Many larger firms, particularly on the sell-side, have started to invest in the integrated surveillance, which seeks to bring together diverse data sets and analyze them holistically because that’s expected to lead to enhanced risk mitigation and business insights.
However, due to the significant investment required to get it right, many smaller firms have not yet started to develop an integrated data program for surveillance. Scattered data impacts the time it takes to respond to threats, market movements and regulatory changes.
To stay ahead of the curve, firms will have to start to seriously think about how to bring together data such as transactions details, communications, market data and more. It requires investment as there are no quick fixes, but when executed correctly, integrated surveillance is a great opportunity to establish a rich, value-adding data set that can power entire organizations. On the other hand, unless firms can fundamentally combine infrastructure and data in a scalable manner, it has limited business value.
Regulators favor integrated data
While regulators do not specify that surveillance needs to be carried out holistically, they are increasingly interested in seeing firms adopt a more integrated framework for dealing with data. This pressure will only increase as technology evolves and regulators themselves enhance their data management capabilities.
Firms need to think strategically about the data-driven technologies they require in order to combine vast volumes of information, so they can reap the long-term benefits of an integrated approach.
A successful program needs to be scalable and embed the ability for firms to change, grow and ingest new data sources, platforms, and systems over time. One of the most important aspects of getting an integrated program right is figuring out how different data sets meet and interact. How do you overlay LEIs, with trader IDs, chat profiles and phone numbers so that a link can be established? This is an extensive data mapping exercise that many have tried and failed at.
Most traditional regtech or surveillance vendors approach regulatory requirements from the perspective of the output – what firms need to report or store. As a result, there are many devised prescriptive and inflexible data schemas that financial institutions must meet before their data can be ingested, and a platform or tool used. This approach is expensive, resource intensive and makes it very difficult for firms to get a return on their investment.
With growing data volumes and varying formats, the key is to work with technology that can ingest data in any format, that can also capture new channels and sources quickly. Another key consideration as firms try to combine data that has a different format is how to ensure all the relevant meta data is captured and nothing missed. With a rigid data schema, it is nearly impossible integrate new formats that do not fit the prescribed template – or guarantee that everything is being captured.
However, there are data-driven platforms that can automatically determine the common denominators and key differentiators between different data types, and then link data together using the commonalities while also bringing in the unique fields. The use of artificial intelligence and machine learning can thereafter learn what a piece of data is meant to look like, so that flags can be raised when there is a change.
Technology has a significant role to play in facilitating integrated surveillance and while many vendors still have some way to go in their ability to make sense of vast volumes of data, there are solutions and platforms that already enable firms to take a more future-proofed holistic approach.
Excerpts from an article written by SteelEye CEO, Matt Smith