The past has shown that failure to manage risks appropriately has been very costly for financial institutions. One of the key responses to the recent market manipulations was the European Market Abuse Regulation (MAR), which came into force in June 2016, and saw the start of a new era of surveillance implementations.
While MAR is the regulation that most clearly defines the types of market abuse practices that need to be monitored, it creates the danger of a false sense of security through a mentality of just ticking all the boxes. Focusing on known manipulation patterns can come at the cost of missing rogue trader behaviour. Recently regulators have started inquiring about what financial institutions are doing on top of MAR, implying that the MAR is not the “be all and end all”.
Maturing of technologies like advanced analytics, big data technology, natural language processing and understanding (NLP / NLU), and machine learning, has resulted in these technologies becoming an integral part of newer surveillance solutions. They help to bring keywords and phrases into context and increase true positives while significantly decreasing the noise and effort involved in processing false positives for communications while also helping to better identify patterns for trade surveillance.
Solutions promising holistic surveillance capabilities have started to appear. These tools aim to combine previously siloed Compliance areas and provide a fuller picture of transactions, communications and behavioural patterns to enhance the investigation process. However, these solutions are still at the early stages of combining different forms of data in order to raise new or suppress false alerts.
Financial institutions need to decide if they want to move along the surveillance maturity curve as leaders or followers in the industry. Moving along the curve brings with it a variety of challenges, such as ensuring data availability, upskilling staff, and potentially making significant monetary investments. Nevertheless, it can bring several benefits such as more accurate detection of truly manipulative behaviour coupled with a reduction in false positives, which frees up Compliance resources to focus on deeper analysis and looking beyond the alerts. Surveillance related data and tools can also be leveraged in other business areas, such as Front Office, to gather markets insights and add additional value to the business.
To move from “reactive” to “proactive” surveillance functions, firms need to focus on the following three key interdependent areas:
Understanding the regulations with which the firm must comply globally is the first step towards understanding the scope of surveillance requirements and the technologies needed to sufficiently cover these. Thereafter, it is necessary to look at the business model to define a suitable surveillance strategy and a surveillance operating model tailored to the associated risks of the business. Once defined, the strategy needs to be operationalised and regularly reviewed to convert lessons learnt from the daily process into the tools and processes used by Compliance. Together, these three areas represent the journey from a purely regulation driven surveillance setup to a strategic and operationally effective Compliance function. Along all three stages of the journey lie pitfalls. In the next blogs of this series, we will focus on each of the stages, helping firms to understand the steps they can take to improve their market abuse surveillance capabilities and the latest developments in the market.