AI for Finance
Monday, 12 August 2024
Enterprise Performance Management (EPM) involves monitoring and managing an organisation’s performance across various financial, operational, and strategic metrics. Emerging AI technologies are increasingly integrated into EPM software to enhance decision-making, improve efficiency, and provide deeper and automated insights. Current use cases for AI within the performance management process include:
Financial Planning and Analysis
AI algorithms can analyse historical financial data to forecast future trends and performance. By identifying patterns and anomalies, AI enhances the accuracy of financial planning and budgeting processes. This allows organisations to create more reliable financial models and scenarios, ultimately leading to better decision-making.
Automated Reporting
AI automates the generation of performance reports, reducing the time and effort required by human analysts. Natural language generation (NLG) technologies can convert complex data sets into easy-to-understand narratives, providing clear insights into an organisation’s performance metrics and helping stakeholders make informed decisions quickly.
Predictive Analytics
AI leverages predictive analytics to anticipate future performance and identify potential risks and opportunities. By analysing historical data and external factors, AI models can provide forecasts and recommendations, enabling proactive management and strategic planning.
At mecklemore, we keep a finger on the pulse as we observe the different approaches taken by our software partners.
- Jedox socialises the concept of an AI-powered 'digital business partner' as the ultimate goal of its 'autonomous finance' vision - a world defined by natural language interaction, AI-based recommendations and automated report creation.
- Board has similar aspirations for its front end but also seeks to integrate more closely with the ML and AI capabilities of its underlying Azure cloud platform.
- Oracle ships 'Intelligent Performance Management' (IPM) with its Enterprise EPM licences, which enable auto predictions, proactive IPM insights, and BYO machine learning models.
Our clients are generally excited by the opportunity, but we haven't seen widespread adoption yet. We suggest that users remain in the driver's seat for now and use predictive capabilities as a co-pilot (pardon the pun) to validate forecasts rather than determining them. Traditional AI capabilities are available in all major EPM products today.
The generative AI element, however, remains in its infancy. Providing a natural language narrative on financial and operational results is basic at best. How good would it be if we could get the major headlines across all our datasets presented to us daily — a bit like the AI-powered minutes of Teams meetings? It would be a game-changer. We believe it is coming.
If you want to discuss real-life AI opportunities for your xP&A function, please contact us today!
