Automating Financial Analysis in IBM Planning Analytics using AI

Webcast recording from November 19, 2025

In this session, we discussed the automation of financial analysis using AI tools in IBM Planning Analytics and a broader EPM environment.

We demonstrated the ability of AI tools to interact with data and understand the relationships between different data stores (OLAP, Relational, files, external etc). Using simple business prompts, the tools can follow rules and processes, deliver insight into drivers of business performance and drill down to transactional drivers residing in different parts of the infrastructure.

We discussed and demonstrated the following specific use cases:

• Ability to retrieve information related to key metrics and financial performance
• Drill down and pivot within a cube, as well as understanding data across multiple cubes. Our example shows the names of new hires that drive an increase in compensation expense, with summary and detail information stored in two separate cubes that are connected with a rule
• Ability to span an IBM PA cube and a relational data store to retrieve deal-level detail and explain the drive of increase in sales. The data is loaded into IBM PA using a process and the tools are able to mine both in a single query using a simple business prompt
• Automate financial analysis by producing meaningful summaries of drivers and performance metrics that can be used as starting point for further analysis.

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