Company insight
By utilising advances in AI and cloud computing, Regnology has developed a ‘RegOps’ regulatory reporting system, allowing regulators to pull data in real-time.
It is here that the outsourcing model can utilise the latest technological advances – notably cloud computing and artificial intelligence (AI) – to rework the regulatory reporting process to introduce standardisation and industrialisation. “Because we are so obsessed with standardisation and industrialisation, we can take care of the mutualisation of the costs, as happened in the automotive industry, and we can make the exchange of data between banks and regulators way more efficient,” emphasises Piechocki.
same logic, and there is less and less room for outcome control in regulatory reporting,” Windmoeller explains. ”So, I don't see any objections as to why this should not be outsourced.” Cloud computing provides flexibility in terms of demand, lower cost and high availability, removing the need for a bank to maintain systems in-house. Incorporating AI in the gathering and analysis of data further improves performance.
“Hyperscalers really offer better pricing models to deal with peaks in demands
“Regnology’s purpose is to rethink the burden on banks by bringing to bear unrivalled experience in regulatory reporting and risk data aggregation.”
Outsourcing in action Back in 2013, Regnology was asked to build a regulatory factory in Austria on behalf of the Austrian National Bank, which would affect around 850 of the country’s banking institutions. The company decided to put all the regulatory reporting in a countrywide shared utility called AuRep. Regnology provided the technological backbone to standardise the entire regulatory reporting process for all 850 banks, delivering the data to the Austrian National Bank and the Austrian Financial Markets Authority.
“There is no competitive advantage in regulatory reporting, especially as we see that regulators are looking for every bank to apply the same rules and the
Future Banking /
www.nsbanking.com
and that can bring costs down,” explains Windmoeller. “More automation enables better services and better processes, and we integrate additional services with third-party data providers with other tools. AI brings more intelligence to how banks can handle data, and some banks spend 30–50% of their efforts in regulatory reporting managing bad data quality, and more predictive solutions can help to manage data quality better.” These technologies also open the door for regulatory reporting to be an opportunity for innovation. For Regnology, that means turning the process of data exchange on its head.
“How far from reality is that Star Trek vision of a real-time view of data flows?”
Piechocki asks. “In 2019, we coined an approach we called RegOps, and the simple idea was whether it was possible for a regulator to get data from the whole national banking industry within a week. What needs to happen for such a process to be possible?”
Regnology has been involved in three RegOps projects: one for the Bank of International Settlements and the G20; another for the Federal Deposit Insurance Corporation in the US; and finally one for the Monetary Authority of Singapore. These initiatives have driven the design of a system where the regulatory transfer between the banks and the regulators use the data pull approach. “Today, the approach pushes data from reports into the regulator, but we have redesigned the system so the regulator can pull in the data,” Piechocki explains. “We see a great appetite for RegOps and the pull approach among regulators. If your regulators are able to pull the data at any time and scrutinise it, banks approach the topics of data governance and of data hunting in a different way, which drives a huge chunk of innovation.”
Innovation is about attitude, culture, approach and process, as much as it is about technology. Regnology understands all these aspects of the innovation cycle and is working to take the burden of regulatory reporting off the shoulders of banks. ●
www.regnology.net 27
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