Despite astronomical sums being spent by banks on surveillance – almost US$ 740m by 15 surveyed Tier I and Tier II banks alone in the first two years after MAR came into effect in the UK1 – electronic surveillance is still in its infancy, and gaps in efficacy and performance mean that there is appetite for further spending, development and automation.
In 2019, EU financial markets regulatory authorities imposed fines and other sanctions on a number of firms and institutions that failed to provide sufficient evidence of their ability to implement effective and efficient market abuse risk management measures.
Trade surveillance encapsulates the processes and procedures that help financial institutions detect and prevent trading rule violations. While various regulations push for increased scrutiny and security, MAR and MiFID II notably have far-reaching implications for trade behavior, post-trade surveillance and pre-trade risk controls checks.
Under MAR and MiFID II, firms are required to detect and report unlawful behaviour in a timely manner by putting preventative measures and solutions in place. To achieve compliance, first and second line surveillance functions need to be created that provide more holistic, forward-facing surveillance solutions.
For those overseeing the orderly conduct of trading, the Market Abuse Regulation (MAR) in mid-2016 introduced some significant challenges.
Predictive analytics is a branch of advanced analytics wherein a variety of different types of software tools can be used to make predictions about future events.
Exploring why and how buyside firms must appraise their current outlay of trade and transaction order and execution management systems used to generate regulatory reporting data in the EU as well as the technology debt associated with any legacy systems.
