Torchora
Back to Home

Key Responsibilities and Required Skills for a Fraud Manager

💰 $110,000 - $175,000

Risk ManagementFinanceSecurityOperations

🎯 Role Definition

As our Fraud Manager, you will be the cornerstone of our organization's defense against fraudulent activities. This is a highly visible and critical role where you will architect, implement, and continuously refine our end-to-end fraud prevention framework. You will lead a dedicated team, leveraging cutting-edge technology and deep data analysis to proactively identify emerging threats, mitigate risks, and minimize financial losses. Your strategic vision will directly impact our bottom line, protect our brand reputation, and ensure a secure and trustworthy experience for our global customer base. You are not just managing fraud; you are building a resilient ecosystem of trust and safety.

📈 Career Progression

Typical Career Path

Entry Point From:

  • Senior Fraud Analyst / Lead Fraud Analyst
  • Risk Operations Manager
  • Data Scientist (with a focus on risk or trust & safety)

Advancement To:

  • Director of Fraud & Risk Operations
  • Head of Trust & Safety
  • Vice President of Risk Management

Lateral Moves:

  • Senior Compliance Manager
  • Head of Payments Strategy
  • Product Manager, Risk & Identity

Core Responsibilities

Primary Functions

  • Architect, implement, and continuously optimize a comprehensive, multi-layered fraud prevention strategy for all transaction channels, including credit/debit cards, ACH, and alternative payment methods.
  • Lead, mentor, and scale a high-performing team of fraud analysts, fostering a culture of critical thinking, proactive investigation, and continuous learning.
  • Own the complete lifecycle of fraud case management, from initial detection and investigation to resolution and reporting, ensuring timely and effective handling of all incidents.
  • Conduct deep-dive analysis of large, complex datasets to identify sophisticated fraud patterns, emerging attack vectors, and underlying vulnerabilities in our systems.
  • Develop, monitor, and refine fraud detection rules, machine learning models, and scoring algorithms to maximize detection rates while minimizing friction for legitimate users.
  • Manage and own the key performance indicators (KPIs) for the fraud function, including loss rates, chargeback rates, manual review efficiency, and false-positive ratios, reporting on these metrics to executive leadership.
  • Oversee the entire chargeback and dispute process, developing strategies to effectively represent and win disputes to recover revenue and maintain low chargeback rates.
  • Act as the primary liaison and manage relationships with third-party fraud solution vendors, payment processors, and banking partners to enhance our fraud prevention capabilities.
  • Collaborate closely with Product, Engineering, and Data Science teams to design and implement new anti-fraud features, tools, and data pipelines into our core products.
  • Spearhead the organization's incident response during large-scale fraud attacks, coordinating cross-functional efforts to contain the threat, mitigate losses, and conduct post-mortem analysis.
  • Assess fraud risks associated with the launch of new products, features, and market expansions, providing strategic recommendations to business stakeholders.
  • Maintain a deep understanding of the global fraud landscape, including account takeover (ATO), friendly fraud, payment fraud, and other emerging typologies relevant to our industry.
  • Ensure all fraud prevention processes are compliant with relevant legal and regulatory requirements, including KYC (Know Your Customer) and AML (Anti-Money Laundering) standards.
  • Develop and deliver ongoing fraud awareness training and documentation for internal teams, including customer support, to create a strong first line of defense.
  • Drive the optimization of customer authentication and verification flows, balancing robust security measures with a seamless and positive user experience.
  • Prepare and present compelling business cases and strategic roadmaps for new fraud prevention technologies, tools, and headcount investments.
  • Analyze and interpret performance of machine learning models in production, providing feedback to data science teams for model retraining and enhancement.
  • Establish and refine policies and procedures for manual review queues to ensure consistency, accuracy, and operational efficiency.
  • Lead complex, sensitive investigations into internal and external fraud, collaborating with legal, HR, and law enforcement agencies as required.
  • Champion a data-driven decision-making culture within the risk organization, using data to tell a story and influence senior leadership.

Secondary Functions

  • Support ad-hoc data requests and exploratory data analysis for various business units.
  • Contribute to the organization's broader risk management strategy and roadmap.
  • Collaborate with business units to translate data needs into engineering requirements.
  • Participate in sprint planning and agile ceremonies within cross-functional teams.

Required Skills & Competencies

Hard Skills (Technical)

  • Advanced SQL: Deep proficiency in writing complex queries for data extraction, manipulation, and analysis from large relational databases.
  • Fraud Detection Platforms: Hands-on experience with industry-standard fraud management tools (e.g., Sift, Kount, Forter, Seon, or similar in-house systems).
  • Data Analysis & Visualization: Expertise in using tools like Python (Pandas), R, Excel, Tableau, or Power BI to analyze trends and present findings.
  • Payment Ecosystem Knowledge: In-depth understanding of the payment lifecycle, including card network rules (Visa, Mastercard), ACH processes, and chargeback reason codes.
  • Rule Engine Management: Proven ability to create, test, and maintain complex rule sets within a fraud prevention system.
  • Statistical & ML Concepts: Familiarity with statistical analysis and machine learning concepts as they apply to fraud detection and risk modeling.

Soft Skills

  • Strategic & Analytical Mindset: Ability to see the big picture, analyze complex situations, identify key risks, and develop effective, data-driven strategies.
  • Leadership & Team Development: Proven experience in managing, coaching, and motivating a team of analysts to achieve peak performance.
  • Exceptional Communication: Ability to articulate complex fraud concepts and data insights clearly and concisely to both technical and non-technical audiences, including executive leadership.
  • Cross-Functional Collaboration: A natural ability to build strong relationships and work effectively with teams across Product, Engineering, Data Science, and Operations.
  • Decisive Problem-Solving: The capacity to make sound, timely decisions under pressure, especially during active fraud incidents.
  • Resilience & Adaptability: Thrives in a fast-paced, dynamic environment and can quickly adapt strategies in response to evolving fraud tactics.

Education & Experience

Educational Background

Minimum Education:

  • Bachelor's Degree in a relevant field.

Preferred Education:

  • Master's Degree in a quantitative or related field.
  • CFE (Certified Fraud Examiner) certification is a strong plus.

Relevant Fields of Study:

  • Business Administration
  • Finance / Economics
  • Criminal Justice
  • Data Science / Statistics
  • Computer Science

Experience Requirements

Typical Experience Range: 5-8+ years of progressive experience in the fraud prevention, risk management, or trust & safety space.

Preferred:

  • 2+ years of direct people management experience, leading a team of fraud or risk analysts.
  • Experience within a high-growth tech, e-commerce, or fintech environment is highly desirable.
  • Proven track record of owning fraud loss metrics and successfully reducing them through strategic initiatives.
Explore More Careers