Fraud Detection in India: Rising Patent Momentum and a Nascent Startup Landscape

What it is

Fraud detection is the practice of identifying and blocking deceptive activities across transactions, user accounts, and digital systems. It combines rules-based logic, behavioral analytics, and machine learning to spot anomalies in real time or retrospectively, assigning risk scores that can trigger alerts, block actions, or request extra verification.

Modern systems ingest vast streams of data—from payment logs to biometric signals—and apply supervised models like Random Forest, XGBoost, and deep learning to distinguish legitimate from fraudulent behavior. Blockchain is also used to create tamper-proof audit trails, especially in supply chains and identity management.

Why it matters: as India's digital economy accelerates, fraud vectors multiply. The country's real-time payments infrastructure (UPI), e-commerce boom, and government digitization have made robust fraud detection a national priority, directly impacting consumer trust and financial stability.

The value chain

• Upstream – Data & Infrastructure: Sources of transaction data, user behavior logs, threat intelligence feeds, and cloud/on-premises infrastructure. Key global players include IBM and AWS; in India, telecom and banking data lakes feed national initiatives.
• Midstream – Fraud Detection Software & Platforms: AI/ML-powered analytics engines, rules platforms, authentication layers, and governance/risk/compliance (GRC) solutions. Global leaders: FICO, Signifyd, Feedzai, Elliptic, Transmit Security. This is where defensible IP and margins concentrate.
• Downstream – Integration & Deployment: System integrators, APIs, and platforms that embed fraud detection into business workflows—payment gateways, UPI apps, supply chain systems. Indian examples: PhonePe, Paytm, Google Pay, DHL Supply Chain.
• End-User Industries: Banks, insurers, e-commerce firms, healthcare providers, and government agencies that consume fraud detection to protect transactions and identities. Major Indian adopters: HDFC Bank, State Bank of India, Punjab National Bank, Canara Bank.

Where it's heading

Global and India-specific trends point to an arms race between fraudsters and defenders, with AI on both sides. The research brief highlights several shifts reshaping the space.

• AI and machine learning are becoming central to real-time fraud detection, enabling behavioral analytics and anomaly detection at scale (Entrust, Autodesk).
• Fraud-as-a-Service is rising, where criminals offer tools and services for fraud, increasing scale and sophistication (Entrust).
• Deepfake technology is increasingly used in biometric fraud attempts, now linked to 1 in 5 biometric fraud cases (Entrust).
• Blockchain is being combined with AI to create tamper-proof audit trails in supply chains, preventing counterfeit parts and invoice fraud (IJEDR Paper).
• Governments are launching national fraud risk indicators; India's Financial Fraud Risk Indicator (FRI), launched in May 2025, classifies mobile numbers by fraud risk and is integrated into banks and UPI apps (GASA).
• Within four months, the FRI helped prevent over 4.8 million fraudulent transactions, saving users more than ₹140 crore (US$15.8 million) (GASA).

The opportunity in India

India's fraud detection market is valued at USD 1.69 billion in 2025 and is projected to reach USD 8.86 billion by 2034, growing at a CAGR of 20.18%—faster than the global average—driven by digital payments and regulatory mandates (IMARC Group). Yet the startup landscape remains surprisingly thin on the surface.

Our data shows a sharp contrast: 115 patent-holding startups are active in fraud detection, but only 13 deep-tech companies explicitly reference the technology in their profiles. This suggests a large pool of innovators who may be building fraud detection capabilities within broader platforms (fintech, health-tech, gaming) rather than positioning as pure-play fraud detection firms.

The dominant patent sector is health-life-sciences, not BFSI, hinting at under-explored applications in insurance claims, pharma supply chains, and medical identity fraud. With the RBI mandating FRI adoption and UPI transaction volumes soaring, a dedicated fraud detection startup that can offer real-time, AI-native, API-first solutions for banks, fintechs, and e-commerce platforms could capture significant white space.

Funding data for the broader health-life-sciences sector shows 973 companies raised $2.58 billion, but fraud detection-specific funding is not isolated, indicating a potential capital gap for startups that explicitly tackle fraud as a core product.

India signal: patents, startups, capital

Our dataset maps 113 patents to fraud detection, with momentum described as rising—published filings are up even before the last two years fully publish, a strong signal of growing inventive activity.

We count 115 patent-holding startups in this space. The list includes a mix of companies and individual inventors: WinZO Games (3 patents, South Delhi), NISSI Software Systems (2 patents, Bengaluru Urban), Google (3 patents, Chennai), and multiple filings by individual inventors named Sanjeev Kumar across cities. This breadth indicates innovation is distributed, not concentrated in a few labs.

Only 13 deep-tech companies in our data explicitly reference fraud detection in their profiles. Examples include RAPTORXAI (Medak), CARAPAX Technologies (Thane), TrustLayerLabs (Bapatla), FINLOCK Technologies (South Delhi), and ZYNOVIQ Solutions (Chennai). Many more likely operate under adjacent labels like fintech, regtech, or cybersecurity.

Sector funding context: the health-life-sciences sector (dominant for fraud detection patents) has seen 973 companies raise a total of $2.58 billion, with a median raise of $1.0 million. Notable funded names include Enveda ($517M), Qure.ai ($130M), and SigTuple ($54.7M), though none are pure fraud detection plays. Dedicated fraud detection startups have yet to attract large disclosed rounds in our data.

In our data

Sources

• What Is Fraud Detection? | IBM ↗
• How Fraud Detection Works: Common Software and Tools ↗
• Fraud Detection Systems for Identity Verification: How Do They Work? ↗
• How manufacturers can use AI to stop supply-chain fraud ↗
• Fraud Detection In Supply Chain: An AI And Blockchain-Based Approach ↗
• Fraud Detection with AI in Supply Chains ↗
• Fraud Detection and Prevention Market Report 2025-2030, ... ↗
• Fraud Detection and Prevention Market Report 2026 ↗