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New accounting standard IFRS 9: a game changer for economists?

New accounting standard IFRS 9

The new accounting standard IFRS 9 is effective from 1 January 2018 and delivers a host of reporting changes, including how organisations should account for financial instruments like cash and cash equivalents, trade receivables, loans and other financial assets.


Maura Feddersen


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The way in which financial institutions account for credit losses, for example, has implications for provisioning and hence directly impacts their profitability and reported bottom line. It is not surprising, therefore, that many organisations are paying close attention to how the new reporting standard impacts their growth outlook.

The role of economists is also shifting. Previously, in-house economists may have focused on devising economic outlook information for strategy formulation, trading and investment decisions or internal capital planning purposes, for example. With the advent of IFRS 9, economists’ views are not only a desired, but required input into credit modelling and gain further relevance as a newly audited component under IFRS 9.

What exactly is the relevance of economics in IFRS 9?

According to the standard, to arrive at an estimate of expected credit loss (ECL), an organisation should use all reasonable and supportable information available at the reporting date about past events, current conditions and forecasts of future economic conditions. Furthermore, the ECL estimate should be probability-weighted and unbiased, based on the inclusion of probability-weighted scenario views of possible future economic conditions. As a result, the measurement of credit losses can be particularly sensitive to changes in macroeconomic forecasts. As the level of judgement required in making the ECL calculation rises, it becomes ever more important that the inputs, assumptions and techniques used in estimating the ECL are reasonable and supportable.

What economists may consider in deriving forecast views

Due to the combination of econometric modelling and expert judgment usually required to derive economic forecasts, economists generally spend a considerable amount of time deliberating:

  • Overarching model paradigms, for example, models that reflect a demand-side or supply-side viewpoint
  • Econometric modelling techniques to consider and apply, guided by data characteristics 
  • Pertinent economic variables and data availability
  • Model selection criteria like goodness of fit, theoretical support, statistical soundness 
  • Validation approaches, including back-testing, where applicable 
  • Approaches to scenario generation and choice of probability weightings

These decisions have a significant influence on the degree of confidence that can be placed on the forward-looking information devised by economists and may still require frequent updating, especially in more volatile emerging markets like South Africa.

What economists consider in linking economic and credit information

Once these forward-looking views are ready for incorporation into the ECL estimate, they must still be suitably linked to relevant credit parameters, where economists would place emphasis on the following modelling decisions:

  • Methods to determine variable selection: Often single factor analyses, correlation tests and knowledge of existing theoretical and empirical research can help in choosing suitable macroeconomic variables to reflect credit risks at the portfolio level.
  • Choice of modelling methodology: For time series data, econometricians often consider simple regressions, autoregressive distributed lag (ARDL) models, vector autoregressive (VAR) models, or combinations of cointegrating long-run equations and error correction models (ECM) to model the links of macroeconomic factors and credit parameters.
  • Validation and sensitivity testing: This helps to establish the stability and reasonability of forward-looking adjustments to the ECL estimate. 

Since the choice of variables, modelling methodology and model validation can significantly influence the size of the forward-looking adjustment to the ECL estimate, strong governance and accountability are essential in supporting the implementation of the forward-looking component under IFRS 9.  

The way forward

Economists play a key role in helping organisations move from an incurred- to expected view of credit losses. Furthermore, their role extends beyond devising appropriate forward-looking views, as they are also key in facilitating the implementation of econometrically robust models that link economic information and credit parameters.

All entities adopting IFRS 9 must consider how the changing reporting requirements shift the scope of work for the economists who advise them. Because economists now play a role in helping organisations estimate ECLs under IFRS 9, they carry an additional responsibility to uphold the highest possible standards of economic modelling that combine insights from econometrics as well as a deep understanding of the mechanics of economic activity, including their implications for credit risk. In an environment of volatile and complex economic conditions, economists face the tall order of formulating clearly defined views of possible future economic outcomes, as well as to link these reliably to portfolio risks. While this may prove difficult, it can help organisations better manage the effects of changing economic conditions, especially the implications of worsening economic prospects.

Visit our IFRS – Financial instruments page for a range of tools and resources in relation to IFRS 9.

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KPMG International Cooperative (“KPMG International”) is a Swiss entity.  Member firms of the KPMG network of independent firms are affiliated with KPMG International. KPMG International provides no client services. No member firm has any authority to obligate or bind KPMG International or any other member firm vis-à-vis third parties, nor does KPMG International have any such authority to obligate or bind any member firm.

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