Automating the Regtech Workflow
The regulatory industry has undergone some momentous shifts in the past year, with Brexit and the Trump administration. As regulatory uncertainty continues to rise, “regtech” firms have cropped up to help banks and financial firms tackle a landscape that increasingly resembles a game of whack-a-mole. Regtech, for reference, is technology designed to solve challenges around regulation compliance, including risk management and data reporting.
Some stats to consider: Since the 2008 financial crisis, banks have paid $321 billion in fines. And that’s just on the reactive side of the equation. To get ahead of the curve, firms should be investing in proactive strategy, but that isn’t cheap, either. Thomson Reuters projected that the financial services industry would spend $100 billion on compliance expenditure in 2017 alone.
Hear from Kevin King of ID Analytics on ways to stay ahead of evolving fraud tactics in today’s digital landscape.
During a speech on GDPR and accountability, UK Information Commissioner Elizabeth Denham said it best. “If a business can’t show that good data protection is a cornerstone of their practices, they’re leaving themselves open to a fine or other enforcement action that could damage bank balance or business reputation.”
While it’s all well and good that regtech is here to help with the mounting complexity of compliance, many financial firms are still behind the times when it comes to implementing regtech. In looking to the future, CB Insights named automation as a top regtech trend to watch. The firms that have yet to implement a solid proactive strategy are idling in the seedling stage of their workflow. They’re manually capturing data on their customers and prospects, perhaps once a month or once a quarter, and then organizing that data in Excel spreadsheets.
As these firms mature and their compliance strategy matures with them, automation will be the next step. Automated technology will help to not only collect data more efficiently, but also to continuously monitor it. Ultimately, CB Insights expects full-fledged regtech processes to rely on predictive analytics, using AI and machine learning to proactively identify and prepare for risk.
Take identity verification as an example. Though on the surface, modern identity verification processes seem automated, many still require manual review on the back end. Utilizing automated data capture, on the other hand, will allow firms to verify the digital identity of a consumer on demand with machine learning technology.
To sum it up, automating the regtech workflow means more than just smoothing out processes and enhancing efficiency. It means moving away from a model of static data, where databases sit vulnerable to breaches. It means having an adaptable system that’s continuously learning and updating. It means complying with today’s regulations as well as the regulations of tomorrow.
To learn more about combating risk and managing fraud with automated data, talk to an Urjanet data expert today.
You might also be interested in:
- Solidifying Digital Identity in the Sharing Economy
- Highlights from FinTech South 2018
- From KYC to KYB: A Brief History
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About Amy Hou
Amy Hou is a Marketing Manager at Urjanet, overseeing content and communications. She enjoys writing about the latest industry updates in sustainability, energy efficiency, and data innovation.