About the role
We’re on a mission to make migration easy. We started building Marshmallow in 2017. Since then, we’ve grown from 3 to 700+ people, gained unicorn status, raised ~£140M over three funding rounds, turned profitable, insured millions of drivers and lent millions in car loans. But we’re only just getting started. Our goal is to become one of the largest financial services providers in the world. Over the next 10 years we’ll grow exponentially, not only by scaling our existing products, but also by building new ones. To achieve our goals we need incredibly ambitious, commercially driven people who never settle for ‘good enough’. Marshmallowers are hungry for autonomy and ownership, and would rather improve than coast. Everyone raises standards and has an impact, with a focus on collective success over self-interest. We’ve created an environment where curious, tenacious people win and grow together. If that sounds motivating, this could be the place for you. The Fraud Intelligence Team The Fraud Intelligence Team is a small, newly expanding team that defends Marshmallow against fraudulent activity through investigative analysis and industry intelligence.
The team goes beyond rules-based fraud checks - we exist to detect new policy fraud trends, investigate networks, and find what automated systems miss. Think ghost broking rings, organised misrepresentation, identity fraud, and patterns that only surface through deep, creative investigation. This is an early-stage function with a lot to build, and you'll have a direct hand in shaping what it becomes. We’re hiring a Senior Fraud Intelligence Analyst to bring experience to
the team - someone who has investigated policy insurance fraud before and can hit the ground running while helping shape what this function becomes. Please note we are not in a position to offer sponsorship and/or a visa for this position. What you’ll be doing Investigating fraud networks end-to-end: taking a single alert signal and expanding it into a full intelligence picture across linked policies, devices, addresses and identities Using tools like device fingerprinting, banking data, identity verification, quoting history and telematics to build evidence for cancellation Analysing internal policy data at population level to identify emerging fraud trends before they become entrenched Working with data science to develop and refine fraud detection models, network analysis tools, and automated alerting systems Building and expanding fraud detection capability across the policy lifecycle Working with AI tools and SQL to query data, spot patterns and accelerate investigations Documenting investigations and producing intelligence reports for internal stakeholders and external bodies (IFB, IFED, CIFAS) Mentoring and quality-assuring the work of more junior analysts in