AI & automation for finance
Automate the paperwork, keep the compliance
Onboarding, document processing, reconciliation and reporting - automated with the security, data boundaries and audit trails that a regulated business needs. AI you can actually adopt.
Where I help
What automation looks like in banking & finance
Client onboarding & KYC
Automate document collection, checks and data entry so onboarding is faster without cutting compliance corners.
Document processing
Extract and route data from statements, applications and forms with AI - reviewed by a human where it counts.
Learn moreReconciliation & reporting
Automated reconciliation and report generation that replaces the weekly spreadsheet ritual.
Secure by design
Private models, data boundaries and full audit trails so adoption survives a security review.
Learn moreProblems I solve
The specific pains in banking & finance
Finance is drowning in documents and checks, and 'AI is too risky' is the usual reason nothing changes. Done properly - private models, strict data boundaries, full audit - it isn't risky, and the payback on automating this paperwork is enormous. Here's where it hits.
The problem
Client onboarding and KYC is slow because documents are collected and checked by hand.
How I solve it
Automated intake collects and validates documents, pre-fills data across systems and chases what's missing - onboarding drops from days to hours without weakening checks.
The problem
Analysts spend hours re-keying data from statements and applications into core systems.
How I solve it
AI reads the documents and extracts the data, with a human approving the results - accurate, faster and fully logged.
The problem
Month-end reconciliation and reporting is a manual grind prone to error.
How I solve it
Automated reconciliation matches transactions across systems and generates reports on schedule, so month-end stops being a scramble.
The problem
Leadership won't approve AI over data-security fears.
How I solve it
A secure implementation - private or self-hosted models, documented data boundaries, access control and audit - gives the benefits while keeping data inside your walls, so it passes review.
Built with people who do the work
Your sector, your systems, your outcome
Every project starts with how your business actually runs - not a generic template. No preferred vendor, no lock-in: I tell you honestly what's worth building and then build it.
Frequently asked questions
Done properly, yes. With private or self-hosted models, strict data boundaries, access controls and audit logging, you get the benefits without your data leaving your environment.
That's the whole point of the secure-implementation approach: governance, access control and audit are designed in from day one so it stands up to scrutiny.
Yes - document collection, validation, data entry and chasing can all be automated while keeping the actual risk decisions with a human.
Every step is validated and logged with a full audit trail, so results are both accurate and provable to an auditor.
No. AI can run on private or self-hosted infrastructure so sensitive data never leaves your environment or trains an external model.
I build it. Strategy and execution come from one person - I map what's worth doing, then make it and hand it over documented, so you get a working system, not a report.
That's the default. I build around your existing systems wherever possible rather than forcing a costly rip-and-replace.
No preferred vendor. I recommend and build with whatever gets you the outcome, and I'll tell you honestly when you need less software, not more.
With a first call and, for larger work, a short readiness assessment that maps where automation pays off. You keep the roadmap either way.
I quote per project once the scope is clear, so you know the number before anything starts - a fixed-price assessment, a defined build, or an ongoing retainer.