- Santriya Technologies is seeking an AI Fraud & Financial Crime Analyst to investigate fraud and financial-crime alerts using AI/ML risk signals, transaction data and documented typologies while retaining human accountability for customer-impacting decisions and escalation.

- Product & documentation operating model: You will be assigned one or more company products, client solutions or operational services.

- The approved product documentation, SOPs, policies, process maps, knowledge articles, release notes, controls, scripts and AI runbooks are the source of truth.

- Use only approved enterprise AI tools to retrieve, summarize, draft, classify, prioritize or automate work.

- Validate material AI outputs against current documentation and authoritative system data, record exceptions, and escalate conflicts or missing guidance.

- Do not invent product features, prices, customer entitlements, engineering limits, regulatory positions or safety instructions.

Key Responsibilities:

- Review alerts, cases, customer activity, device/payment signals and related evidence.

- Use AI to summarize complex activity, link entities and surface relevant typologies, verifying every material fact in source systems.

- Differentiate model score from evidence and document rationale for closure, restriction or escalation.

- Apply AML, sanctions, fraud, scam and customer-protection procedures relevant to jurisdiction and product.





- Escalate suspicious activity and prepare explicit investigation narratives for authorized reporting teams.

- Identify false-positive drivers, emerging fraud patterns and control gaps and feed them to model/rules teams.

- Observe strict confidentiality, access and need-to-know controls.

- Participate in QA, calibration and post-incident review.

- AI-enabled ways of working:

- Use approved GenAI copilots, enterprise search/RAG, analytics and workflow agents to reduce repetitive work and improve decision preparation.

- Keep prompts, outputs and automated actions within approved data-access, confidentiality and retention rules.

- Correct inaccurate summaries, classifications or recommendations before they become customer, operational or system records.

- Feed recurring AI errors, knowledge gaps and process friction into product, documentation and control improvement.

- Human accountability: AI is a copilot, not the accountable decision-maker.

- The role holder remains responsible for judgement, quality, privacy, security and appropriate escalation.

- Credit, fraud blocking, legal/regulatory, financial advice, safety-critical, clinical, employment and other high-impact decisions must follow delegated authority and required human review.

- Success Measures:
- Investigation quality and timeliness improve

- False positives reduce without missed risk

- Decision rationale is audit-ready

- Emerging threats are fed back into controls

📌 AI Fraud & Financial Crime Analyst (Chennai)
🏢 Santriya Technologies
📍 Chennai