In BFSI the question is usually framed as funding, but the real constraints are regulatory. Here’s an honest read on both. (dgm implements osFoundry, a separate company’s platform — dgm is an independent integration partner, not osFoundry, and not a funding advisor. General information, not professional, legal or financial advice.)

The funding reality

There is no dedicated scheme that funds banks, NBFCs, financial-services firms or insurers to adopt AI. Investment is corporate and VC-driven. India’s AI-in-BFSI market is growing fast — reported at strong double-digit CAGR — but that’s market momentum, not a grant. BFSI firms adopting AI generally fund it themselves.

What actually shapes BFSI AI: regulation

For BFSI, the deciding factors are compliance and data control, not funding:

  • DPDP Act — personal-data obligations.
  • RBI — data localisation for payment and financial data (store in India).
  • SEBI Regulation 16C — entities are solely responsible for AI/ML outputs in securities markets.
  • IRDAI — bias testing and explainability expectations in insurance.

This is why BFSI AI demands auditable, self-hostable deployment — see AI for BFSI and compliance AI.

GIFT City

GIFT City’s IBM watsonx cluster offers financial firms a sandbox and PoC support — an infrastructure facility, not an adoption subsidy. It can lower the barrier to experiment, but doesn’t fund your own deployment.

Where dgm fits

dgm helps BFSI firms adopt AI compliantly by implementing osFoundry — model-neutral and self-hostable for data control and auditability aligned to RBI/SEBI/IRDAI expectations — for a transparent $399 assessment and $3,999/month (INR approximate; 18% GST domestic). We don’t provide funding; we make compliant adoption practical.

General information, not professional, legal or financial advice. Confirm regulatory obligations with qualified advisors.