With the finalization of our work on the IFRS 9 module in our Credit Risk System, it has become very apparent that the whole concept of IFRS 9, whilst is a good thing, leaves many questions unanswered. We hope to cover some of these in this article for your benefit.

This article is the third on IFRS 9, with the earlier two: IFRS 9’s impact on Credit Risk and The impact of IFRS 9 on Credit Risk – part 2 describing the impact on Credit Risk in general and raising potential clashes with the Basel accords. In these, I outlined 10 pertinent changes that IFRS 9 will bring to the world of credit risk, and the significant differences with the Basel Accords. What I would like to provide you in this article is experience on how to implement some of the IFRS 9 changes in your business, and what you should keep an eye on in terms of implementation.

The Good News

No doubt the fact that IFRS 9 will be imposed on 1.1.2018 with or without Central Banks’ approvals is a very good thing. This will force banks (and their Central Bankers) to look at Credit Risk is a much more measurable way.

It will also force banks to start using pre-fact methodologies to predict default, and hopefully reduce reliance on reactive rather than pro-active tools to help them achieve this.

The Not So Good News

In our opinion the IFRS9 guidelines were not assessed fully when applied to banking. They lack in several areas, some of which are:

1. Double Discounting: The need to discount Probability of Default (PD) when already Loss Given Default (LGD) is discounted under the Basel Accords. The process of applying a discounted PD in an Expected Loss (EL) that already uses a discounted LGD makes for a double discounting, and reduces the EL unnecessarily. Surely this defeats the objective.

2. Lack of Coverage: It only applies to on-balance sheet items. IFRS 9 does not even cover financial guarantees which are CCFed 100% like direct lines. Good news for banks, but does not cover all the risks as in the Basel Accords, leaving banks to calculate capital adequacy twice. So why the added complication?

3. Shortfall in applying Collateral Values: How to apply collateral, individually on facilities or collectively on obligors? Despite the notion that collateral security needs to be discounted to make it applicable (leaving the discounting period very judgmental in the first place), it does not account for how the collateral value is applied. For example if you have a right of offset on all facilities and collaterals, the Expected Losses across all facilities will be lower at the obligor level than those aggregated across individual facilities under certain circumstances. So banks need to calculate both Collective and Individual ELs and then decide on which to use.

4. Shortfalls in evaluating Collateral Values: The IFRS 9 calls for ELs to be judged at ORR level with adjustments made on suitably discounted collaterals. This does not account for FRRs and mitigation on LGDs. As an example a cash collateralized facility in different currency is not a 100% subtractable amount. There is a portion of the facility that is not fully mitigated and which remains clean. Unless you are familiar with splits, the management of this exposure will be difficult.

Using the Wrong Tools

Although this is a major problem to handle, it is not part of the issues raised above as the onus of predicting ELs rests with banks, not IFRS 9. If you are still using the wrong tools in your risk rating methodology (or not using anything at all – imagine some banks are still not using anything), the time frame to implement IFRS 9 is too short for change, and you will face a higher than usual provisioning on your credit exposures over time. That is not so bad as banks should be accountable for their decisions; however given that bankers do not generally admit to making mistakes will not solve this particular problem. The issues you will face adopting IFRS 9 in your credit environment relating to tools can be described as below.

Misleading Risk Rating Methodologies

For some reason, some banks opted to use risk methodologies that are no longer valid in terms of applicability or coverage (dinosaur era like). For example if you were to use Regression Analysis in “modeling credit risk” based on business, industry or other conception, it is like saying “I do not know why companies default and as such will create models to predict that. To ensure that these models are OK, I will use regression analysis to validate my work.” You have no idea how silly one sounds if this is said out loud. Besides if banks using such systems do not understand default and their causes, what are they doing in banking in the first place?

Risk rating systems, unlike risk scoring systems in consumer lending, have 177 criteria for predicting defaults as a generic base, and another 50 criteria for TMRACs. Using regression analysis for predicting defaults with so many variables will inevitably produce such low correlations (below 90%) that make the entire process useless. Haven’t you heard of the correlation between the Dow Jones index and the average temperature of Ulan Bator, the Capital of Upper Mongolia? The Gini coefficient was never a good way to validate systems in the first place, never mind under IFRS 9 conditions.

Post Fact Driven

Aside from the erroneous sense of comfort banks achieve by hiding behind mathematical modeling (that they themselves do not understand fully), the problem with risk modeling systems is that they are all post-fact driven. In other words, they base their entire predictive engines on after defaults take place. So in the case where obligors are using bank lines to cover other bank settlements (the “passing the hat syndrome”), or the excessive withdrawals that place pressure on ability to settle in future, or the wrong business model of the firm; such factors are not captured in these models, thus limiting predictive capabilities. The end result is that the ELs used are not appropriate and unexpected incidents induce too much volatility in the provisioning of the business.

To add insult to injury, some methodologies subdue the volatility by introducing the notion of Through the Cycle ratings, which dampens ELs even further and exposes the banks to unwarranted blindness.

Applying IFRS 9

I wish you luck in applying IFRS 9. Clearly not all of the issues have been raised yet, and much by way of discussions and arguments will be raised up to 1.1.2018. Unless you have already adopted our Basel compliant Processes and Procedures, and are using our Credit Risk System, then we recommend you contact us for help on ramzi.watfa@6sigmagrp.com.

© 2016 6 Sigma Group

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