Fraud Data Analyst

2 weeks ago

London Area, United Kingdom LexisNexis Risk Solutions Full time

Fraud Data Analyst

About the Business: LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Business Services vertical, we offer a multitude of solutions focused on helping businesses of all sizes drive higher revenue growth, maximize operational efficiencies, and improve customer experience. Our solutions help our customers solve difficult problems in the areas of Anti-Money Laundering/Counter Terrorist Financing, Identity Authentication & Verification, Fraud and Credit Risk mitigation and Customer Data Management. You can learn more about LexisNexis Risk at the link below, risk.lexisnexis.com

About our Team: You will be part of a team of analysts using global data from the largest real-time fraud detection platform to optimise solutions for our enterprise customers.


About the Role: You will use your experience with data analysis to investigate suspicious behaviour. This will provide new insights to customers leading to immediate real-world impact in the form of lower customer friction, reduced fraud losses and as a result, increased customer profitability.

You’ll leverage a real-time platform analyzing billions of transactions per month for some of the largest companies operating in Financial Services, Insurance, e-Commerce, and On-Demand Services. These tools will allow you to attain a unique perspective of the Internet and every persona connected to it. You’ll be continually collaborating with internal product and engineering teams, customer-facing account teams, and external business leaders and risk managers. The comprehensive policy you build will go head-to-head against some of the most motivated attackers in the world to protect billions in revenue.


Responsibilities:

  • Conducting in-depth reviews of complex fraud cases. identifying trends and actionable insights, documenting your findings and making clear recommendations on how to mitigate risk
  • Using your SQL and Python skills to increase our customers’ fraud capture. While reducing false positives, conducting offline analysis of customer data to expose patterns and statistically tune policies. Produce executive-level reports and own the end-to-end delivery of your recommendations by writing rules into the ThreatMetrix® decision engine
  • Building dashboards & reports to track value delivered by the solution. Increasing focus on more bespoke external-facing dashboards that surface the most important insights to each customer
  • Using your excellent attention to detail and ability to craft a story through data. Delivering industry-leading presentations for external and executive audiences with non-technical background
  • Scoping, planning, and delivering customer-focused projects including root cause analysis, reports, dashboards, rule mining and health checks. Demonstrate a professional and customer-centric persona when interacting directly with customers via phone, e-mail, and chat
  • Collaborating with ThreatMetrix teams. Including Products, Engineering, Sales and other Professional Services colleagues around the world to continually redefine best practices


Requirements:

  • Experience within a Fraud Strategy or Fraud Analytics function.
  • Proficient in SQL (Python knowledge and BI tools like SuperSet, PowerBI, Tableau a bonus).
  • Experience of working with fraud system management, such as ThreatMetrix, Emailage, Featurespace, Hunter, Iovation, BioCatch, Actimize Falcon, etc.
  • Interest or experience in consulting within the risk, fraud or payments industry.
  • Have attention to detail to ensure quality of project delivery for customers stands out amongst industry peers
  • Track record of building external and executive reports and presentations
  • Have extensive multi-tasking and prioritization skills. Needs to excel in fast paced environment with frequently changing priorities
  • Fluency in languages spoken across EMEA are a bonus.



Learn more about the LexisNexis Risk team and how we work here

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