IFRS 9 and CECL: The Challenges of New Financial Standards


By Tom Kimner, Head of Global Product Marketing and Operations, Risk Management

The Board of Accounting Standards has published its Accounting Standard Update on Financial Instruments – Credit Loss (Topic 326). This was the second phase of a global change in accounting standards that began when the International Accounting Standards Board published their new standard, known as IFRS 9 financial instruments (a replacement for IAS 39) to the rest of the world in 2014.

The updated guidance on measuring credit losses (using a current estimated credit loss estimate) represents a fairly significant change from the previously accrued loss model that was in place for some time. Eg. Recognized loss model recognized losses only when they have reached one likely loss threshold. Many analysts have suggested that this model had a negative impact during the financial crisis because potential future losses were recognized and predicted far too late.

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While the American standard (known as current expected credit losses, or CECL) differs in a few significant ways from the international IFRS 9 standard, both audited accounting standards share an important function: the calculation of the expected loss is now based on the life of the loan. This change increases the credit impairment over the affected assets (where some estimates are as high as 35 percent), resulting in higher provisioning costs and a negative impact on capital.

Working with uncertainty

IFRS 9 and CECL are primarily principles-based. As such, the implementation guidelines are likely to change as consensus and clearer guidance is established. Given the evolutionary nature of these standards, institutions may need to spend more time iterating model development cycles prior to the transition to IFRS 9 and CECL reservation.

As IFRS 9 and CECL development will be in conjunction with ongoing stress testing activities, stress tests are likely to include preliminary allowance models that lack a full set of reviews. In a decentralized environment, additional model risks may arise when methods and models used in stress test production are out of sync with IFRS 9 or CECL models. Institutions must ensure that the quota models used for stress testing keep pace with the development of accounting standards and that the assumptions remain consistent between the testing activities.

In addition, models with lifetime loss may rely on data elements not previously required for stress testing. As a recent report revealed, only 17 percent of the surveyed banks had a comprehensive data record for stress testing. This suggests that many banks are not prepared for the ever-increasing integration of financial and risk data required for IFRS 9 or CECL and stress testing. This can create a risk of data integrity as analysts get the necessary data through ad hoc channels to meet their stress test deadlines. Institutions must ensure that the data used for stress test connectivity binds data used for IFRS 9 and CECL model development.

Meet the challenges

To meet the changing regulatory and financial standards requirements, organizations need to look at resolving these issues collectively and comprehensively in several areas. Otherwise, overall compliance costs can be burdensome, especially if different parts of the organization find themselves creating redundant or overlapping processes.

Consolidating financial and risk data provides a number of benefits across the institution. A common data repository for stress testing and quotas calculation greatly reduces audit and reconciliation issues and model risk. It also reduces the cost of managing multiple platforms.

An organization’s loss modeling and stress testing processes need to be robust, yet flexible. They must be able to accommodate dynamic changes in quota modeling while maintaining sufficient controls to withstand the regulatory scrutiny of the capital adequacy assessment under stress. Institutions find that consolidating their stress tests and quota estimation platforms provides the best basis for achieving this goal.

A centralized model library provides a structure to maintain control over the stress testing process such as development allowance model and test development. With proper model versioning, management can maintain oversight and make informed decisions about integrating new models into the stress testing process.

In addition, a flexible and modular model library facilitates sensitivity testing. This is becoming an increasingly important tool for understanding the larger effects of changing models and assumptions on IFRS 9 and CECL development cycles.

By exchanging model components iteratively, comparisons can be made between model versions. Institutions can also quantify the overall effect of model refinements on their balance sheets while under stress. Sensitivity testing is also an effective tool for analyzing trend attribution – a key component of stress testing. Previous stress tests can be run again with updated model components or vice versa to quantify the effects of ongoing model development on stress test results.

The changes in regulatory stress tests and accounting standards have necessitated the need for historically independent risk and financial divisions to further integrate and collaborate. The importance of tight collaboration and data sharing will only intensify as the new accounting standards begin to take effect. Departmental lines are becoming increasingly blurred in terms of regulatory and accounting compliance, and the mutual dependence on the various functions will only be intensified.

The transition to IFRS 9 and CECL presents many financial and operational challenges – reinforced by the many implementation details that continue to be subject to various interpretations. Institutions must tackle these challenges holistically with the flexibility to adapt over time. Regulators and investors need to know that banks effectively assess and manage the risks in their portfolio. Proactively implementing a well-regulated approach to managing data and models gives confidence that there are processes ready to deal with these critical issues now and in the future.



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