FinTech Financial Crimes and Fraud

Join Financial Crimes and Fraud TalentCloud

If you possess mastery in any of the roles or skills below, you can apply to this TalentCloud. Once you become an approved Experfy TalentCloud member, you will get exclusive access to jobs and project opportunities from our clients.

Popular Cloud Architect Roles in this TalentCloud

  • Criminal Analyst
  • Cyber Fraud Analyst
  • Ethics and Conduct Management Analyst
  • Financial Intelligence Analyst
  • Financial Compliance Analyst
  • Financial Crimes Analyst
  • Financial Crimes Data Analyst
  • Financial Crimes Insights Analyst
  • Financial Crimes Risk Analyst
  • Financial Due Diligence Analyst
  • Financial Investigative Analyst
  • Financial Support Analyst
  • Forensic Payments Analyst
  • Fraud and Risk Analyst
  • Fraud Control
  • Fraud Detection
  • Fraud Operations

Cloud Description

Experts in this TalentCloud should be able to create automated risk decision strategies as well as data-driven fraud mitigation strategies. Leverage customer data and transactional unstructured data to build risk segmentation and mitigation strategies. Other responsibilities include:

  • Review monetary and non-monetary fraud transactions, conduct interviews, and analyze transaction data to detect fraudulent or unusual patterns and trends in support of the investigative process
  • Build necessary reporting to track the effectiveness of risk strategies and decision tools
  • Work closely with engineering teams to drive the availability of relevant data, tools, and infrastructure and continue to enhance automated underwriting capability
  • Scale strategic and financial planning processes (Forecasts, Budgets, Strategic Planning)
  • Analyze and report actual financial performance to Executives and other leaders
  • Prepare recurring credit stress testing, Dual Risk Rating, and other credit risk reports and dashboards as well as ad hoc credit risk analysis or reports as requested by management
  • Work closely with the Financial Partnerships, People, and Talent teams to forecast and operationalize financial budgets and headcount plans
  • Lead projects and contribute your thought leadership to implement financial crime risk management frameworks across the organization
  • Own KPI reports to management on financial performance and progress
  • Design and implement financial risk systems and software
  • Implement and perform model monitoring tests and procedures and produce recurring reports evaluating the continued validity of department-owned models
  • Conduct all aspects of the compliance review, including scoping, sampling, data analysis, research, control testing, meetings with management, root cause analysis, and preparation of the final report
  • Assist with the improvement of business procedures and process updates as necessary to meet compliance requirements
  • Stay up to date on regulatory changes, assess impact, and communicate changes to relevant stakeholders

Preferred Education

  • Bachelor’s degree in accounting, quantitative field, finance, computer science, computer engineering, IT or economics

Required Skills

  • 3+ years of financial or risk-related analytical experience preferably in any of the following: Financial Crime, Fraud, Credit Risk, Collections, Operations
  • Hands-on experience with either SQL, SAS, R, or Python
  • Strong analytical abilities and proficiency with spreadsheets and slides 
  • Ability to conduct research, work independently, determine priorities and meet deadlines
  • Excellent written and verbal English communication skills
  • Advanced quantitative and analytical skills, with strong detail orientation
  • Proven organizational and project management skills, including excellent time management and the ability to handle multiple concurrent assignments
  • Ability to work under pressure, allocate time efficiently and manage multiple priorities at once

Preferred Skills 

  • Prior experience in banking in risk or FIU/AML/KYC function
  • Experience in producing Business Intelligence reports, such as Looker, Tableau
  • Exposure to statistical concepts
  • Quantitative and hands-on knowledge of various machine learning, deep learning, and AI algorithms and their implementations
  • Strong interest in fraud trends, strategies, and tools