Financial Forecasting

The goal of this plug-and-play solution is to show finance teams how Dataiku can be used to transform your forecasting process by streamlining your data process and improve accuracy through machine learning. More details on the specifics of the solution and legal disclaimer on the use of this solution can be found in the knowledge base. This solution is only available on installed instances.

Business Overview

The Financial forecasting processes managed by Finance teams play a central role in supporting companies to make appropriate cost management and investment decisions. Yet 40 percent of CFOs feel their forecasts are not accurate and that the process takes too much time*. More precise, less costly-to-produce forecasts are of immediate value, but connecting to the data and tapping into the different techniques needed to achieve them can feel out of reach. This can be a result of too little time available to dedicate to setting up a new forecasting project or a lack of confidence in the statistical and machine learning techniques involved. 

Enhancing the efficiency of Financial Forecasting requires: 

• Improving the capacity for Finance teams to quickly access data and automate data pipelines. Rather than relying on manual checks and merges via spreadsheets, teams can streamline their processes, save time and reduce errors, allowing them to focus more on analysis and decision-making. 
• Easing the comparison of traditional and advanced statistical / machine-learning forecasting techniques, with simple tests and selection of appropriate drivers, developing more accurate projections alongside full ownership and explainability. 

Dataiku’s Financial Forecasting Solution offers Finance teams an opportunity confidently transition through a transformative shift in their business impact while retaining full control of process and outputs.

Highlights

• Enrich your forecasting approach by blending machine learning and enhancing existing techniques, improving results while reducing effort.
• Flexible driver-based evaluation allows your team to quickly test and select potential financial drivers from internal (e.g., headcount) or external (e.g., inflation) sources.
• Business-friendly explainable AI allows Finance teams to quickly create and immediately understand the results of machine learning-based predictions without complex development.
• Powerful visual analytics clearly reveals historical and future forecasting accuracy, ensuring existing and improved techniques can be directly compared and evaluated.

Plug and Play across any financial dimension

Using the step-by-step Application, teams can easily load costs, revenues, cash flow and more, and customize time horizons, alongside business or geographic splits. Then connect driver dataset if desired, and get immediate and actionable results that can be presented directly to business users and management.

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Versatile and shareable financial reports

Perform as much of your existing and enhanced financial forecasting analytics within Dataiku as you wish, using integrated dashboards (or your own custom creations) to view new machine learning insights alongside historical forecast and actual data, then share the results with ease.

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Powerful visual forecasting analytics

Explore and better understand your historic forecasting performance, from bottoms-up and top-down methods, and how new statistical and machine learning techniques can enhance accuracy without requiring complex data science expertise.

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Compliment existing expertise with ML

Develop more powerful forecasts by integrating expert knowledge of potential drivers with data-driven machine-learning techniques to evaluate their effectiveness. Thoroughly and easily interpret each model’s findings through quick and insightful analyses of key drivers.

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