IFRS 9 Compliance
ECM Analytics is mathematically constructed and actuarially informed (forerunner of Artificial Intelligence) to measure and thereby manage the lender’s retail loan portfolio.
Credit Expo’s primary and most popular product
This is Credit Expo’s main and most popular product. It is mathematically constructed and actuarially informed to measure and thereby manage the lender’s retail loan portfolio. The new international reporting regulations, IASB 9 and FASB represent a radical shift from the former Incurred Loss Model to the Expected Loss Model, for loss provisioning. (ECM includes all the principals of AI analysis)
How we can assist.
Introduced in the US in 2020 the Credit Reporting Regulations for retail credit Risk are known as FASB (also CECL).
The European Regulations are IASB, and they were introduced in 2018.
To avoid regulatory arbitrage, both IASB and FASB have the same requirements and both reference IFRS 9. With minor variations allowed for local interpretation, the requirements of IFRS 9 include the following:
Key requirements of IASB, delivered by ECM
Calculation must include reference to reliable credit scores, but should not depend overly on the scores which can only calculate risk for the borrowers
- Calculations of Provisions must be calculated on the lender’s own experience, (empirical) rather than being, as formerly, based on fixed rate assumptions of credit risk exposures
- Calculations must include credit risk in the Well Performing (up- to- date) Loans, embracing the Expected Loss Model, rather than being, as formerly, confined to recorded arrears (the Incurred Loss Model)
- The base statistics must reference the lender’s experience over an adequate time period, viz. between two and three years
- Loan assets must be differentiated and segmented to provide a real basis for differentiation of risk calculations, e.g. cars, versus home improvement loans.
- The Lender’s recovery experiences must be recorded and verifiable, as an important input to the risk calculation
- The base statistics must be recent. Historical statistics are important for comparatives and for trend analysis, but recent figures are the more relevant
- The data base must be large enough to be statistically reliable.
- Calculation must include reference to reliable credit scores, but should not depend overly on the scores which can only calculate risk for the borrowers
- Calculations should be variable over time and should be seen to respond to prevailing local and economic conditions
Analytics
ECM Analytics, not only fully complies with the above macro-level IFRS 9 requirements, but provides in addition, invaluable micro-level calculations e.g. Credit Risk Pricing, Portfolio Valuations, together with full League Tables for all risk contributors, viz, Loan Officers, Referral Sources, Asset Types, Loan Maturities and all other characteristics.
ECM Analytics provides all the risk quantifications, from the portfolio level, down through the characteristics into the loan sectors and sector combinations (an early form of AI.)
Note: Credit Scoring, on the other hand, as supplied by Experian, Trans Union, Dun and Bradstreet and CRIF, provides NO quantification, or risk measures. Credit Scores give approximate ‘ Yes’, ‘ No’, and qualified ‘ Maybe’ answers on the loan applicants, without reference to the Assets, the Specific Geography, or Surrounding Characteristics.
For precise quantification, Credit Scores should ideally be integrated with ECM Analytics.
Complimentary Consultation
We would be delighted to undertake a complimentary consultation to show you our approach and identify where we can be of assistance to your organisation in reducing credit risk.
