Unlocking quantified AI potential in finance processes.
An activity-level analysis makes automation potential economically assessable and creates a robust basis for targeted AI investments.
The question
How can relevant AI potential in complex finance processes be identified and prioritised without investing resources into unclear or economically unattractive use cases?
Our answer
We analysed finance processes down to activity level and identified suitable starting points for AI and automation. The expected efficiency potential was quantified, translated into concrete use cases and business cases and prioritised by impact and feasibility. This resulted in a robust roadmap for targeted implementation.




What we delivered
AI levers made visible at activity level
Process activities analysed and suitable starting points for AI and automation identified
Efficiency potential quantified and made economically comparable
Expected effort reductions assessed and translated into robust business cases
Investments focused on the highest-value use cases
AI use cases assessed and prioritised by impact and feasibility
What it achieved
- A transparent potential map shows AI levers along the finance processes
- A prioritised roadmap focuses resources on value-creating AI use cases
- Quantified business cases create a robust basis for investment decisions
- Identified automation potential opens up concrete efficiency gains
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In 25 minutes you will understand whether we can help. No slides. No demo.
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