Senior Product Manager (Fraud)

Ayasdi

Ayasdi

Accounting & Finance, Product

India · Bengaluru, Karnataka, India

Posted on Apr 28, 2026

Job Description

Job Title: Senior Product Manager – Fraud (AI-First)

Company: SymphonyAI Financial Services
Location: Bangalore, India (Hybrid)

Overview

SymphonyAI Financial Services is seeking a Senior Product Manager (AI First) to define and build a market-leading fraud platform used by banks, insurers, payment providers, and gaming companies to detect, prevent, and manage fraud and financial crime at scale.

This role is for a hands-on, deeply technical, domain-fluent product leader who understands that modern fraud is no longer a rules problem — it is a real-time decisioning, orchestration, and learning problem spanning detection, prevention, investigation, customer experience, and regulatory defensibility.

You will own the end-to-end fraud product strategy, from real-time risk assessment and adaptive decisioning through investigation, recovery, and continuous learning. You will work at the intersection of AI, real-time systems, financial crime, and customer experience, and help define how fraud decisions are made across industries.

This is not a maintenance role.
This is a category-shaping role.

What You Will Own

You will be accountable for building a fraud product that:

  • Outperforms incumbents on accuracy, speed, and explainability
  • Scales across multiple verticals with different fraud economics
  • Balances loss prevention, customer friction, operational cost, and regulatory expectations
  • Evolves continuously as fraud tactics change

Key Responsibilities

Product Vision & Strategy (Category Leadership)

  • Define and continuously refine the long-term product vision and multi-year roadmap for SymphonyAI’s fraud platform.
  • Articulate a clear AI-first and Agentic AI strategy for fraud, spanning:
    • Real-time scoring and decisioning
    • Adaptive controls and step-up actions
    • Alert generation, suppression, and prioritization
    • Automated and assisted investigations
    • Recovery, reimbursement, and learning loops
  • Position the fraud product as a platform, not a point solution — extensible across channels, geographies, and industries.
  • Translate emerging fraud typologies, regulatory changes, and customer needs into differentiated product capabilities.
  • Define how fraud integrates with the broader financial crime and risk ecosystem (AML, KYC/CDD, sanctions, investigations, customer risk, entity resolution).

Domain & Customer Leadership (Multi-Vertical Fraud Expertise)

  • Act as a trusted domain expert for customers across:
    • Banking & Payments: cards, wires, ACH, RTP, instant payments, digital banking, account takeover, scams.
    • Insurance: claims fraud, application fraud, policy abuse, first-party fraud.
    • Gaming & Digital Platforms: bonus abuse, multi-accounting, collusion, bot-driven fraud, identity abuse.
  • Deeply understand and shape fraud operating models, including:
    • Real-time vs post-event decisioning
    • Alert triage and prioritization
    • Analyst workflows and investigation quality
    • Customer communication and resolution
    • Chargebacks, claims, recovery, and reimbursement
    • QA, audit, governance, and regulatory oversight
  • Engage directly with fraud leaders, operations heads, risk executives, and product teams at Tier 1 and Tier 2 institutions to validate strategy and execution.
  • Maintain strong awareness of global regulatory and network expectations (e.g., Reg E, PSD2/PSR, APP reimbursement regimes, card network rules, consumer protection and explainability requirements).

AI & Agentic AI Productization (Best-in-Class Execution)

  • Partner with AI/ML and data science teams to deliver state-of-the-art fraud capabilities, including:
    • Real-time and near-real-time risk scoring
    • Behavioral, device, identity, and network-based detection
    • Alert clustering, suppression, and dynamic prioritization
    • Agent-driven evidence gathering across internal and external data sources
    • AI copilots for fraud analysts (recommended actions, summaries, decision rationales)
  • Define and operationalize Agentic AI patterns for fraud, such as:
    • Autonomous resolution of low-risk events
    • Adaptive step-up authentication and control selection
    • Proactive scam detection and customer intervention
    • Continuous tuning driven by outcomes, feedback, and emerging threats
  • Own the balance between innovation, explainability, human oversight, and regulatory defensibility.
  • Ensure all AI-driven decisions are transparent, auditable, and production-safe.

