24 Nov IFRS 9: Getting to grips with the data challenge
November 24, 2015 – By Fraser Hall, Head of Service Delivery, EMEA, AxiomSL
Financial firms in many countries are preparing to make fundamental changes to the way they do their accounting. Having traditionally focused on the past performance of their financial instruments, the introduction of International Financial Reporting Standard 9 (IFRS 9) means they will also need to take into account the impact of possible future events when calculating their capital provisions. This presents a range of challenges, not least the need to source and integrate large volumes of data that have not previously been required for accounting.
Like so many requirements being rolled out today, IFRS 9 is a response to the events of the financial crisis. The accounting standards in use in the years before 2007-2008 failed to highlight the losses that firms would face because they were based on analysis of past events. This led firms to catastrophically underestimate the capital provisions they required, and the rest (including the bailouts and bankruptcies) is history.
To address these issues, IFRS 9 will require firms to model future events in the macroeconomic environment and calculate expected credit losses (ECL) for their financial instruments over either a 12-month or lifetime period. They will need to offset these expected losses with capital provisions. A long time in the making, IFRS 9 is set to come into force in 2018, with some countries opting for an earlier adoption.
The forward-looking approach mandated by IFRS 9 means firms will need to either revise or completely replace the credit loss models they have relied on for some time. Many firms, particularly tier-two and tier-three organizations, currently use spreadsheets to manage their accounting. This will no longer be feasible under IFRS 9 due to the sophistication of the models that are required and the volumes of data involved. Instead, firms will need to use a regulatory calculation platform to automate the entire compliance process. If firms want to use models they have built themselves, they must choose a flexible regulatory platform that can easily integrate these models.
In order to run the models, firms will need large amounts of data that have not historically been required for accounting. This includes external data, such as macroeconomic information, ranging from gross domestic product (GDP) and house prices to interest rates. The use of such external data is a big change for firms, which have until now relied on internal financial data to run their accounting processes. Firms will also need far more internal data than before. For example, to calculate the ECL, they will need historical data that goes back many years.
Integrating all of this internal and external data presents particular challenges for firms that use a traditional, black-box regulatory calculation tool with a fixed data model. Firms with a tool like this will need to set up an extract, transform, load (ETL) layer to convert their source data into the required format. This is a complicated, time-consuming process. It increases the total cost of ownership (TCO) because a firm will need to maintain both the calculation tool itself and the ETL layer. It also makes it virtually impossible for users to drill down on their data to understand the numbers that are being produced by their calculation tool. This is particularly concerning in light of the Basel Committee on Banking Supervision’s 239 (BCBS 239) Principles for Effective Risk Data Aggregation and Risk Reporting, which come into force in 2016.
To avoid the above issues, firms should use a data-agnostic regulatory calculation platform to address the requirements of IFRS 9. Firms that choose this option will not need to undertake any data conversion work – they will be able to plug their data directly into the platform. This will significantly reduce complexity and time to market. It will also cut TCO by eliminating the need to maintain an ETL layer. And it will ensure users have a transparent view of the transformations and calculations that are being performed by their platform.
The internal data required for IFRS 9 includes risk and financial data. In this way, IFRS 9 joins a growing list of requirements (such as BCBS 239) that call for a much closer relationship between risk and finance. These two functions have historically operated in isolation from one another, employing different governance procedures, operating models and data formats. While finance is accustomed to external reporting and being held to account by regulators, risk is usually an internal monitoring process, which must adhere to internal, rather than industry-wide, standards.
The simplest way for firms to reconcile these differences and comply with IFRS 9 is by implementing a single calculation platform on top of the systems they currently use to manage risk data and financial data. The platform should integrate and normalize data from the different systems and ensure it conforms to the same standards. The platform should also include user control functionality that will facilitate more rigorous data governance procedures within risk.
At the moment, most firms are focusing on gaining a better understanding of how they will be impacted by IFRS 9. They are investigating the gaps in the data they currently use and the suitability of their incumbent credit loss models and regulatory compliance technology. To address the fundamental changes that are being made to accounting, it is important they also think carefully about how they will integrate and manage all of the required data.
This article was originally published by Tabb Forum.
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