November 17, 2015 – By Fraser Hall, Head of Service Delivery, EMEA, AxiomSL
Financial firms are starting to sit up and pay close attention to International Financial Reporting Standard 9 (IFRS 9). The new standard will fundamentally change accounting practices and require the use of a host of additional data sources. With capital provisioning also set to increase sharply as part of IFRS 9, firms are eager to optimize their implementations of the standard and avoid tying up more capital than necessary.
IFRS 9 is part of the International Accounting Standards Board’s (IASB) response to the issues that were exposed by the financial crisis. In the years before 2007-2008, the accounting practices of the day painted a broadly positive picture of the financial markets and failed to highlight the risks that laid ahead. This was because the relevant accounting standards had been designed to analyze the past performance of firms’ financial instruments rather than their likely future performance.
To avoid a repeat of these mistakes and to provide a more accurate view of the health of the markets, the IASB will now mandate the use of a new, forward-looking approach to accounting. As part of IFRS 9, firms will be required 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 then need to offset these expected losses with capital provisions.
The switch from a backward-looking approach to accounting to a forward-looking approach to accounting is an enormous change. It means that firms will need to either adapt or replace the credit loss models they have used for some time. It also presents a number of significant data challenges.
In order to model future market events, firms will need large volumes of data that has not previously been required. This includes external data, such as macroeconomic information. The use of such external data is a big change for firms, which have historically 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 several years.
Integrating all of this internal and external data will be a major challenge for firms that use a traditional regulatory calculation and reporting tool with a fixed data model. Firms that have such a tool will need to program an extract, transform, load (ETL) layer that will convert the source data into the format mandated by their software vendor. They will, for example, need to set up a network of ETL to extract all of the data they need from their legacy systems. This will be a complicated, time-consuming exercise. ETL will also add complexity for business users who want to drill down into their data to understand how it has been transformed and used in calculations.
Instead of going down this route, firms should use a data-agnostic regulatory calculation and reporting platform, which does not require them to undertake any data conversion work. Once the data has been loaded, the platform should validate and normalize it to ensure it all conforms to the same standards of data quality. A platform that offers this type of functionality will significantly reduce complexity and time to market because firms will not need to spend time setting up an ETL layer. It will also reduce total cost of ownership by eliminating the need to maintain both the platform itself and an ETL layer.
The internal data needed for IFRS 9 includes financial data and risk data (which has not in the past been used in accounting). In this regard, IFRS 9 joins a growing list of requirements (such as BCBS 239 and AnaCredit) that call for a much closer relationship between risk and finance functions.
Risk and finance have historically operated in isolation from one another, employing different governance procedures, operating models and data formats. The simplest way for firms to reconcile these differences and comply with IFRS 9 is by implementing a single calculation and reporting 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 adheres to the same standards.
The results of getting the above implementation work wrong could be costly. IFRS 9 includes many scenarios under which financial firms will be obliged to calculate the ECL for the lifetime of an instrument. As a result, firms’ provisioning requirements could be significant. To avoid over-calculating their provisioning requirements or erroneously triggering a requirement to calculate the lifetime ECL, it is important that firms have easy access to the right data and that they use it to run their models.
IFRS 9 will come into force in 2018, although some countries have chosen to require use of the standard before this date. At the moment, most firms are still in the process of analyzing the requirements. They are investigating the gaps in their data and the suitability of their incumbent credit loss models and calculation and reporting platforms. To ensure the success of their IFRS 9 programs, it is important that firms also start thinking now about how they will integrate all of the required data.
This article was originally published by Bobsguide.