Fraud Investigation Analytics Lead

Traveloka

Banten

On-site

IDR 360,000,000 - 600,000,000

Full time

14 days+

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Job summary

Traveloka is seeking a seasoned Fraud Analytics professional to strengthen its PayLater fraud detection and losses mitigation framework. You will analyze large-scale fraud cases, design countermeasures, and partner with product and operations teams to implement data-driven improvements.

The role requires deep domain knowledge of BNPL, strong data analytics skills, and the ability to translate complex findings into actionable business outcomes while maintaining high integrity and cross-functional

Qualifications

  • 5-7 years’ experience in Fraud Investigation/Management in unsecured personal loan/BNPL.
  • Proficient understanding of OJK regulations, BNPL fraud landscape, and credit fundamentals.
  • Fluency in data analytics and presenting data-driven findings; detail oriented and vigorous pattern recognition.

Responsibilities

  • Analyze PayLater fraud cases at scale to design actionable countermeasures and fraud rules.
  • Support asset recovery actions to minimize losses while backing GBV growth.
  • Refine early investigation frameworks to improve efficiency across PayLater, payments, and platform.

Skills

Data analytics
Detail orientation
Communication skills
Integrity & confidentiality
Ambiguity tolerance
Fast decision making

Education

Bachelor’s degree (STEM preferred, GPA 3.5/4.0)

Job description

Job Description

Job ID: MJ000231

Responsibilities
Data Analytics & Model Enhancement
  • Conduct deep‑drive 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
  • Analyze complex TPayLater fraud cases at scale to design actionable countermeasures, implement robust fraud rules, and recommend product‑level fixes.
  • Execute strategic asset recovery actions to minimize actual or potential financial losses while actively supporting Gross Booking Value (GBV) growth.
Process & Framework Optimization
  • Continuously evaluate and refine early investigation frameworks across the PayLater ecosystem, payments, and the broader platform to enhance operational efficiency.
Compliance, KYB & Stakeholder Management
  • 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.
  • 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
  • Perform proactive intelligence‑gathering to uncover emerging fraud modus operandi and preemptively intercept risks.
  • Partner with social media and cross‑functional teams to design and drive customer‑facing fraud awareness initiatives.
Requirements
  • Have 5‑7 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 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 confidentiality.
  • Comfortable with ambiguity and iterative approach.
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