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Slides Pres. Credit Alliance Jan 2011

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slides on global credit scoring quality

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Slides Pres. Credit Alliance Jan 2011

  1. 1. Credit Scoring:World Wide Quality &Lessons learnedGertjan Kaart 18 01 2011Graydon Nederland1 CreditAlliance Annual General Meeting, January 18th, 2011
  2. 2. Topics • World wide scoring. • One size fits all? • Interpretation: AAA = AAA? • Quality of scoring models • Quality, what is that? • Criteria and business requirements • Experiences and improvements • Crisis • Innovation by co creation2
  3. 3. World wide quality and Granularity • High granularity of scores results in best quality use the best/detailed (market) data available • Multiple models based on availability & accuracy of • DEFAULT data • INPUT data  Guarantees optimal use of data, and fine tune multiple models to market/data conditions in order to get higher quality results.3
  4. 4. Blending 2 scores4
  5. 5. Many models: Interpretation of scores? • Standardization of presentation and notation of scoring model outcomes. • PD % attention: what is the definition of default! • PD rating scales (example rating classes AAA, B, etc) attention: what is the mapping!  Basel committee publishes a mapping, with default rating classes.5
  6. 6. Definition of quality of credit scores? • Gini, distribution, CDR (technical quality)6
  7. 7. Definition of quality of credit scores? • Gini, distribution, CDR (technical quality)7
  8. 8. Definition of quality of credit scores? • Gini, distribution, CDR (technical quality) • Coverage • Speed and uptodateness • Delivery (structured data, workflow integration, etc) • Presentation (interpretation) • Services (value add / monitoring, benchmarking, decision engines) • Price • Customer complaints (type 1) • Usage / users8
  9. 9. Experiences • More educated users and customers • More awareness of the value of info and ratings • Trend? Social business media: publish your own ratings • Crisis; sudden death cases. Changing rules of the game. • Frequency of calibrating of models must go up • More need for behavioral data (accuracy) • Break down Chinese wall between information suppliers and users (and objects).9
  10. 10. Experiences10
  11. 11. Experiences • More educated users and customers • More awareness of the value of info and ratings • Trend? Social business media: publish your own ratings • Crisis; sudden death cases. Changing rules of the game. • Frequency of calibrating of models must go up • More need for behavioral data (accuracy) • Break down Chinese wall between information suppliers and users (and objects).11
  12. 12. Credit Scoring:World Wide Quality &Lessons learnedGertjan Kaart 18 01 2011Graydon Nederland12 CreditAlliance Annual General Meeting, January 18th, 2011

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