With regulators pushing for enhanced risk aggregation and reporting, it’s incumbent upon financial institutions to be able to aggregate risk across geographical, product and departmental boundaries, according to Alex Tsigutkin, CEO of Axiom SL, a provider of regulatory reporting and risk-management systems.
“The key aspect is to provide information that can be actionable so that people can control the process properly, as well as control capital adequacy,” Tsigutkin told Markets Media. “It's about enhancing the infrastructure for risk reporting to enable the board and senior management to identify, monitor and manage risk.”
In January 2015, the Basel Committee on Banking Supervision published the second progress report on banks’ adoption of the Committee’s principles for effective risk data aggregation and risk reporting, known as BCBS 239. Of the 31 participating banks, 14 reported that they would be unable to fully comply with the Principles by the 2016 deadline.
The average ratings of all 11 principles ranged from 2.43 to 3.33. The three principles with the lowest reported compliance were Principle 2 (data architecture/IT infrastructure), Principle 6 (adaptability) and Principle 3 (accuracy/integrity) as nearly half of banks reported material non-compliance on these principles.
The three principles with the highest reported compliance were Principle 8 (comprehensiveness), Principle 9 (clarity/usefulness), and Principle 11 (report distribution).
Tsigutkin participated on a panel discussion held Wednesday on best practices for enterprise data and risk management, hosted by The Professional Risk Manager International Association and The Toronto Financial Services Alliance in Toronto.
The panel focused on dealing with challenges in data governance, enterprise risk management and addressing regulatory requirements including BCBS 239 and related issues, including establishing greater transparency and strategic controls of the data management process within financial institutions.
One of the topics on the agenda was meeting demand for business intelligence technology to support risk management, data visualization and automation.
“Business intelligence technology is a broad term for software-related solutions which encompass the ability to analyze information at the higher levels of the enterprise, and be able to drill down to the lowest level of granularity available,” said Tsigutkin. “The reason it's called business intelligence is that there is quite a challenge for senior management to make decisions on capital allocation, on products and services the financial industry should provide in view of growing concerns for cost and profitability.”
