The Rise of AI-Enabled SupTech

What are regulators doing with reporting data?

You’ve all heard of FinTech and RegTech, now comes SupTech (Supervisory Technology). More recently being coined, SupTech refers to a new class of tools being created for regulators and other supervisory firms to support their monitoring of data. With the advances of AI, financial regulators are using advanced analytics and AI to gain deeper insights from the vast amounts of regulatory data submitted by firms.

This topic featured in Cappitech’s Q2 EMIR & MiFIR Webinar, where we reviewed ESMA’s latest Transaction Reporting Data Quality Report. Encouragingly, ESMA highlighted improvements across several key EMIR data quality indicators, particularly in areas that had been long-standing regulatory focus points, including valuation reporting, maturity date accuracy, and UTI pairing.

At the same time, ESMA continues to identify discrepancies in MiFIR transaction reporting, particularly where counterparties report different values for the same trade. Common data quality issues were identified in fields such as price, quantity, TVTIC, and transaction timestamps.

As regulators continue investing in AI-powered supervisory capabilities, reporting data is becoming far more than a compliance exercise. It is increasingly being used to identify trends, detect anomalies, and assess data quality at scale. For firms, the message is clear: high-quality reporting data and robust controls are more important than ever as regulatory oversight becomes increasingly data driven.

Standardized DQIs to AI Driven Anomalies

The DQIs and MIFIR counterparty mismatches are based on standardized data reviews that ESMA has put in place to supervise submitted values. In their Data Quality Report, ESMA discussed the start of expanding their supervisory tools to include generative AI. A key example was the launch of a pilot program AI agent tool to review methodologies used by rating agencies. They also stated they were in the final stages of a proof of concept (POC) being organized along with NCAs to monitor for market abuse. The statements from ESMA come after individual EU NCAs have made public AI tools that are live or being built to assist with market abuse and governance monitoring.

During June’s webinar, Cappitech raised a few directions where AI SupTech can be expected to cover. As noted by ESMA and other NCAs, market abuse monitoring fits well with outputs that AI can produce. Using the technology, regulators can set alerts to detect suspicious trading activity, investment firms with higher than average execution price markups and managing discretionary accounts beyond expected risk parameters. The latter is possible by using CONCAT’ed date of birth information in MIFIR reports and reviewing for age suitability.

ESMA also expects AI to help them detect changes in market behavior. This includes revealing trends in what products different segments of the population are trading and changes in notional sizes of asset class/contract type combinations. Such analysis assists regulators with insights into areas they should better focus on monitoring trading and investment activity.