In a little more than a year, Canadian banks and lending companies will be facing a massive data analytics tasks brought on by an upcoming financial industry reporting standard.

IFRS 9 is an International Financial Reporting Standard promulgated by the International Accounting Standards Board (IASB) which primarily alters current industry requirements compelling financial firms to report projected credit losses should a crisis occur. This new model of accounting for financial instruments is meant to address criticism that impairment models used during the financial crises of 2008 allowed companies to delay recognition of assets impairments. IFRS 9 requires recognition of full lifetime losses more quickly.

Later in this article, you will find eight questions that can help your organization identify the right technology solution to speed up IFRS 9 compliance.

While of much of the world’s banks are expected to comply with IFRS 9 by January 1, 2018, Canadian firms will have to implement the standards by October 31, 2017, because the country’s financial calendar begins November 1.

“This leaves Canadian banks a little over a year to deploy solutions and test their models,” according to Darryl Ivan, national lead for risk at analytics software company SAS Canada. “This will really be a big challenge for many organizations because they will have to apply very sophisticated analytics to project losses based on massive amounts of data coming from various data points and available in different forms.”

For example, while even small financial firms may have just thousands of customers compared to the big banks’ tens of thousands of clients, each client is likely to have several forms of credit associated with a company. Firms will have to create models forecasting projected losses for each account.

He said, ideally companies such have in excess of six months to test the accuracy and reliability of their models.

IFRS 9 would require companies to comb through massive amounts of data to address the new calculations required by the new standard. Ivan foresees the need for support from analytics and modeling technology to ensure that reports are up to snuff for scrutiny by regulators, auditors, and investors.

The new requirement will take into account forward-looking scenarios that need to be developed by various departments working together.

“Banks will need to come up with risks assessments. But this time it will require finance, risk, and even the IT department together to bring this about,” said Ivan.

That’s because the release of forward-looking reports will entail extensive disclosure requirements and appropriate disclosure frameworks need to be established since the data released at a much earlier time could have a negative impact on the company. While the previous regime required that projections cover a 12-month period, IFRS 9 coverage will be for the “lifetime of the loan which could be anywhere from six months to 10 years,” according to Ivan.

Ivan suggests that decision makers ask the following questions:

  1. Will the solution be able to dynamically test the impact of changes to staging allocation rules as well as other important inputs related to the accounting standard?
  2. Will the solution be robust enough to calculate expected credit loss down to the loan level with confidence?
  3. Is the IFRS 9 platform, or its components, reusable in other critical areas such as stress testing, Basel model deployment or economic capital?
  4. Will the solution have adequate controls and the ability to provide transparency/audit trails that hold up against rigorous examination from regulators and auditors, while minimizing manual intervention in the workflow and in data aggregation and output?
  5. How can IT accelerate speed to the execution of IFRS 9 to allow the commencement of early testing/parallel runs, preferably with existing infrastructure?
  6. How can the organization manage all of the data challenges, including sourcing, quality, aggregation and traceability/lineage of data?
  7. What are the ongoing maintenance costs and operational risks beyond the initial deployment of an IFRS 9 solution? Is it scalable; can it easily move from relatively simple models to more complex models, and from segment level analysis to loan level analysis?
  8. How will the product be supported, and what is the vendor roadmap for it? Do you have a partner, or a relationship with an experienced vendor, who can provide reasonably priced, deep support beyond the initial deployment of the IFRS 9 solution?

For more information on how to achieve IFRS 9 compliance, check out this white paper from SAS