The increasing volume and diversity of data present opportunities for organisations to grow and expand into new areas. However, it also presents challenges, such as the “garbage in / garbage out” principle. Data is critical to operations, and when used wisely, it can yield valuable insights that enhance revenue, reduce expenses, and mitigate risk. However, inefficient data handling can lead to reputational, legal, and regulatory risks, as well as very expensive growing pains.
In response to the rapidly evolving threat landscape and feedback from our financial crime-fighting community, we are highlighting several data-driven strategies that support our clients.
At FinCrime Dynamics, we specialise in enabling fintechs and digital banking innovators to deploy next-generation, AI-powered financial crime programs. Our focus lies in testing and redefining core control systems—particularly transaction monitoring and sanctions screening—using artificial intelligence and synthetic data.
Our solutions don’t just reduce risk—they empower clients to unlock new revenue opportunities, expand into previously high-risk markets, and launch new product lines with confidence. With the right compliance tools, businesses can scale faster and safer.
Data-driven decision-making is no longer optional—it is a competitive imperative. Our work ensures that clients stay ahead of the curve.
Modern fintech products, like virtual debit cards or real-time payments, create high transaction volumes. Launching these services without a robust, scalable compliance infrastructure increases exposure to risk and testing these systems is essential.
By using AI and data strategies:
Systems learn from data to understand what “normal” looks like and highlight anomalies, often discovering patterns that humans would miss. This results in faster, more accurate detections, fewer false positives, and reduced operational burdens. And, if there is limited data available, say with a new product line, synthetic data is the key.
As data volumes and diversity grow, so do the stakes. Poor data handling can lead to regulatory fines, operational failures, and reputational damage. We address the “garbage in, garbage out” challenge by emphasising data integrity and intelligence, turning messy datasets into strategic assets.
How do we do it?
Our suite of services is tailored to tackle financial crime challenges with data and technology at the core:
Daniel Turner, chief product officer
Daniel is a strategic product leader with deep expertise in machine learning applications and financial system modelling within the space of financial crime prevention. He has tackled complex challenges in data sharing, intelligence synthesis, and the delivery of complex technologies to customer systems. His interest lies in combining his training in Neuroscience with financial crime behavioural data to improve machine learning systems. Daniel holds an MSc in Neuroscience from the Institute of Psychiatry, Psychology & Neuroscience (KCL).
Martyn Higson, chief technology officer
Before joining FinCrime Dynamics, Martyn worked at Featurespace (acquired by Visa) for 7 years, helping the business grow from 60 to 400 people. He deployed machine learning platforms into some of the world’s largest banks and processors, before scaling the Implementation Engineering team to over 30 engineers globally. As part of managing the front-line technical teams, Martyn played a key role advocating for customer-centric features and improved maintainability.
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