AI strategy and governance · Bengaluru
We help fintech companies in Bengaluru choose the AI uses worth funding, then set the rules your compliance lead and partner bank can check before anything reaches customers.
Most fintech teams in Bengaluru did not wait for permission. Engineers have wired language models into support replies and know your customer checks, and marketers draft campaign copy with whatever tool is open in the browser. Some of that work touches customer financial data, and nobody has reviewed where that data goes.
The pressure usually arrives from outside. A partner bank asks how an AI model affects onboarding decisions. A buyer in Europe or the US sends a security questionnaire with a section on AI, and a deal that looked strong after the demo sits in compliance review for weeks. Your compliance lead cannot approve what they cannot see. So the pilots in underwriting or fraud stay small and never reach the volume that would show a return.
Payments, lending, wealth and software sold to banks each answer to different rules and different buyers, so one generic policy does not fit. Teams here are technically strong and careful with cost, and the first instinct is often to write the rules in-house. Writing the document is the easy part. The slower work is choosing which uses deserve funding and naming who answers for each one when a regulator or customer asks.
A Bengaluru firm sells compliance software to banks in the Middle East and wants AI agents to handle first-line support and back-office checks. Its buyers' risk teams ask how each agent reaches a decision and where its actions are logged. With an inventory, a risk register and named owners in place, the sales team can answer the AI section of a security review from a written record, and the agent pilot has an owner who can approve its next step.
A lending app pays heavily for installs, yet most new users drop out during identity verification and never fund an account. The product team wants AI to guide users through know your customer steps and to flag fraud, but the partner bank and the compliance lead hold back. A business case for each use, measured against activation and conversion to funded account, sets the order. The policy states which customer data the model may see and when a person must approve, so compliance can sign off on a contained first rollout.
The Reserve Bank of India (RBI) oversees banks, payments, lending and NBFCs, the non-banking financial companies. If your product touches securities markets or investment advice, the Securities and Exchange Board of India (SEBI) applies. The Digital Personal Data Protection Act, 2023 governs how you collect and use the personal data of people in India. Its obligations are being phased in, and that shapes which data an AI tool may see. The Information Technology Act, 2000 covers electronic records, and CERT-In covers the reporting of cybersecurity incidents.
Your risk register and approval rules are mapped to the rules that apply to your product, to your partner bank's requirements and to your customer contracts. Because we are not a law firm, we work alongside your lawyers on how each rule is read.
We work with fintech companies in Bengaluru from Mumbai. At founder-led firms the founder is usually the buyer, and decisions can move quickly. At larger firms that need sign-off from a global headquarters, we write the plan so it can be approved by people who were never in the room. Many engagements begin with a smaller first step, such as the inventory, and the wider scope is agreed after that.
Yes. Bank buyers abroad often send security reviews that ask how AI decisions are made, checked and logged. A risk register, approval rules and named owners give your sales team a written answer to that section, mapped to the contracts and rules each buyer cares about, so the review has less to stall on.
Your engineers can write a policy, and many teams here weigh that first. The slower part is choosing which uses to fund and agreeing who owns each one across product, risk and compliance. Before Burraq Quantum was formed, our founder architected an AI governance platform that received the GEC Award 2025: Innovative Vendor for AI Governance and Compliance. We work alongside your engineers so the rules fit the systems they run.
No, we are not a law firm. We map your AI policy, risk register and approval rules to the rules that apply to your product, and your lawyers give the legal opinion. Our part is the business case for each use, the controls and the named owners that make those rules work on real tasks.
AI strategy and governance for Riyadh fintech companies: the AI uses worth funding, and rules mapped to SAMA, CMA, PDPL and NCA controls.
An AI inventory, funded uses and clear rules for Web3 teams in Dubai, mapped to the regulators and platform policies that apply to your license.
Start here
A 30-minute call to see whether we can really move your numbers. You leave with a clear next step, even if we never work together.
The diagnostic
Tell us what you want to achieve and where things stand today. We read every message ourselves and reply within two working days.
Q
