CLIENTS
Clients
Below are some of the leading banks and credit unions that we have assisted over the years. For reasons of confidentiality we cannot go into detail about work completed. However we are able to present broad outcomes, set out in the following Case Studies.








Banks, Finance Houses and Credit Unions
Reduced loan losses
One bank, operating on optimistic estimations of early Probability of Default (PDs) and of Loss Given Default, (LGDs) was neglecting the collection of early arrears. By measuring the true credit risk, via CRA, the bank was incentivised to undertake earlier intervention and, rapidly, to reduce its write off experience. Additionally, early identification of ‘Hot Spots’ improved Collections Management and reduced bad debts by a measured 20% against initial forecasts
Banks, Finance Houses and Credit Unions
Portfolio Valuations
The accurate measurement of portfolio credit risk and projected impairments, on both well performing and under-performing debt, makes it possible to value an entire loan portfolios for sale or purchase. Valuations of such Sales or Purchase can be undertaken on a ‘ going concern’ basis or on a ‘gone concern’ basis, the difference being related to the composition of the portfolio, final maturity and the loss provisions to be recognised on the relevant date.
Credit Expo completed two recent evaluations for a bank purchaser, finding alternatively, one valuation above the bank’s own estimations, with the other being significantly below the bank’s estimation. Following discussion of Credit Expo’s valuations, the company’s valuations were adopted for bidding, some months ahead of rival bids. The benefits of the CRA analysis were high in terms of portfolio pricing and the timing and confidence level of the bids.
Banks, Finance Houses and Credit Unions
Credit Risk Analytics and Credit Union Regulation 49
CRA’s empirical measurement of differentiated and rolling credit risk was responsible for identifying the former seriously misleading fixed-rate risk matrix, Resolution 49, introduced by Credit Unions in the boom year 2002 but not revised thereafter to recognise the 2007 recession. When the CRA calculations were adopted, the true position of credit union loan risk was measured, resulting in higher provisioning requirements, higher loan pricing and more focused collections. The CRA software is currently in use in over 40 Irish CreditUnions
Banks, Finance Houses and Credit Unions
Revising Loss Given Default calculations (LGD) and new loan pricing
One client was operating based on an assumed, universal LGD/Write off rate of 66%. Using CRA analytics it proved possible to complete current net present values (npv) calculation of the net recoveries and to measure the bank’s LGDs across asset types and loan maturities, with LGDs now varying between from 40% and 80%. This prioritized specific asset types and accounts for collections. Importantly, the review also differentiated strategic loan pricing.
Banks, Finance Houses and Credit Unions
Securing additional relief from Corporation Tax
A CRA review of one client’s provisioning calculations identified that earlier reported calculations had understated the Bank’s credit risk and the associated provision requirement. By recasting the calculations empirically, it was possible to make a retrospective adjustment in the Bank’s financial statements and, with Revenue approval, to secure significant additional corporation tax relief.
Banks, Finance Houses and Credit Unions
Rigid and inaccurate calculations of loss probability
In another case a bank was applying PD figures “imported” from another Loan Portfolio to measure its Micro Finance exposures. However, the two portfolios had very different customer bases and diverse loan securities with very different, measured LGDs. CRA analysis showed that the common loss probabilities/PDs then being applied greatly understated the risk for Micro-Finance. Once the true Credit Risk was identified, micro finance lending was suspended and relevant arrears were prioritized for collections.
The benefit of this early action was later measured by the Bank at some €4 million.
Banks, Finance Houses and Credit Unions
Elimination of Cross Subsidization of loan losses, with enhanced profitability
Cross Subsidization within banks is, very frequently the biggest source of loss to lenders and is typically invisible.
For one bank, it was found that while the overall calculation of the Loss Forecast was broadly accurate, the distribution of risk across different regions and branches was skewed, resulting in seriously misleading perceptions of risk, of individual performances and of local profitability.
By retuning formerly undifferentiated Loss and Profitability calculations to measure local experiences and, now differentiated, product losses to eliminate local losses, the former overall modest profitability of one bank was increased by a startling 400%.
