FinTech Pact Aims to Remake Banking AI Without Costly Data Migration

PALO ALTO, CA & PUNE, INDIA – April 20, 2026 – A new strategic partnership between a Silicon Valley data innovator and an Indian technology powerhouse is set to tackle one of the biggest obstacles in financial services: leveraging artificial intelligence without getting bogged down by decades of legacy data. The Modern Data Company, creator of the DataOS® platform, has joined forces with Bajaj Tech.AI, the technology arm of Indian financial giant Bajaj Finserv Ltd., to accelerate the delivery of advanced data and AI solutions to banks and insurers across the United States and India.

The collaboration aims to combine The Modern Data Company’s novel “data operating system” with Bajaj Tech.AI’s extensive experience in enterprise-scale digital transformation. The partnership promises to help financial institutions modernize their data infrastructure and operationalize AI, not in years, but in weeks—a bold claim in an industry often paralyzed by complex, high-risk data migration projects.

The AI Modernization Imperative

Financial institutions worldwide are under intense pressure. On one side, nimble fintech startups, unburdened by legacy systems, are rapidly acquiring customers with slick, personalized digital services. On the other, customers themselves now expect instantaneous, intelligent, and seamless interactions. This has created an urgent need to adopt AI for everything from risk analytics and fraud detection to hyper-personalized customer experiences.

The demand is palpable in the world's largest financial markets. In the U.S., an estimated 65% of financial institutions are already actively deploying AI, with 42% planning to increase their AI investments by more than 50% by 2026. In India, the AI in BFSI (Banking, Financial Services, and Insurance) sector is projected to surge, with spending forecast to hit $9.2 billion by 2028. This growth is fueled by a national push for digitalization and financial inclusion.

However, this AI gold rush is hampered by foundational challenges. In both countries, executives point to fragmented data, entrenched data silos, and outdated core systems as primary barriers. Traditional solutions often require complex and costly “lift-and-shift” data migrations, a process so risky and expensive that it can stall innovation for years. This is the Gordian Knot the new partnership aims to cut.

A 'No-Migration' Approach to a Legacy Problem

The core of the partnership's technical proposition lies in DataOS, which The Modern Data Company markets as the world's first data operating system. Its key differentiator is a “no-migration” architecture. Instead of physically moving data from legacy mainframes, data warehouses, and disparate cloud environments into a single new location, DataOS creates a virtualized, unified data layer over the top of existing systems.

This approach, often discussed in the context of data fabric or data mesh architectures, allows an organization to connect, govern, and operationalize data wherever it resides. For a bank, this means data from a 30-year-old core banking system can be seamlessly and securely combined with information from a modern cloud-based CRM and third-party market feeds, all without a multi-year migration project.

“Financial institutions are under intense pressure to innovate with AI, enhance the customer experience, and meet evolving regulatory requirements, all while managing increasingly complex data ecosystems,” said Saurabh Gupta, president and CEO of The Modern Data Company. “By partnering with Bajaj Tech.AI, we are combining deep expertise with the power of DataOS to help financial institutions simplify data complexity, deliver business-ready data products, and accelerate AI adoption across the U.S. and India.”

Bridging Continents and Capabilities

While The Modern Data Company provides the technological key, Bajaj Tech.AI brings the deep industry knowledge and implementation muscle required to unlock its potential at scale. As a strategic division of the $116 billion Bajaj Finserv conglomerate, Bajaj Tech.AI possesses an intimate understanding of the financial services landscape, not just as a technology vendor but as part of a major financial institution itself.

This partnership leverages a powerful synergy: cutting-edge U.S. data technology combined with the proven, large-scale implementation capabilities of India's formidable IT services sector. Bajaj Tech.AI will integrate DataOS into its transformation programs, using it as the foundational layer to help its clients accelerate AI use cases and modernize their data platforms.

“We see tremendous opportunity for financial institutions to unlock measurable value from their data investments, but legacy architectures and fragmented systems often slow progress,” said Ashish Panchal, Managing Director and CEO of Bajaj Finserv Direct Ltd. “Our partnership with The Modern Data Company will enable us to offer our clients a modern, scalable data foundation that helps accelerate AI adoption, strengthen governance and deliver measurable impact in weeks instead of years.”

Navigating the Gauntlet of Governance and Compliance

For the BFSI sector, innovation is always tethered to security and regulation. The promise of AI is matched only by the risks of data breaches, algorithmic bias, and non-compliance. This is where the partnership places another significant bet, focusing on robust, automated governance.

DataOS is built with features like “policy-as-code” governance and “zero-trust” data access, which are designed to meet the stringent demands of financial regulators. This is critical in a global environment where bodies like the U.S. Securities and Exchange Commission (SEC) and the Reserve Bank of India (RBI) are intensifying their scrutiny of AI usage. The SEC applies existing rules on supervision and recordkeeping to AI tools, while the RBI has developed a comprehensive framework for ethical AI, emphasizing trust, fairness, and accountability.

The partnership’s solution aims to embed these compliance requirements directly into the data architecture, automating the enforcement of data access policies and providing clear data lineage and observability. This helps ensure that as financial institutions accelerate their AI initiatives, they are building on a foundation of discoverable, contextual, and trustworthy data that can stand up to regulatory audits.

Through this collaboration, which includes joint solution development and coordinated go-to-market efforts, the two companies are providing a framework intended to unify enterprise data and drive innovation securely. As financial services organizations in two of the world's most dynamic markets navigate the complexities of digital transformation, this alliance offers a compelling new path forward.