About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Corlytics Regulatory Risk Intelligence Adds New Dimension to Compliance

Subscribe to our newsletter

With regulators taking a tough stance on non-compliance, enforcement actions running into billions of dollars, and compliance departments under stress, how can financial institutions pull-back from the brink, improve control of compliance, and reduce regulatory risk? We caught up with John Byrne, CEO at Corlytics (and former CEO at Information Mosaic) to discuss how firms can improve compliance by employing regulatory risk intelligence and analytics.

Corlytics was founded in 2013 to provide regulatory risk intelligence to both financial institutions and regulators. A self-styled regtech, the company collects, normalises and analyse global enforcement data and other important regulatory information to give firms evidence-based intelligence that can be used to make better regulatory planning and execution decisions.

Byrne explains: “Post-trade activity is often seen as a cost, but most regulatory issues, such as fraud, often have a root cause in lack of controls in the middle and back office. Financial services firms invest in risk and compliance systems, many invest about 20% of IT spend here, but the outcome of regulation can still be horrific as middle and back office controls are starved of spend. Which is why we started Corlytics. People talk about regulatory risk, but we define and measure it on a risk weighted basis.”

Corlytics Controls Explorer gathers enforcement action, under licence, from regulators around the world. An action from the SEC, by way of example, could be about 200 pages of legal judgement. Corlytics categorises the information into 160 data attributes that are also used across UK Financial Conduct Authority (FCA) and Asian enforcement actions – to ensure it is making like-for-like comparisons. It then normalises the data before applying analytics to expose the root causes of enforcement actions.

This is no mean feat, with Corlytics employing a multidisciplinary team of legal analysts, risk professionals and data scientists to understand and analyse enforcement actions. The company uses a modicum of machine learning to match legal text and the 160 data attributes it uses in risk models developed in Python, and artificial intelligence bots to pick up any changes published by global regulators.

The software is usually procured by compliance, internal audit, heads of non-financial risk, or chief control officers, an emerging function in financial institutions’ front-line defence. Byrne says: “Banks model credit and market risk, but do little around the biggest risk in the bank, legal and regulatory risk. Balance sheets often show about 100 people working on credit impairments and only three on legal issues with regs.”

By using Corlytics Controls Explorer, financial institutions can understand their regulatory risks, implement controls to reduce them or, at least, gain early warnings of potential risk.

The company has more than 10 clients split pretty equally between regulators and banks, and expects the balance to endure as client numbers rise in response to the desire of both regulators and banks to achieve beneficial outcomes from regulation.

Corlytics’ recent projects include work with the FCA to produce an intelligent regulatory handbook. The project applied a central, common taxonomy to all regulations, allowing material in the handbook to be tagged and machine read, thus turning a legal document into a searchable database. The company is also involved in an FCA sandbox working on how to reduce the risk associated with compliance modelling for regulated firms.

Subscribe to our newsletter

Related content

WEBINAR

Upcoming Webinar: GenAI and LLM case studies for Surveillance, Screening and Scanning

6 November 2025 11:00am ET | 3:00pm London | 4:00pm CET Duration: 50 Minutes As Generative AI (GenAI) and Large Language Models (LLMs) move from pilot to production, compliance, surveillance, and screening functions are seeing tangible results — and new risks. From trade surveillance to adverse media screening to policy and regulatory scanning, GenAI and...

BLOG

Fenergo Enhances Financial Crime Compliance Capabilities with Agentic AI Integration

Fenergo has introduced an updated financial crime solution – the FinCrime Operating System (FinCrime OS) – featuring a new agentic AI layer aimed at significantly improving operational efficiency within financial institutions. This development comes against a background of spiralling operational costs and rising compliance demands enhanced by geopolitical tension and regulatory flux. Marc Murphy, CEO,...

EVENT

ESG Data & Tech Briefing London

The ESG Data & Tech Briefing will explore challenges around assembling and evaluating ESG data for reporting and the impact of regulatory measures and industry collaboration on transparency and standardisation efforts. Expert speakers will address how the evolving market infrastructure is developing and the role of new technologies and alternative data in improving insight and filling data gaps.

GUIDE

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...