INDUSTRY · BANKING

Artificial intelligence in banking: AI prepares, the banker decides.

Pre-assessed credit files, compliance checks, advisors prepared before every meeting: we build uses that respect the AI Act, DORA and banking secrecy.

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  • AI Act, DORA, ACPR built in from the design stage
  • Customer data stays within your perimeter
AI IN BANKING
For
Branch network, operations, compliance
Who decides
The banker
Updated
October 15, 2026

THEY TRUST US

  • Celio
  • Plein Sens
  • Shiseido
  • Green-Got
  • Promologis
  • Bridgestone

IN BRIEF

Where is AI useful in a bank?

Wherever the work is reading, checking and summarizing: assessing business credit applications, compliance and know-your-customer checks, meeting preparation, visit reports, regulatory watch.

The framework is demanding. The AI Act classifies creditworthiness assessment of natural persons as high-risk; DORA governs the use of ICT service providers, including AI model providers; the ACPR, France’s banking supervisor, expects governance of algorithms. We design uses so that AI prepares and the banker decides.

In practice: every AI action is logged, customer data stays within your perimeter, and the decision stays human.

FIVE USE CASES

Pre-assessed credit · Faster compliance · Prepared advisors · Meeting reports · Regulatory watch.

  • Executive management
  • Branch network
  • Operations
  • Compliance
  • IT

Updated October 15, 2026.

WHAT YOUR TEAMS FACE

Time goes into files, not into clients.

What branch network and compliance leaders tell us.

  • CREDIT

    “Documents get checked one by one, before the file is even analyzed.”

  • COMPLIANCE

    “Checks pile up faster than the teams can keep up.”

  • MEETINGS

    “The advisor prepares for the meeting in the elevator.”

WHO IT’S FOR

  • Executive management
  • Branch network
  • Lending
  • Compliance
  • IT

USE CASES

AI prepares, the banker decides.

Uses built with your teams, connected to your tools, with a record of every action.

  • Pre-assessed credit

    AI checks the documents and drafts the summary of the business credit file. The account manager decides.

  • Faster compliance checks

    AI checks customer files and prepares the alerts. The compliance officer handles them.

  • Better-prepared advisors

    Before each meeting, AI summarizes the customer’s history and the relevant procedures.

  • Meeting reports in the CRM

    The advisor dictates on leaving the meeting; the report is filed in the CRM, after review.

  • Regulatory watch, summarized

    The relevant texts, summarized with their source and sent to the teams concerned.

  • Rules set from the start

    Traceability, access rights, review: GDPR, AI Act and DORA built in from the design stage.

AI-READY

Your AI agents read and act in the tool, through MCP.

MCP is an open standard: a universal plug, under your control, between your software and AI. Your IT department approves every access.

  • SAMPLE REQUESTS TO YOUR AGENTS
  • “Which documents are missing from this company’s file?”
  • “Summarize this customer’s history before my meeting.”
  • “Which texts published this week concern compliance?”

BEFORE / AFTER

What changes for your customers.

TODAYWITH AI, APPROVED BY YOUR TEAMS
CreditDocuments checked one by one.File pre-assessed, summary ready, human decision.
MeetingsPrepared in a rush.History and procedures summarized in advance.
ReportEntered in the evening, or never.Dictated on the way out, filed in the CRM after review.

Every gain is measured in your company, from your starting point.

OUR METHOD

Four steps, with your compliance team.

The four steps of our method, in a loop. Each can be done on its own; together, they organize AI across the whole company.

  1. Inspire your leadership team

    A keynote built on cases from your business. Your leadership decides where AI will be useful, and where it will not.

  2. Map your operations

    We spot the bottlenecks, rank use cases by gain and difficulty, and name the tools to keep.

  3. Bring your teams on board

    In a hands-on session, everyone arrives with a real problem and leaves with the AI agent that solves it. An AI policy sets the shared rules.

  4. Build with the AI Factory

    Our engineers build AI-ready business tools with you. You keep the keys.

You take back the keys.

The code and data stay with you, documented. We keep improving the tool with you, or you take it over. This is step 4 of our method: Build with the AI Factory.

YOUR QUESTIONS

What banks ask us.

What are the use cases for AI in banking?

The most common: assessing credit applications, compliance and know-your-customer checks, advisor preparation, meeting reports, regulatory watch, and answers to internal questions on procedures.

Which AI uses are high-risk under the AI Act?

In banking, notably creditworthiness assessment and credit scoring of natural persons (Annex III). Document summaries and support for credit assessment, when a human decides, fall under a different regime.

Is an AI model provider a third-party provider under DORA?

An AI service supplied by a third party is one of the ICT services covered by DORA: it falls within your third-party risk management. Check the exact scope with your compliance team.

What does the ACPR expect on AI?

The ACPR published principles for the governance of AI algorithms (2020) and devoted a review to AI (2024): explainability, human oversight, data quality, performance monitoring.

Can AI decide on its own to grant a loan?

We do not build that kind of use. AI checks and summarizes; the account manager or the committee decides.

Does customer data leave the bank?

No: it stays within your perimeter, hosted in France or on your premises if your rules require it. Access rights are set with your IT department.

How do we start without launching a two-year program?

With a keynote for leadership and a well-chosen first use case, put into service in one team, then extended.

SOURCES

The texts and studies cited on this page.

Every figure on the site is sourced. See all our sources.

LET’S TALK ABOUT YOUR PROJECT

Let’s talk about your teams and your customers.

Thirty minutes to understand your priorities, and tell you where we would start.

Your contact

The AI Origin team that runs the projects

You talk directly with the people who will run your project, from scoping to go-live.

No specific project yet? Start with a hands-on session: everyone brings a real problem and leaves with the AI agent that solves it. See step 3, Bring your teams on board

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