As a consequence of the experiences made during the great financial crisis 2008/09 the IASB changed financial instruments accounting away from the incurred loan losses approach to a forward looking expected loan losses approach. Concretely, the new IFRS 9 Financial Instruments applies a 3-stage model which requires to classify loans into performing, under-performing or non-performing based on observations of credit risk movements. Each of these three stages triggers different levels of reserves (balance sheet allowances, provisions). The following graph highlights this (we have already shed some light on this topic in one of our former blog posts where we have explained the general functioning of the new standard (HERE); please refer to this post for an understanding of the IFRS 9 system in general).
* In practice the liftetime losses are proxied by a 3 year forward looking analytical horizon.
This makes sense in principal as it is the future, i.e. the expected losses that matter for decision making for banks. But as always when we talk about the future the input to our decision making tools becomes more and more blurred. In terms of financial instrument accounting this means: While incurred losses of loans were easy to determine based on actual data points, forward looking expectations always need subjective inputs. It is the old dilemma of accounting in general, and IFRS and US-GAAP accounting in particular: If you want to have more relevance of reporting you have to give away some degrees of reliability of it. Or putting it differently, while the strengths of the good old local GAAPs (e.g. German GAAP) was that numbers were highly reliable their weakness was that it was not always a good set of numbers to base decisions on. And for IFRS and US-GAAP it is the other way round: Their strengths is the focus on relevant information but at the cost of less reliable or more subjective information.
The academic world still fights today about how this tension field can be solved, with some saying that less reliable information cannot be more relevant (exactly because of the lack of reliability) and others stating that decision-useful information must be highly forward looking because that is the only thing that matters in business valuations (only future cash flows matter). The truth is, however, somewhere between the extremes. Of course, investors want to be able to build forward looking expectations based on the set of accounting information, but they also do not want to give too much forward looking power and hence discretion into the hands of companies’ management because this would open the door for manipulation. In short, there is an optimum – but this optimum is hard to find in reality!
A seemingly logical way of dealing with this problem is to include more ‘hard’ benchmarks or guidelines or indicators into the expectations-building process. This can take out some subjectivity by contemporaneously allowing for a forward looking nature of information. And this is a clear trend to be observed in accounting practice over the last years.
While we applaud this trend in general we also have to emphasize that there are certain situations where this way of dealing with forward looking information brings a lot of problems. It might be that the indicators or benchmarks are bad in general (often the case in goodwill impairment tests) or that the indicators or benchmarks are bad in certain extreme situations (very often the case in every extreme situation). And it is this latter case that makes our accounting often quite vulnerable because investors are quite ok with accounting information in normal situations – the need for high quality information is relatively low if all develops in normal paths – but they desperately need high-quality information in tricky times. This accounting problem is like an airbag in a car that works well all the time except for when you have an accident.
Moreover, if the indicators do not work properly in these extreme times then investors run into a very dangerous ‘Unknown Unknowns’ situation, i.e. they even do not know that something is wrong with the information (in contrast to a pure ‘Known Unknowns’ situation where investors know that the information has some weaknesses).
