RiskTech Forum

SunGard: Why IFRS 9 is A New Chance to Align

Posted: 1 February 2016  |  Author: Marco Seeliger


Under International Financial Reporting Standard 9 Financial Instruments (IFRS 9), a more forward-looking approach to credit loss is set to bring the accounting and risk management functions of banks closer together than ever before. But what does this new regulation mean for your risk management framework as a whole?

Perhaps the most important goal of IFRS 9 is to incorporate assumptions about the future, as well as past events and current conditions, into credit risk management. Using techniques that were formerly restricted to asset liability management (ALM), this will see accounting move from an incurred loss model to an expected loss model.

To manage impairment, IFRS 9 stipulates that banks include a loss allowance in their financial statements that amounts to the expected credit loss (ECL) on their financial assets. This loss allowance must be included from the origination of the asset until it is derecognized. At the heart of the new impairment calculation will stand a model very similar to that used in stress testing, with the same point-in-time probability of default (PDPIT) and loss given default (LGDPIT) parameters. The intention is to calculate expected loss over the next 12 months or the complete lifetime of the loan, and to discount these contributions with a discount factor derived from the loan’s effective yield.

Because PDPIT and LGDPIT reflect current macroeconomic conditions, the calculation must also be adjusted to include future expectations. If the economy is booming and everyone can pay back their debts then PD will be much lower, while in a recession it increases. By changing the risk parameters to boom, bust or somewhere in between, you can estimate and allow for impending impairment.

The challenge, of course, is to figure out what your future expectations are, and the level of adjustment required. That depends on the stage you’re currently at in the macroeconomic cycle and relies on variables such as GDP growth, unemployment rates and interest rates.

Under IFRS 9, banks must also calculate exposure at default (EAD) which estimates the amount of outstanding debts at a particular point in time. Typically, EAD is not solely determined by contractual cash flows but also by implicit options such as the right to prepay a loan. As prepayments reduce the principal of a loan sooner than expected, the bank will earn less interest income over the lifetime of the loan. This makes it critical to factor prepayments into EAD calculations – and, from the reverse perspective of credit adjusted ALM, to included expected credit losses in forecasts of net interest income. Here, again, you must also take macroeconomic conditions into consideration, as customers will naturally be more willing and able to prepay loans in a boom phase than a recession.

There is, however, a big difference between a prepayment and a credit default. The former does not reduce the expected cash inflow from a loan but only alters it from a timing perspective. The latter, meanwhile, can either stop cash flow altogether, reduce it significantly or postpone the expected inflow. But if the loan is collateralized, as with a mortgage on a house, then the value of the collateral could actually increase above the amount of the original loan – or, in a recession, fall below it.

So, for ALM purposes, you must consider:

In this new world of risk management, where ALM meets credit risk, consistency is critical for banks. ECL write-off and recovery amounts should not only be incorporated into income simulation but also the calculation of other important risk metrics, from present value to gap profiles, and regulatory requirements for liquidity and capital management. This requires banks to think very differently from before: where risk was previously managed in silos, the same measures must now be applied enterprise wide.

In the coming age of IFRS 9, banks will see more and more interdependencies emerge between their different risk management functions, ALM included, and a growing focus on macroeconomic forecasts. ALM teams in particular could see their tried and tested techniques used in a wider context across their organization. The gap is certainly being bridged between risk management, finance and treasury. But the models, methodologies and macroeconomic assumptions that are applied to risk calculations must also remain constantly aligned, for a complete and accurate picture of risk present and future.