Radix Analytics Pvt Ltd

Credit Scoring for Leasing Company

Radix Analytics Pvt Ltd > AI ML > Credit Scoring for Leasing Company

Issues & Objectives

  • A large company in UK finances lease of office equipment, primarily to small and medium companies with ticket size less than £10K
  • Leased items depreciates rapidly and seizure of collateral does not recover the debt
  • The company currently cherry picks customers who seldom go bad
  • They want to expand customer base while controlling risk
  • For this they want a scorecard to replace rule driven underwriting for better screening

Benefits

  • Scorecard developed by Statistical method
  • Scrutiny restricted to high scorers reducing manual work by a factor of 5 -10

Project information

Techniques

Risk Analytics

Client

Equipment Leasing Company 

Industries

Financial Services

Location

UK

Challenges

  • Company book identified only 2.5% bad lease – payment history data was fraught with inconsistent figures
  • After incorporating liquidation/insolvency/dissolution status and rating from credit bureau record, the incidence was boosted to 12%. The process classified non takers of loan to Good and Bad by a logical method and not by reject inference

Solution

  • Model developed by R program
  • 2 scorecards with and without credit bureau ratings were delivered
  • Discriminatory power of the scorecards were high as seen from high KS and GINI

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