Ravelin: Advancing Fraud Prevention Through Real-Time Data Engineering

Overview

Ravelin is a fraud detection and payment optimisation platform operating at the intersection of machine learning, behavioural analytics, and real-time data processing. In an environment where fraud tactics evolve continuously, their technology must adapt dynamically while maintaining accuracy, speed, and reliability at scale.

Knight R&D has supported Ravelin since 2017, working closely with their technical teams to ensure that sustained innovation across their machine learning and data infrastructure is properly identified and defended within R&D tax legislation.

The Technical Challenge

Fraud detection systems must operate in milliseconds, analysing behavioural signals, transaction histories, and contextual data to determine risk in real time. The challenge is not only to detect known patterns, but to anticipate new and evolving tactics without degrading system performance.

Ravelin’s engineering teams developed adaptive scoring models, scalable data ingestion pipelines, and proprietary behavioural analytics frameworks capable of processing high-volume transactional data with minimal latency. Technological uncertainty arose around how to maintain model determinism while allowing dynamic recalibration, how to scale pipelines without compromising data integrity, and how to optimise real-time decision engines under fluctuating load conditions.

These were architectural and algorithmic challenges requiring iterative experimentation and advancement beyond established approaches.

Knight R&D’s Approach

Our role was to work directly with Ravelin’s engineers to distinguish genuine advancement in machine learning and data architecture from routine software iteration.

We analysed the development of proprietary scoring methodologies, real-time data synchronisation frameworks, and adaptive modelling techniques, translating complex machine learning innovation into a structured and defensible technical narrative aligned to HMRC’s criteria.

Given the increasing scrutiny within the R&D tax regime, particular care was taken to ensure the submission clearly articulated technological uncertainty and advancement.

The Outcome

The engagement secured a £1 million benefit, recognising the scale and depth of Ravelin’s innovation.

Beyond the financial return, the process strengthened internal documentation standards and established a robust framework for future claims as the company continues to evolve its fraud prevention capabilities.