Fraud Investigation Analytics Lead

• Job Responsibilities
• Data Analytics & Model Enhancement

Advanced Fraud Analytics

Conduct deep-dive data analytics on the PayLater portfolio to detect shifting behavioral patterns and transaction trends among high-risk or fraudulent users, directly contributing to the optimization of fraud detection models.

Investigation & Loss Mitigation

Incident Investigation & Countermeasures

Analyze complex TPayLater fraud cases at scale to design actionable countermeasures, implement robust fraud rules, and recommend product-level fixes.

Financial Recovery

Execute strategic asset recovery actions to minimize actual or potential financial losses while actively supporting Gross Booking Value (GBV) growth.

Process & Framework Optimization

Framework Improvement

Continuously evaluate and refine early investigation frameworks across the PayLater ecosystem, payments, and the broader platform to enhance operational efficiency.

Compliance, KYB & Stakeholder Management

Regulatory & External Relations

Serve as the primary point of contact for fraud-related inquiries, delivering precise and timely responses to regulators (OJK), law enforcement agencies, and internal product teams.

Risk Mitigation (KYB/KYE)

Execute rigorous Know Your Business (KYB) checks for merchants to secure the lending space, and manage internal Know Your Employee (KYE) reporting compliance.

Intelligence & Awareness

Fraud Intelligence

Perform proactive intelligence-gathering to uncover emerging fraud modus operandi and preemptively intercept risks.

Customer Awareness

• Partner with social media and cross-functional teams to design and drive customer-facing fraud awareness initiatives.
• Job Requirements

Have minimum 7 years experience in Fraud Investigation/Management in unsecured personal loan/BNPL. Some experience in card payments fraud and/or chargeback handling is highly appreciated.

Proficient understanding of OJK regulations, fraud landscape in BNPL, and with credit-related fundamentals.

Fluency in data analytics and comfortable in presenting findings and patterns backed with data; detail oriented and vigorous pattern-recognition; able to move fast with imperfect data.

• Bachelor’s degree in any major, preferably in STEM from a reputable university with minimum GPA of 3.5 on a 4.0 scale.
• Demonstrated experience working horizontally cross-functions and vertically.
• Proven track record building and owning P&L; comfortable with end-to-end accountability target-setting to variance resolution.
• Good interpersonal and communication skill, comfortable translating between technical and business terms.
• Fluency in English both in written & verbal.
• Honest and ethical with high levels of integrity and confidentially.
• Comfortable with ambiguity and iterative approach.