About MobiKwik

MobiKwik is India's leading Digital Financial Services platform and largest Digital Wallet, trusted by over 167 million users and 4.4 million businesses. As a pioneer in the Fintech space, MobiKwik offers digital payments, credit and investments, with a mission to democratize financial inclusion. Recently, MobiKwik achieved a significant milestone with its Initial Public Offering (IPO), marking a new chapter in its journey of innovation and growth.

About the Role

We are looking for a fraud and risk professional with strong data analytics skills to build and scale a data-driven fraud, AML and risk intelligence function. This role sits at the intersection of fraud operations, data science and AI. You will own fraud detection and prevention strategy, build Early Warning Systems (EWS), risk models and scorecards, and enable real-time, automated risk monitoring across the organization.

Key Responsibilities

1. Fraud Detection, Prevention & Investigation

- Lead the development and execution of fraud detection, prevention and investigation strategies.
- Implement systems and controls to monitor transactional activity and detect anomalies.
- Analyse fraud trends, investigate root causes and drive process improvements.
- Ensure timely resolution of fraud alerts and incidents, including customer recovery processes where applicable.
- Collaborate with product, operations, tech and customer experience teams to embed fraud controls into products and journeys.
- Build and manage a high-performing fraud operations team.

2. Risk Modeling, EWS & Scorecards

- Design and build Early Warning System (EWS) models using regression (linear, logistic) and classification techniques (tree-based and ensemble methods).
- Identify leading risk indicators across transactions, customer behavior and operational metrics, and define thresholds, triggers and alert logic.
- Build risk scorecards for customer risk, transaction risk / fraud signals and operational risk.
- Run simulations, scenario analysis and stress tests on models and thresholds.




- Develop anomaly detection frameworks, and continuously refine models using performance data and feedback loops.

3. Anti-Money Laundering (AML) & Compliance

- Oversee the AML compliance program in line with applicable regulations.
- Manage transaction monitoring systems, sanctions screening and escalation of suspicious activity.
- Lead the filing of Suspicious Transaction Reports (STRs) or equivalent with regulators.
- Update and enforce AML policies and procedures, conduct AML risk assessments, and coordinate internal audits and regulatory reviews.

4. Data, Automation & AI

- Write effective SQL queries on large transactional and operational datasets.
- Build and manage data pipelines (ETL / ELT) for real-time and batch processing, ensuring data quality and scalability.
- Build and enhance risk monitoring dashboards with near real-time visibility, automated alerts and exception reporting.
- Work hands-on with Claude and other LLMs for risk signal extraction from unstructured data and incident summarization and classification.
- Build agentic AI workflows for automated alerts, intelligent monitoring and escalation, ensuring secure and compliant AI use.

5. Law Enforcement & Stakeholder Engagement

- Liaise with law enforcement agencies, including police and the Ministry of Home Affairs (MHA), and with partner banks to support fraud investigations and legal proceedings.
- Translate business problems into scalable analytical solutions for ERM, ORM, Product and Tech teams.
- Regularly report fraud KPIs, emerging risks and incident summaries to senior leadership.

What You'll Bring Qualifications & Experience

- B.Tech / B.E. (Computer Science, IT,



Electronics, Mathematics or a related field) preferred. Candidates with a degree in Finance, Law, Business or Statistics and strong analytics skills are also welcome. Master's degree is a plus.
- 710 years of experience in fraud prevention, risk or AML, preferably in fintech, payments, financial services or e-commerce.
- Proven experience leading teams and working with cross-functional stakeholders.
- Deep understanding of fraud typologies, AML regulations and financial crime frameworks.
- Certifications such as CAMS, CFE or CFCS are preferred.

Technical Skills (Mandatory)

- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, etc.).
- Advanced SQL skills.
- Hands-on experience in predictive modeling, scorecard development, anomaly detection and scenario analysis.
- Experience building data pipelines (ETL / ELT frameworks).
- Experience implementing and managing fraud / AML systems and tools.

AI & Emerging Tech

- Hands-on experience with Claude or similar LLMs.
- Understanding of agentic AI and workflow automation.

Key Competencies

- Strategic and data-driven mindset.
- Strong analytical and investigative skills.
- Excellent communication and stakeholder management.
- High integrity and sound judgment.
- Ability to thrive in a fast-paced, evolving environment.

How Success Is Measured

- Accuracy and effectiveness of EWS and fraud models (precision, recall, early detection).
- Reduction in fraud losses and faster resolution of alerts and incidents.
- Performance of risk scorecards and predictive models.
- Reliability and scalability of data pipelines and monitoring dashboards.
- Level of automation in risk detection and reporting.

Why MobiKwik?

- Build a next-gen, AI-driven fraud and risk analytics function.
- Work on high-scale fintech data and real-time risk problems.
- High ownership at the intersection of fraud, data science and AI.
- Progressive career, reward and recognition driven culture, and lean hierarchy.

📌 Manager / Senior Manager - Fraud & Risk Analyst (Gurugram)
🏢 Mobikwik
📍 Gurugram