The evolution of regtech
Our CEO once commented, “over our long history periods of significant regulatory change have provided the greatest opportunities” – and it couldn’t be more true.
Since the global financial crisis a plethora of regulation has been introduced and enforced. Whilst the pace of new regulatory initiatives has certainly ebbed, the consequences of such change are vast and remain in play.
Many industry commentators question whether this increasing level of regulation will hinder innovation and slow down processes. Contrary to this belief, the opposite trend is emerging with a greater focus on developing technological solutions to new/greater regulatory requirements.
What to do?
While it can appear initially overwhelming to market participants affected by such regulation, tackling what is required through a simple framework is a good starting point. For example:
- identify required information/ risks;
- aggregate and normalise data;
- perform any required calculations;
This framework is particularly effective as it can be applied to any regulation, whether it is Solvency II, the Alternative Investment Fund Managers Directive (AIFMD), the Packaged Retail and Insurance-based Investment Products regulation (PRIIPS), or the Markets in Financial Instruments Directive II (MiFID II).
We see financial institutions concentrating on the first the three steps, investing in new data management technologies and seeing meaningful results.
While many risk analytics and reporting procedures are standardised these days, innovative technologies are also coming to market. Firms are making increased use of new data and analytics tools and services, using machine learning, to help interpret it.
For example, we are currently piloting a machine learning (ML) tool for chief risk officers, which builds “intelligent networks” based on a clients’ portfolio. An example of how it could work would be – there’s been a copper mine explosion in North America. Based on the data the client has given us, we know they have a high weighting in Apple, which uses copper when making its iPhones; and this explosion will cause a spike in the copper price. So the tool would then send an alert to the chief risk officer to inform them of this. This can also be used to better inform investment decisions and enhance performance.
How has this evolution come to pass?
Regulation and the solutions required to comply with them evolve. There are examples where regulation is introduced at a high level – with some high level principles defined – followed by a series of technical specifications. In response, affected institutions rush to create operations in order to comply. Then, usually following a few reporting periods, the financial institutions take a step back and review whether the system they have implemented is fully effective; similarly, the regulators also review whether the regulation is working as intended.
There are many examples of where financial institution realise they developed something so quickly it is not necessarily fit for purpose. For example, some clients introduced a Solvency II reporting solution that needed to be updated to something more scalable from a data management perspective.
There are also a handful of examples where the regulator dials back or expands certain technical requirements. One example is PRIIPS, which is an evolution of the Key Investor Information Document (KIIDS). Both are meant to be standardised, comparable fund summaries for retail investors. Both are meant to show key features of an investment (e.g. time horizon, underlying investments, risk levels etc) in a consumer friendly format. The Undertakings for Collective Investment in Transferable Securities (UCITS) has included KIID requirements since 2011, whilst the PRIIPS KID is for non UCITS retail funds. Fortunately, existing technologies can be adapted to address its broader scope.
At this pivotal point of regulatory and technological evolution, the industry has proven itself to be resilient and, as always, it will find a way to adapt. The industry will continue to evolve to maximise efficiencies, drive down costs and manage risks.
At the moment, when it comes to emerging technologies and artificial intelligence (AI) there is a lot custom, niche solutions being created independently, and not much scale. Over the years, there will likely come a time when these products will be available off-the-shelf.
Mark McKeon, global head of investment analytics, State Street Global Exchange