Platform, Architecture & Extensibility

  • Collaborate with UX, platform and engineering teams to ensure the fraud product is built on:
    • Real-time decision engines and streaming architectures
    • Configurable workflows and decision orchestration
    • Rich data models ontology and entity resolution
    • APIs and integration points for partners and customers
  • Enable customers to configure, extend, and evolve fraud strategies without vendor dependency.
  • Support complex enterprise needs: high throughput, low latency, multi-tenant SaaS, data residency, permissions, and global deployments.

Product Execution & Delivery

  • Translate strategy into clear, prioritized roadmaps, epics, and user stories with measurable outcomes.
  • Lead discovery, backlog refinement, sprint planning, and release execution with engineering, UX, and data science.
  • Drive the full product lifecycle — from concept to scaled adoption.
  • Partner with UX to deliver best-in-class analyst and operator experiences, including:
    • Real-time dashboards and queues
    • Alert and case views
    • Investigation timelines and evidence workspaces
    • Decisioning, overrides, and controls
    • Management reporting and governance tooling

Go-To-Market & Commercial Impact

  • Partner with Sales, Marketing, and Customer Success on strategic deals, RFPs, workshops, and demos.
  • Own product packaging, pricing input, ROI narratives, and competitive differentiation.
  • Support Marketing with clear positioning and thought leadership on fraud, scams, and AI-driven prevention.
  • Define and track success metrics, including:
    • Fraud loss reduction
    • False positive and customer friction reduction
    • Analyst productivity
    • Recovery and reimbursement performance
    • AI adoption and measurable impact

Ideal Candidate Profile

Experience

  • 7+ years of product management experience in fraud, risk, payments, fintech, regtech, or financial services.
  • Deep hands-on experience with fraud detection, prevention, and investigation in at least one major vertical; exposure to multiple is a strong plus.
  • Proven experience building AI-powered, real-time, enterprise-scale products.
  • Track record of driving platform products, not just features, from concept to adoption.
  • Experience working with large banks, insurers, gaming companies, or global platforms.

Skills & Competencies

AI-First & Systems Thinking

  • Ability to reason from first principles about decisioning, orchestration, and learning systems.
  • Comfort translating ML, LLMs, and decision engines into real-world product behavior.

Fraud & Risk Depth

  • Strong understanding of fraud economics, trade-offs, and customer impact.
  • Fluency in explainability, governance, and operational controls.

Product Leadership

  • Proven ability to set direction, make hard trade-offs, and lead cross-functional teams.
  • Data-driven, outcome-oriented decision maker.

User & Operator Empathy

  • Passion for building products that reduce friction while improving outcomes.
  • Ability to simplify complex workflows without oversimplifying risk.

Communication & Influence

  • Clear, credible communicator with executives, customers, and technical teams.
  • Comfortable representing the product externally with customers and partners.

Nice to Have

  • Experience with real-time decisioning, streaming systems, or payments infrastructure.
  • Exposure to graph/network analytics, identity, device intelligence, or behavioral biometrics.
  • Familiarity with Agentic AI frameworks or autonomous workflows.
  • Background in data platforms or distributed systems.

What Success Looks Like (First 12–18 Months)

  • A clear, bold fraud product roadmap aligned with SymphonyAI’s platform strategy.
  • Delivery of step-change improvements in fraud accuracy, speed, and explainability.
  • Strong adoption by flagship customers across multiple verticals.
  • Demonstrated, quantified customer ROI and competitive wins.
  • Recognition of SymphonyAI as a serious, modern fraud platform, not just a vendor.

Why SymphonyAI

  • Build the next generation of fraud and financial crime decisioning platforms.
  • Work on mission-critical, real-time systems that directly impact customers and institutions.
  • Shape a category alongside senior leaders in product, AI, and financial crime.