinguishing lower and higher risks Credit scoring was developed in order to provide quick, accurate, inexpensive and consistent credit evaluation Credit history or “bureau-based” scores are based exclusively on credit record data from credit reporting agencies Credit scores are widely used to: evaluate and price credit based on Probability of default JUDGMENTAL vs. STATISTICAL identify prospective borrowers for acquisition manage existing clients and its accounts Scoring is heavily used in banking, consumer finance and insurance, and also in employment,Page 5 utilities and marketing ???
  6. 6. Decision: Statistical vs. Judgmental Scoring BOTH Assume that the future will resemble the past Compare applicants to past experience Aim to grant credit only to acceptable risks EVALUATED VALUES JUDGMENTAL STATISTICAL STATISTICAL SCORE ADDED VALUE Age + 10 Defines degree of credit risk for each Income - 5 applicant Marital Status + 7 Ranks risk in relation to other applicants Household + 4 ….. ….. ….. Allows decisions based on degree of risk # of Credit Aplications 6M - 28 Enables tracking of performance over time % of Avg. Credit Lines Usage + 23 Permits known and measurable …… …… …… adjustments Total + 135 _____________ ______ ______ Permits decision automation Decision Accept Accept PD ?? 2,8%Page 6
  7. 7. Comparison of Individual Credit Processes Performace Figures 500 450 400 350 300 250 200 150 100 50 0 Average processing time (minutes) Variables required (data Average costs per application Accuracy (Delinguent fields) (USD) cases /1000) Standard Credit Loan Granting Process with Judgmental Decision Credit Loan Granting Process with Financial and Non Financial Analysis Credit Loan Granting Process with Credit Scoring Based Decision Source: MFI pool ResearchPage 7
  8. 8. Statistical Scoring - Methods LINEAR REGRESSION LOGARITHMIC REGRESSION CLASSIFICATION TREES RECURSIVE PARTITIONING ALGHORITMS LINEAR PROGRAMMING NEURAL NETWORKSPage 8
  9. 9. Credit Scoring Typology Application Score - Application scores are a type of credit score used by banks and finance houses to decide which applicants are to be taken on, based purely on the information given in the credit application form. This scoring is heavily used during the acquisition period of a credit life cycle. Bureau Score - A Bureau Score is a credit score which is calculated only based on the information from a detailed credit report. Sometimes there is a mixture of private and public credit reports used to obtain the „bureau score“. This scoring is heavily used during acquisition, monitoring and collection periods of a credit life cycle. Behavioural Score – This is limited to existing client portfolio of a bank or a finance house. This score allows lenders to make better decisions in managing existing clients by forecasting their future performance. This score is heavily used for credit limit renewal, credit limit increase, up-selling, cross-selling and also for the soft collection period of a credit life cycle.Page 9
  10. 10. Credit Scoring Data Sources (Retail) Credit application Banking credit history Banking deposit history Credit bureau report Public bureau report Public debtor databases Register of pledges Demographics Billing file Deal termsPage 10
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  12. 12. Concerns over Credit Scoring Influence on the Credit Granting Process Credit scoring may have adverse effects on certain populations, particularly minorities Credit scoring is not loss prevention panacea and it is neccessary to keep that in mind during credit lending process definition and design Some factors used to estimate credit scores may have an adverse effect on certain groups Automated technologies may disadvantage individuals with nontraditional credit experiences Judgmental evaluations may be better able to detect errors or inaccuracies With lending and retailing becoming more automated, risky consumers will face growing disadvantages and this may lead to some acting in the name of social justicePage 12
  13. 13. Conclusion The Credit Lending Industry is an area, where RISK is the norm rather than the exception It is necessary to adopt many measures which may help to reduce exposure to high risk Those who would like to win the market battle have to find a balance between risk and return on assets Credit scoring is a pragmatic and widely proven method of risk identification and quantification The statistical credit scoring model is much more powerful than a judgmental opinion and decision The use of credit scoring during loan providing and monitoring is an essential feature of a modern bank and its implementation costs are quickly recovered Companies that are confident in their models, will start cherry picking and can target the most profitable customers.Page 13
  14. 14. Thank you for your attentionTomáš DenemarkFinancial Systems & Enterprise Applications DirectorARBES Technologies, s.r.o.+420 724 096 904tomas.denemark@arbes.comwww. Arbes.com www.arbes.com

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