4 of 4 Fraud Analyst Jobs in London

About the team: As part of the Forensics & Integrity Services, our Forensic Data Analytics team provides advanced analytics services to support high profile and sensitive client matters such as fraud investigations, financial crime, disputes and litigations. Our work involves developing data and analytics solutions to regularly ingest and monitor data to detect regulatory and compliance risks such as fraud … data science techniques such as investigative data linking, social network analysis, statistics, machine learning and large language models. About the role: We are seeking a dynamic and experienced Senior Fraud Analyst to join our team. In this role, you will work closely with financial services clients to identify and analyse emerging fraud trends, develop, and implement effective … fraud detection strategies, and provide expert guidance on fraud and scams prevention. You will collaborate with client teams to manage multiple priorities and deliver high-quality solutions. Acting as a subject-matter expert, you will address third-party fraud, APP scams, and money mules, ensuring clients receive the best advice and support in mitigating fraud risks. More ❯

and comprehensive benefits. Your Mission The Customer Risk Monitoring team is responsible for implementing and maintaining the analytical intelligence that protects Teya and its customers from financial risks, including fraud, money laundering, and terrorism financing. Our goal is to minimise financial losses and risk exposure while supporting and maintaining our customers' trust and ensuring compliance with regulatory requirements. We … data-informed decisions Partner with data engineering to design and maintain scalable, reliable data models and ETLs that underpin both operational and strategic use cases Help define and analyse fraud and AML KPIs, helping the business plan and course-correct with confidence Promote a culture of data-driven decision-making across the organisation Your Story We're looking for … a Senior Data Analyst with a strong analytical foundation and a passion for tackling complex, ambiguous problems in the financial risk domain. Must-haves 4+ years of professional experience as a data analyst, preferably in fraud, AML, or financial risk monitoring Solid understanding of statistical concepts and experience applying methods such as forecasting, time series analysis, A More ❯

see one, and the judgement to know that 'can' doesn't always mean you 'should'. What you can expect You'll be joining the team as a Senior Analyst in Financial Crime Models Management, specialising in fraud monitoring. Reporting to the FinCrime Models Management Lead, you'll be a part of a fast-growing business that is … Payment Screening tools are effective and robust. The team supports the business day-to-day whilst also being a key participant in strategic projects. We are looking for a Fraud Models specialist to design, develop and tune rules and machine learning models targeting fraudulent transactions. You will be familiar with the fraud risks across a variety of banking … grow in your role, enriching your FinCrime knowledge while developing more sophisticated FinCrime analytics and capabilities to identify potentially suspicious activity. This is a role for someone who understands fraud typologies and monitoring approaches with experience of working with vendors to deliver an essential part of our ambitious, growing organisation. You will understand the impact of data quality issues More ❯

We are currently seeking a Fraud Analyst to work with our public sector client 6 months contract Excellent day rate inside IR35 Location: London/Hybrid The ideal candidates will have a proven Fraud Analyst background within public sector ideally holding active SC clearance. Skills & responsibilities: Review and triage fraud alerts from live service data. … Ensuring queues & workstreams are well maintained and sufficient time is allocated for priorities. Experience in the counter-fraud or financial crime space. Able to identify key trends and movements in data, as well as potential anomalies that require further investigation. Ability to work in a targeted and fast-moving environment. Demonstrable ability to manage and prioritise workload effectively, particularly More ❯