Four defining trends for the future of regulation

Increasing complexity and higher volumes of data have entered the regulation conversation, compelling financial institutions to shift their compliance strategies.

The pace and complexity of regulation that’s built up since the global financial crisis has made it harder than ever for financial firms to manage compliance – from trade reporting mismatches to sprawling and increasingly outdated systems, financial institutions are assessing if there may be a better way to handle regulatory change.

deltaconX’s director of product management, Paul Rennison, walks through some of the key regulatory and compliance developments that the C-suite will need to be prepared for in the coming months.

1. Data standardisation goes global

The wave of financial regulation that came out in the wake of the global financial crisis, such as the Dodd-Frank Act in the US and the European Market Infrastructure Regulation (EMIR) in the EU, has created a mountain of reporting requirements that are expensive to comply with, says Rennison. One of the shortcomings with those rules is a lack of standardisation; trades could be reported by both counterparties in slightly different ways, resulting in significant amounts of reporting data that doesn’t match up, he explains.

As regulators seek to refresh those rules, the International Organization of Securities Commissions (IOSCO) and the Committee on Payments and Market Infrastructure (CPMI) are working together to create a common lexicon for trade reporting to establish greater data harmonisation across jurisdictions. This can improve accuracy but also reduce the expense of having to retain and manage complex data sets that vary depending on where the trade took place. “Standardising this makes it easier for an apple to equal an apple wherever you trade that apple,” says Rennison.

2. The growth of grey IT’

Organisations have fewer resources at their disposal after many people left the industry during the pandemic, while the pace of regulatory change remains relentless, says Rennison. “It’s never a single project within a firm; it’s a programme of work,” he says. “It’s like painting the Forth Bridge – you get to the end and look back, and you have to go and start again.”

This ongoing monitoring and managing of rule changes is expensive. Systems that were robust when post-financial-crisis regulations were first implemented are growing outdated. “It is hard to get continuing reinvestment, you get stuff bolted on to keep it going, so you get the growth of grey IT which becomes even more expensive to maintain as it starts to die,” says Rennison. Organisations need to start reassessing their approach to technology and how to manage compliance where change is constant, and costs continue to surge.

3. Outsourcing strategies for uncertain times

The cost of managing in-house compliance systems is prompting many organisations to consider outsourcing strategies, especially where the benefits of the cloud can be realised. In the past, data was retained in-house because it was deemed to be commercially sensitive information and too high risk to go beyond the organisation’s firewall, says Rennison. Over the past 10 years, that view has shifted as organisations recognise the potential savings – particularly as datasets get bigger and more costly to manage in-house, he says.

By moving to the cloud, systems can be lighter, more agile and more elastic, making it easier to scale in tandem with the growth in data volumes. “If I can get someone else to operate the services for me, then I can take that finite, scarce internal resource and reallocate it somewhere else,” Rennison says. “You’re taking away a lot of the water-carrying functions – the repeat operation processes – so your compliance team can do higher-value work with the data collected.”

4. Driving proactive compliance with AI

Regulators are already adopting AI to support their analysis of reporting data, helping them look for patterns or behavioural changes at both a market level and also at an individual entity level, says Rennison.

The end goal for using AI in this way is the hope that it can help regulators spot incidents like the collapse of Lehman Brothers or Silicon Valley Bank before they happen. “That can enable regulators to start providing warnings rather than just being reactive,” he says. AI is also giving regulators more confidence to analyse larger data sets, with financial institutions expected to supply even more detailed reporting information to support that deeper analysis. AI will also help compliance teams better analyse trading data to bolster efficiency and develop a complete understanding of their risk exposures.

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