By: David Pagliaro, EMEA head of State Street Global Exchange
Our CEO once commented: “Over our long history, periods of significant regulatory change have provided the greatest opportunities.” This couldn’t be more true today. Since the global financial crisis, a plethora of regulation has been introduced and enforced. While the pace of new regulatory initiatives has ebbed, the consequences of such change are vast and remain in play.
For the largest banks the heavy lift is almost complete as they were the focus of earlier waves of regulation; insurers are reaching the tail end; and for asset managers it is slightly more intense today. Overall, institutions are notably better prepared when it comes to regulation.
However, the need for the right data remains critical. Building efficient processes in the face of new data and reporting requirements is a significant challenge. While it can appear overwhelming at times, tackling what is required through a simple framework is a good starting point. For example:
1. Identify required information/risks
2. Aggregate and normalise data
3. 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), Packaged Retail and Insurance-based Investment Products (PRIIPs) regulation, or Markets in Financial Instruments Directive II (MiFID II).
We see institutions concentrating on the first 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, and using machine learning to help interpret the data.
For example, we are piloting a machine learning tool for chief risk officers, which builds ‘intelligent networks’ based on a client’s portfolio. An example of how it could work goes like this: 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. 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.
How has this evolution come to pass?
Regulations and the solutions required to comply with them have evolved. 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, regulators also question whether a regulation is working as intended.
There are many examples of financial institution realising they developed something so quickly it is not necessarily fit for purpose. For example, when banks initially had to comply with stress testing rules it was predominantly an exercise completed by an army of consultants. This eventually evolved into a technical system, which has also evolved as time passes. Similarly, we have examples of clients that introduced a Solvency II reporting solution that needed to be updated with 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. A recent example is PRIIPS, which is an evolution of Undertakings for Collective Investment in Transferable Securities (UCITS) Key Investor Information Documents (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. UCITS has included KIID requirements since 2011, while the PRIIPs Key Information Document (KID) is for non UCITS retail funds. Existing technologies can be adapted to address the broader scope of PRIIPs KIDs.
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. It will also continue to evolve to maximise efficiencies, drive down costs and manage risks.
At the moment, when it comes to emerging technologies and artificial intelligence, there are a lot of 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.
The views expressed in this article are the views of David Pagliaro, EMEA head of State Street Global Exchange, and are subject to change based on market and other conditions and factors. They do not necessarily represent the official views of State Street Global Exchange and/or State Street Corporation and its affiliates.