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AI for Banks and Savings Banks

AI that reaches the business units and meets the requirements of supervisors and internal audit.

The Situation

From Pilot Project to AI in Everyday Use

Many institutions have introduced their first AI tools in recent years. In the daily work of the business units, however, the benefit often falls short of expectations: use cases emerge in isolation, knowledge is not shared, and without clear guardrails the risk of uncontrolled AI use grows. At the same time, every application has to meet the requirements of supervisors, data protection, co-determination and internal audit. We anchor AI in the institution in a structured way, with reusable use cases, enabled employees and an operating model that stands up to any audit.

Use Cases

Where We Start

  • Standard Use Cases

    We develop a portfolio of proven use cases, for example for analysing financial reports, evaluating market information or regulatory reviews. Each use case is defined and tested together with the business unit and moved into operation in an orderly way.

  • AI Enablement

    In hands-on formats, employees learn to use AI safely and effectively for their own tasks. This builds an AI culture in which new ideas are picked up deliberately instead of emerging in unapproved tools.

  • Client Advisory

    AI takes over preparatory steps such as the structured collection of client information and documentation. Advisers go into the conversation better prepared and concentrate on personal advice.

Discover Your AI Potential

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Besprechung im Büro von BLACKFIELD AI.

In Practice

Anchoring AI Across a Bank

For a bank, we are accompanying the path from the first use cases to institution-wide AI use: with a portfolio of standard use cases, an active AI community and a clear organisation for long-term operation.

Guardrails

  • Audit-Proof From the Start

    Responsibilities, approvals and logging fit into your existing IT risk management and remain traceable for auditors and internal audit.

  • Decisions Stay With People

    Your employees make lending and investment decisions. AI prepares and frees up time.

Frequently Asked Questions

By making responsibilities, approvals and logging part of every application from the start. We fit AI applications into the institution’s existing IT risk management so that auditors and internal audit can trace who approved what. Data protection and co-determination are involved from the beginning.

With standard use cases that can be reused across several business units, such as analysing financial reports, evaluating market information or regulatory reviews. Each use case is defined and tested with the business unit and moved into operation in an orderly way. A potential analysis shows which order pays off for your institution.

With approved tools, clear rules and enabled employees. In hands-on formats, employees learn to use AI safely for their tasks. New ideas are picked up deliberately instead of emerging in unapproved tools, and the operating model defines who decides on new use cases.

No. Your employees make lending and investment decisions. AI takes over preparatory steps such as the structured collection of client information and documentation, leaving more time for personal advice.

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