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Author: Phil Flood, Director of Global Business Development for Regulatory and STP Services | December 2, 2021 | Gresham Technology
In an environment full of regulatory reporting complexity and scrutiny, regulators are “severely cracking down”: tolerance for low-quality data and errors is waning, and the era of turning a blind eye is over.
However, this has not led to the reduction in errors and improvements in data quality that the industry might have expected. It raises the question: Is fear enough to force financial institutions to resolve their data and reporting problems? Still need motivation?
High-quality, accurate data has never been more important to companies—or even harder to achieve. The data of financial institutions is stored in multiple repositories and jurisdictions, hindered by manual processes and lack of supervision, which is undoubtedly complicated-and as we see the increasing trend of regulatory differences in different jurisdictions, this situation is only Will get worse.
The methods that motivate companies around regulatory compliance can be divided into two camps: carrots and sticks.
The most commonly used “big stick” is regulatory fines. According to the ESMA sanctions report, the amount of fines imposed by the National Competent Authority (NCA) under MiFID II has more than quadrupled in 2020, reaching a total of 8.4 million euros (including 613 sanctions and measures), compared to only 180 Million euros (371 sanctions) and measures) the previous year.
However, after taking these penalties, data integrity and reliability have not been improved. ESMA’s EMIR and SFTR 2020 data quality report released in April 2021 emphasized data quality as a specific issue for the first time since the European Market Infrastructure Regulation (EMIR) came into effect seven years ago.
According to EMIR requirements, currently about 7% of daily submissions are delayed by counterparties. In addition, as many as 11 million undisclosed derivatives have not received daily valuation updates, and on any given reference date in 2020, between 32 and 3.7 million unreported derivatives are undisclosed. Approximately 47% of publicly available derivatives (about 20 million in total) are still unmatched.
Using legacy solutions that are already prone to data quality issues makes things more complicated. This is particularly evident in the company’s approach to SFTR. Many people think that this regulation is very close to EMIR, and just click copy and paste.
This shows that although the big stick can indeed play a role, it alone is not enough to solve the problem of low data quality in the report.
Rather than penalize companies for poor data quality and inaccurate financial regulatory reporting, it is better to help them realize the benefits of strong data integrity—such as reduced costs, improved operational efficiency, and easier innovation paths—may be more effective in encouraging C-suites And the reporting team prioritizes data quality.
However, this is not to say that carrots and sticks must be mutually exclusive. Using both at the same time may be the most effective way to raise standards.
Most importantly, regulators should convey that taking action is not out of fear, but out of ambition, and is the key to data success.
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Post time: Dec-15-2021