Fraud Analytics & Rules Management Analyst

Bank Islam; Kuala Lumpur; On-site; MYR 60,000 - 90,000; Full time

Job summary

A major banking institution in Kuala Lumpur is seeking a Fraud Analyst to enhance fraud detection systems. The ideal candidate will develop and maintain risk-based detection rules and conduct detailed analyses of fraud patterns. Qualifications include a Bachelor’s degree and 2-4 years in fraud analytics or risk management. This position involves collaboration with regulatory bodies and product owners to mitigate fraud risks.

Qualifications

• 2-4 years of experience in fraud analytics, risk management, data science, or a similar field.
• Experience working with fraud case management systems or detection platforms.

Responsibilities

• Develop and maintain risk-based fraud detection rules.
• Implement fraud typologies from regulatory bodies.
• Conduct deep-dive analysis to identify fraud patterns.
• Develop dashboards for fraud metrics monitoring.

Skills

Proficient in SQL

Proficient in Excel

Analytical thinking

Attention to detail

Problem-solving skills

Education

Bachelor's Degree in Banking, Finance, Information Technology, or related field

Tools

Power BI

Tableau

Job description

Overview

JOB PURPOSE
To enhance the fraud detection system's effectiveness by developing and maintaining risk-based detection rules and analytical models. This role supports regulatory compliance (e.g., NSRC/BNM SFDS), identifies emerging threats, and ensures continuous system accuracy through simulation, tuning, and thematic analysis.

Responsibilities

• Fraud Rules Management & Typology Implementation
  • Implement fraud typologies, indicators, and scenarios sourced from regulatory bodies such as BNM, NSRC, and internal risk governance committees.
  • Maintain and update fraud detection rules based on:
  • Feedback from the investigations team
  • Regulatory alerts and circulars
  • Industry-wide typologies
  • Internal incident reviews
  • Validate and simulate new rules prior to production implementation (if applicable) to assess effectiveness and false positive rates.
  • Monitor post-deployment rule performance to ensure detection accuracy and minimal operational impact.
  • Maintain an up-to-date and auditable log of all rule changes in compliance with governance and audit requirements.

• Periodic Tuning & Optimization
  • Perform regular back-testing and tuning of fraud detection rules based on evolving scam patterns, tactics, and trends (e.g., social engineering, mule account usage, malware/remote access fraud).
  • Analyze false positives and missed detections to refine thresholds and logic conditions.
  • Coordinate with FDS system vendors or internal tech teams for deployment and testing of rule updates.
  • Maintain card usage parameters (e.g., country, MCC, velocity limits) to optimize fraud controls without disrupting customer experience.
  • Apply and fine-tune fraud rules within the card authorization system to block high-risk or abnormal transactions.

• Data Analytics & Thematic Analysis
  • Conduct deep-dive analysis and identify fraud patterns across channels (IBMB, cards, payment rails, etc.).
  • Perform thematic reviews on high-frequency fraud incidents such as:
    • Impersonation scams
    • Account takeover
    • Mule layering schemes
    • Scam syndicate typologies
  • Generate insights to support operational decision-making and preventive controls.

• Dashboards & Regulatory Reporting
  • Develop and maintain analytics dashboards and visualizations to monitor fraud metrics, scenario performance, and alert trends.
  • Support reporting requirements to regulatory bodies, senior management, and interbank collaboration forums by providing data-driven insights.
  • Generate daily and monthly reports on card authorization decisions, fraud attempts, and performance of control rules.

• Product Monitoring Support
  • Ensure timely onboarding of new product codes and transaction types into the fraud detection system to support end-to-end monitoring.
  • Liaise with business and product owners to understand new offerings and evaluate associated fraud risks.
  • Ensure card fraud prevention practices comply with internal policies, network mandates (e.g., Visa, Mastercard), and regulatory requirements.

Qualifications

• Bachelor's Degree in Banking, Finance, Information Technology, or related field.

Years of Experience

• 2-4 years of experience in fraud analytics, risk management, data science, or a similar field.

Specific Skills/Knowledge and Certification Required

• Proficient in SQL, Excel, and at least one analytics or visualization tool (e.g., Power BI, Tableau).
• Knowledge of fraud detection systems, financial crime typologies, and regulatory requirements.
• Strong analytical thinking, attention to detail, and problem-solving skills.
• Experience working with fraud case management systems or detection platforms (e.g., RSAOutseer, other relevant systems).
• Understanding of banking products, payment ecosystems, and common scam vectors.