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Using analytics to overcome IFRS 9 challenges

With IFRS 9, statutory auditors will require more scrutiny, justification and documentation of impairment risk models, says Charles Nyamuzinga, Risk Consultant at SAS.


Johannesburg, 03 Mar 2017
Charles Nyamuzinga, Risk Consultant, SAS.
Charles Nyamuzinga, Risk Consultant, SAS.

Following the 2008 financial crisis, banking regulators quickly identified the delayed recognition of credit losses on loans and other financial instruments as a weakness in existing accounting standards. It was for this reason that the International Financial Reporting Standards (IFRS) 9 standard was developed.

Due to come into effect in January 2018, IFRS 9's goal is to serve as a forward-looking 'expected loss' impairment standard, one which requires banks to provide more timely recognition of expected credit losses (ECL). The ECL figures will be based on future expectations, as opposed to the current 'incurred loss' model.

What this means, says Charles Nyamuzinga, Risk Consultant at SAS, is that the new standard requires banks to account for ECL on an individual financial instrument level, from the moment instruments are first recognised, and they must recognise full lifetime ECL on a timelier basis.

"Effectively, IFRS 9 demands that accounting statements provide a more accurate view of a bank's financial situation, by bringing the impairment methodology used within finance closer to the risk processes employed in expected loss calculations under the Basel regime," he explains.

Nyamuzinga adds that the new standard creates a number of challenges for the financial services sector, starting with an increase in scrutiny by auditors. This is because with IFRS 9, statutory auditors will require more scrutiny, justification and documentation of impairment risk models.

In addition, IFRS 9 is creating concerns about collecting the necessary data. Moving from an incurred loss model to an expected loss model means a wider scope of data must be considered. Furthermore, because the risk models involved are more complex, data must, in turn, be more detailed.

"Another challenge is the high level of uncertainty regarding capital impacts. This is due to the fact that IFRS 9 guidelines are principles, and because of this, there is uncertainty and debate around the impairment rules and capital impacts."

A fourth challenge Nyamuzinga identifies is the complex credit risk modelling and calculation demands. To accurately forecast credit losses, he suggests, banks will need new or updated systems and complex models that use more data.

"To overcome these and other challenges related to the implementation of IFRS 9 standards, banks will need significant support from technology. This includes advanced tools to collect data and ensure proper governance, by maintaining full control over what data is used for calculations and models."

"With advanced analytics solutions, these enterprises will be able to obtain extremely fast run times and adaptive aggregation of results. Achieving this will in itself enable quick analysis and decision making," he continues.

Nyamuzinga points out that IFRS 9 is a very topical discussion at present, with the standards due to come into force in less than a year. He says that he expects large banks to possibly find themselves spending billions in order to comply.

He believes that due to the large volume and granularity of data, combined with the complexity of the calculations applied to it to comply with IFRS 9, there is going to be substantial pressure placed on the underlying technology that banks are currently using. In other words, newer and better technology systems will be required.

"Remember that in terms of IFRS 9 requirements, we are talking about vast amounts of big data, so what will be needed will be high performance capabilities, coupled with advanced analytics. In addition to this, banks are going to require technology solutions that provide for an environment that supports efficient documentation, strong governance, change controls, model management, traceability, workflow and audit trails."

"SAS is able to provide technology solutions designed to not only make data collection simpler, but also to ensure this data is cleansed and is of high quality. In other words, we provide tools that are able to deliver the data governance, the analytical governance and the reporting governance required to meet the standards demanded of IFRS 9," concludes Nyamuzinga.

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