Join our digital revolution in NatWest Digital X In everything we do, we work to one aim. To make digital experiences which are effortless and secure. So we organise ourselves around three principles: engineer, protect, and operate. We engineer simple solutions, we protect our customers, and we operate smarter. Our people work differently depending on their jobs and needs. From hybrid working to flexible hours, we have plenty of options that help our people to thrive. This role is based in the United Kingdom and as such all normal working days must be carried out in the United Kingdom. Job Description Join us as a Fraud Prevention Analyst You’ll identify, assess, mitigate, monitor and report on fraud risk so we can manage any threat of fraud Importantly, you’ll also monitor and evaluate the performance of our fraud prevention processes and strategies This is a critical role where you’ll be responsible for promoting a culture that helps us manage fraud risk effectively within the business What you'll do In your new role, you’ll assess and understand external fraud risks associated with our business activities, while reviewing and developing processes to help mitigate those potential fraud risks. You’ll also: Evaluate new data sources and integrate them into our existing strategies, so we can optimise our ability to prevent fraud activity Provide ongoing, in-depth analysis that will identify existing and emerging fraud trends which will influence business decision making Build and maintain strong internal and external business relationships, sharing information and data to enhance our fraud prevention capability Demonstrate subject matter expertise which will lend itself to the development of new products, systems and processes across the business The skills you'll need We’re looking for someone who has strong technical and numerical skills, with experience in using risk management tools and techniques including credit score systems, data modelling, data mining and behavioural scoring systems. You’ll also have: Experience in applying statistical modelling and evaluation techniques to the development of fraud risk prevention strategies A degree level qualification in a numeric discipline like Mathematics, Statistics or Operational Research Strong database management skills and other programming languages, and proven experience in interpreting management information (MI)