Technological advances and increased automation mean that there’s much more financial data available than ever before. So how can banks and finance firms find and present the right data, to the right regulator, at the right time?
The Bank of England is running a ten-year project to transform the way it collects data from financial services firms. The Bank collects data to “identify risks, design good policy and take action in a timely and targeted fashion”.
Regulated firms must provide the Bank with the information it requires in the way it requires. That’s why the industry will be investing a lot of time and energy in getting its regtech up to speed over the next few years.
Fraser Hall is the Global Head of Product Management – Financial Regulatory Solutions, at ADENZA, a provider of compliance platforms.
Speaking at the RWG RegTech conference in November 2021, he said there are “a lot of challenges around mobilising teams of people to satisfy requirements” like stress tests. He added that people are very focused on current reporting asks, rather than on what future looks like.
However, Hall says when firms boil down the basic information they need to give regulators, it’s often the same information across multiple data regimes in the firm.
Common data models in financial regulation
Firms have developed their own internal data practices over time. Now, the Bank says, some face enormous complexity.
“The data for reports can come from dozens of legal entities, hundreds of business lines, and thousands of systems. Even seemingly simple data points like ‘total lending amount’ can have over ten definitions at some firms, and each of these may have subtle definitional differences from similar terms used by other firms in their sector”.
But regulators also add to the Tower of Babel. As the Bank admits, different regulators ask for similar data “but with slightly different definitions” for lots of different reports, broken down in different ways.
Adam Turnbull, Global Co-Head, Regulatory Engineering, Goldman Sachs – also speaking at the RWG RegTech conference – wants the industry to get to the point of “common data models”.
One benefit, he says, would be regulatory instructions that map to those models, so industry participants know what data the regulator actually wants to see.
“We need to get to a place where different industry participants have a much more consistent output,” says Turnbull.
Goldman Sachs showed its commitment to that on 30 November, by launching their Financial Cloud for Data with Amazon Web Services. This offers fintech plumbing and data for hedge funds and asset managers.
Consistency is also something that the Bank of England has on its wish-list. It wants “common data standards that identify and describe data in a consistent way throughout the financial sector.”
Turnbull at Goldman Sachs suggests making certain critical data feeds more like a library. People will be able to pick the data field they want, but not tailor it.
“I’d leave it to the lawyers to say whether that should be mandated in law, but getting to that library of fields is very important,” says Turnbull. “The question becomes to what extent can the industry coalesce around that…and to what extent the regulator…proscribes a library.”
Turnbull suggests there’s a need for an organisation in the middle to help the industry join the dots and that the regulators might help with the creation of that market infrastructure.
How to get the basic data right
Hall says that “before you even try to tackle the reporting [you] must make sure that the baseline version of data is accurate and correct. All that reconciliation and attestation is [a cost]…[and] an opportunity to do things right first time.”
Turnbull says that firms need to be able to find “the ultimate source of truth” when it comes to regulatory reporting. “You’ve got to make sure your basic data is right.”
He advises starting at the granular level and making sure the data is tied to “some real activity” that the organisation does. That way, the firm will know whether it’s a true picture of the outcome.
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