Capital Markets
AI for Investment Banking: Governed Deployment for IB, M&A, and Capital Markets Workflows
Governed AI deployment for investment banking workflows, pitch books, due diligence, and research summarization, with model risk management built in.
problem
Why Banks Are Stuck at Pilot Stage
Most investment banks have run an AI pilot on pitch book drafting or research summarization, and most of those pilots never reach production because nobody owns the model risk management sign-off, the MNPI data-handling review, or the audit trail a compliance team needs before letting AI touch deal-team work.
usecases
Where AI Moves the Needle
Pitch Books, Comps, and CIM Drafting
Drafting first passes at comparable-company analysis, pitch book sections, and confidential information memoranda, with a banker reviewing and finalizing rather than starting from a blank page.
Due Diligence and Data Room Review
Summarizing and flagging items across a large data room faster than a junior team can manually review every document, with citations back to the source document for every flag.
Research Summarization, Earnings Calls, and Deal-Team Copilots
Summarizing earnings call transcripts and equity research into a deal-team-ready brief, and giving deal teams a copilot grounded in the firm's own research and deal history rather than a generic chatbot.
governance
The Governance Layer That's Actually Missing
Model Risk Management and SR 11-7/SR 26-2 Alignment
Every AI system touching deal-team work needs to sit in a model inventory with a risk tier, validated the way our model risk management under SR 26-2 practice describes, not deployed informally because a team lead liked a demo.
Data Security and MNPI Controls
Material non-public information needs the same access controls and audit logging around an AI system that it gets around any other deal-room system, so a pilot doesn't quietly become an information-barrier problem.
differentiation
Why Off-the-Shelf Copilots Fall Short
A generic AI copilot sold to every industry doesn't ship with MNPI-aware access controls or a model risk validation framework built for a Fed-regulated institution. Closing that gap after the fact is slower and more expensive than building it in from the first pilot.
engagement
How Kriv AI Deploys This
We bring the same governance methodology we use across healthcare and insurance deployments to capital markets: a scoped pilot with model risk management, MNPI-aware data handling, and audit logging built in from day one, using Claude via our Anthropic partnership as the underlying model where a generative layer is appropriate. See our engagement pricing for how a scoped pilot is structured.
Straight answers
Frequently asked questions about AI for Investment Banking: Governed Deployment for IB, M&A, and Capital Markets Workflows
What AI use cases actually work in investment banking today?
Pitch book and CIM drafting, due diligence and data room review, and research summarization for deal teams, each with a banker reviewing and finalizing the output rather than an AI system operating unsupervised.
Will AI replace investment banking analysts?
No, and any vendor claiming otherwise should raise a flag. AI in this context drafts a first pass and summarizes faster than manual review, but a banker still reviews, judges, and finalizes every deliverable.
How does model risk management apply to generative AI in banking?
Any AI system touching deal-team work needs to sit in a model inventory with a risk tier and a validation approach aligned to the Federal Reserve's SR 26-2 guidance, the same rigor traditional models get.
How is MNPI handled when AI touches deal-room data?
The same access controls and audit logging that govern any other deal-room system need to extend to the AI layer, so material non-public information doesn't create an information-barrier gap.
Does Kriv AI have a named investment bank as a client?
We bring the same governance methodology proven across our healthcare and insurance deployments to capital markets workflows. We don't claim a named bank client on this page, and we won't invent one.
How do we scope a pilot?
Book a discovery call to discuss which workflow (pitch books, diligence, research) makes sense as a first governed pilot, and see our pricing page for engagement structure.
Talk to the team that would do the work
Bring your requirements to a working session with the person who'll actually deliver.
Book a Discovery Call