Predictive Analytics

Today’s financial professionals are shifting away from a purely retrospective perspective and toward proactive value creation. This has led to demand for a new set of tools, including predictive analytics, which is essential for making the leap from answering “what happened?” to “what is likely to happen?”

In this month’s edition of Financial Terms Decoded, we’re taking a look at predictive analytics.

📢 The #AFP2025 Session Explorer is live. Discover sessions across a range of topics, including practical applications of artificial intelligence (AI), machine learning (ML) and predictive analytics, and create your own unique experience at AFP 2025, October 26-29, in Boston.

What Is Predictive Analytics?

Predictive analytics is a subset of business analytics that combines statistical analysis and ML to analyze datasets and make predictions about a dependent variable. The foresight provided by predictive analytics enables financial professionals to forecast more accurately and manage risk proactively, driving greater strategic value for their organization.

Predictive analytics can be applied to continuous variables, such as the weight of raw materials ruined during production, or discrete variables, such as the number of unsatisfied customers during a quarter. It’s especially useful in automated decision-making systems that provide event-driven alerts related to unusual events.

Below are examples of predictive analytics use cases for functions in the office of the CFO:

• In accounts payable (AP), predictive analytics can help AP teams determine the optimal time to pay suppliers by analyzing vendor invoices, payment terms and historical payment data.
• In accounts receivable (AR), predictive analytics can help AR teams analyze each customer’s payment history and invoice details to predict when each invoice will be paid.
• In financial planning and analysis (FP&A), predictive analytics can be used to run sophisticated “what-if” scenarios by quickly simulating the financial impact of hundreds of potential business scenarios.
• In treasury, predictive analytics can help treasury teams forecast cash positions with greater accuracy by analyzing real-time and historical data, as well as market trends.

As predictive analytics enhances finance processes, it also transforms the skill set required of financial professionals. Read the full article on AFP’s website to learn the strategic framework financial professionals need to implement predictive analytics and the skills they need to leverage it effectively.

Ready to Dive Deeper?

What Does the Future Look Like for Treasury?

This AFP Executive Guide, underwritten by Wells Fargo, explores key macro trends shaping treasury and shares how automation, data analytics, digitization and investing in people help future-proof treasury.

AFP FP&A Guide to AI-Powered Finance

If you’re company is in the beginning stages of exploring AI, this guide is for you. Discover how AI can enhance a predictive analytics project and gain a framework to avoid common pitfalls when beginning and scaling a project.

Analytics for Finance

This AFP Digital Badge helps you lead with confidence with predictive analytics and demonstrate the power of visualization to quickly glean and convey insights provided by the analysis.

Coming Soon

AFP FP&A Series: No-Code AI for Finance

August 27 | 11:00 AM - 3:00 PM ET | Complimentary | Virtual

Through real-world use cases and implementation frameworks, Gauthier Vasseur, President and CEO of Datawise Academy, will teach financial professionals how to harness the power of generative AI, ML and intelligent agents — without needing to master coding, data science or advanced mathematics.

📅 Register now to save your spot at the virtual event.