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Fraud Prevention Analyst

eFinancialCareers
Job LocationEdinburgh
EducationNot Mentioned
SalaryCompetitive salary
IndustryNot Mentioned
Functional AreaNot Mentioned
Job TypePermanent , full-time

Job Description

Join us as a Fraud Prevention Analyst

  • Apply a data driven approach to identify , assess, mitigate, monitor and report on fraud risk so we can manage any threat of fraud
  • Importantly, youll also monitor and evaluate the performance of our fraud prevention processes and strategies
  • This is a critical role where youll be responsible for promoting a culture that helps us manage fraud risk effectively within the business
What youll do In your new role, youll identify, assess and understand external fraud risks associated with our business activities, while reviewing and developing processes to help mitigate those potential fraud risks. Youll 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 youll need Were 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. Youll also have:
  • Proficiency in data manipulation tools such as SAS, SQL, Python or similar
  • Proven 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)
  • Experience of data visualisation tools such as Tableau

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