Whitepaper: Artificial Intelligence & Finance

Budgeting, Planning and Forecasting

An exploration of the use of Artificial Intelligence (AI) in the management of Budgeting, Planning and Forecasting (BP&F) by the Financial Office.

Summary

Financial success is largely dependent on where the market is heading. Artificial Intelligence or “AI” offers an unprecedented ability to improve the accuracy and predictability of Budgeting, Planning and Forecasting (BP&F). This is able to reduce the expensive and time intensive exercise of the annual budgeting process.

The objective of using AI is the broader concept of using machines to carry out financial tasks in a way that we would consider as “smart”.

Machine Learning or “ML” are the applications of AI in that we are able to give machines access to data and let them learn for themselves using quantitative techniques and thereby reduce estimating errors. AI solutions with machine learning algorithms continue to self-improve as more data is fed into it. The fact is, the use of business intelligence, particularly through AI, to more effectively automate the BP&F process is growing more important as speed, flexibility and agility takes center stage.

BP&F is a 3-step process for determining and detailing an organization’s short and long-term financial goals. The process tends to be managed by the Finance Department under the auspices of the Chief Financial Officer (CFO).

AI impacts BP&F in the following ways:

  • Analyzes unstructured and structured data to reveal patterns, suggesting actions based on trends.
  • Generates signals and indicators for monitoring financial scenarios to help give organic view of the financial risks that improve accuracy over time.
  • Enables near real-time understanding of financial objectives, facilitating changes in direction where required.
  • Enables financial risk assessment through algorithms to make more accurate predictions of market movement.

The objective of using Artificial intelligence (AI) is to better streamline financial managerial tasks and increase the accuracy of forecasting with quantitative predictions, through self-improving systems, thus reducing budget, planning and forecasting errors. AI solutions can more effectively automate the planning process is growing more important as speed, flexibility and agility take center stage.

Key business driver data often lies outside of the “usual suspect” systems. To take advantage organizations need to collect, monitor and react to data in near real-time. Overall innovation is changing current BP&F methods, with more organizations adopting AI solutions to increase their financial accuracy.

A shift towards perpetual, scenario based BP&F models in using AI is a directional “step change”; that helps to eliminate ceaseless manual processes that have financial implications on daily operational realities and direction. Manual solutions won’t capture dynamic operational and financial complexities in a timely fashion.

As AI becomes adopted more into the mainstream, financial forecasting and modeling will become neither reactive nor proactive, instead near real-time and accurately predictive.

November 2017

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