AI for Banking & Professional Services

Automate the paperwork without losing the audit trail.

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Regulated finance and client delivery run on documents, approvals and evidence. Orhan reads the documents, applies your own rules, routes what needs a person to the right person, and records who approved what and when — so the efficiency does not cost you the trail.

Signs you need it

• Onboarding and KYC packs are checked by hand, so the queue grows whenever volume does
• The same client data is re-keyed between the CRM, the core system and the engagement file
• Approvals stall because nobody can see where a request is sitting or who is holding it
• An earlier automation project broke the first time a document format changed, and trust never recovered

Use cases

• Document intake and checking: Onboarding packs, statements, invoices and contracts read, checked against your own rules, and flagged where something is missing or inconsistent.
• Governed approvals: Thresholds, four-eyes checks and escalation written into the workflow, with a complete record of who approved what and on what evidence.
• Policy and precedent answers: Staff ask a policy, product or precedent question and get an answer cited to the controlling document, limited to what they are cleared to see.
• Exception and risk surfacing: Patterns that merit a human look brought forward early, with the evidence attached, instead of discovered in a quarterly review.

What you get

• A mapped, costed workflow that states plainly which steps should and should not be automated
• Agents integrated with your systems of record through documented APIs, not screen scraping
• Human approval gates at every consequential step, with exception handling designed in from the start
• An immutable audit log of every decision and action, with the inputs that produced it
• Source, runbooks and documentation handed over, so your own team can operate and change it

How it works

• Map: We follow the work as it actually happens and measure where the time and the errors really go, which is rarely where the process document says.
• Design: Decision rules, approval thresholds and exception paths are agreed with risk and compliance before anything is built.
• Prove: Agents are tested against real historical cases where the correct outcome is already known, and scored on those.
• Run: A supervised launch with every action reviewable, then monitoring as volumes and document formats change.

When it is not the right fit

Credit decisions, suitability assessments or anything a regulator requires a named, licensed individual to decide. The system prepares and evidences; a person decides.

How is this different from the RPA we already tried?

Classic automation follows fixed screen positions and breaks the moment a layout changes. These agents read the document and the context, so variation is handled rather than fatal — and where they are unsure they escalate instead of proceeding.

Can we show a regulator what the system did?

Yes. Every decision and action is logged with the inputs that produced it, so a case can be reconstructed and reversed. The audit trail is a design requirement, not a reporting add-on.

Will our client data leave our environment?

No. It runs in your own cloud tenancy or data centre, in the Kingdom where that is required, and your data is never used to train public models.

Where should we start?

With a one to two week discovery that maps a single workflow end to end and gives you a costed plan. You own the plan whether or not you build it with us.