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Case study

Financial reporting

Building a co-pilot for SBB to assist in monthly financial reporting.

Challenge

Solution

  • Every department of SBB writes a monthly financial report.


  • All reports are created by manually analyzing hundreds of financial KPIs.


  • This is a complex and time intensive task.


Impact

  • Data pipeline to clean and preprocess KPI data.


  • Feature engineering: Definition of additional compound features from raw KPI variables based on domain knowledge of report writers.


  • Report generation: Engineered an LLM (GPT-4) to analyze the KPIs and to write reports matching both style and scope of human written reports.

  • Time savings: Autonomous generation of the financial report, serving as basis for the creation of the final report by the responsible employee.


  • Additional insights: The reports generated by the AI provide a second perspective, complementing the human point of view.

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