Mumbai-based regulatory technology startup Data Sutram has raised US$9 million in a series A funding round co-led by B Capital and Lightspeed.

The funding will support the expansion of its AI-powered fraud detection and compliance platform into new sectors and international markets.

Founded in 2019, Data Sutram offers financial institutions tools to detect fraud, ensure regulatory compliance, and minimize non-performing assets.

The platform analyzes over 110 million identities and uses a proprietary “Trust Score” to evaluate fraud risks based on digital footprints.

🔗 Source: YourStory

🧠 Food for thought

1️⃣ RegTech funding accelerates as compliance becomes a competitive advantage

Data Sutram’s $9 million Series A funding reflects a broader surge in regulatory technology investment, with the RegTech sector having raised $2.1 billion in 2018 and $1.4 billion in just the first quarter of 2019 alone 1.

This investment momentum comes as regulatory compliance tools transition from being viewed as necessary cost centers to strategic business enablers that can improve customer experience and security 2.

Financial institutions are particularly motivated to invest in these technologies as recent court rulings limiting federal regulators’ powers and potential policy reversals from new administrations create a more complex compliance landscape requiring greater agility 3.

The move beyond traditional banking into insurance, gaming, and cryptocurrency markets aligns with the industry-wide trend of RegTech expansion, as companies like Data Sutram seek to apply their compliance frameworks to multiple sectors facing similar regulatory challenges.

2️⃣ AI-powered fraud detection emerges as a critical investment area

Data Sutram’s focus on AI-driven fraud detection places it in one of the fastest-growing segments of financial technology, with AI vendors specializing in fraud and cybersecurity capturing approximately 26% of total funding in the banking AI sector 2.

The expansion into insurance fraud detection represents a strategic opportunity, as insurance fraud costs the U.S. economy approximately $122 billion annually, with AI technologies potentially saving the industry between $80-160 billion by 2032 through enhanced detection capabilities 4.

Real-time processing of customer identities across digital footprints—like Data Sutram’s system scanning millions of data points from government, telecom, ecommerce, and payment sources—exemplifies the shift from traditional fraud detection to advanced AI technologies that can analyze multiple data streams simultaneously 2.

Data Sutram’s “Trust Score” approach parallels the broader industry movement toward multimodal technologies that integrate diverse data types to enhance fraud detection accuracy. This capability is particularly valuable as soft fraud (inflating legitimate claims) accounts for 60% of all fraud incidents 4.