AI Use Cases in Finance: An Overview

In the third article of the AI in finance series (find the first and second and forth articles here) we will explore some of the most common use cases for AI in finance. Before we dive in, let’s review how AI is used in finance. Below are insights into some of the frequently asked questions regarding AI use cases in finance.

AI Use Cases in Finance FAQs

 

How is AI Used in Finance?

So, how is AI used in finance? Today’s finance professionals use AI tools and applications for a broad range of business benefits by automating routine tasks such as data entry, data reconciliation, and data processing. Modern AI tools allow finance professionals more time to focus on data analysis and strategic planning.

AI algorithms can process and analyze large volumes of financial and operational data much faster than humans, identifying trends and patterns that might be otherwise overlooked. This capability allows for more accurate financial reporting and financial forecasting.

What are Some Examples of Using AI in Financial Planning?

AI-driven financial tools are becoming increasingly common. Below are 5 examples of how finance teams are using AI.

With the help of AI, finance teams can spend less time on spreadsheets and more time on strategy. As technology crunches the growing volumes of data, soft skills like critical thinking, problem-solving, and communication will become crucial for Finance to succeed.

Data Science and Analytics

AI tools provide a boost to data science and analytics, allowing finance professionals to process large datasets rapidly and efficiently. They are able to better identify trends, correlations, and outliers that might be missed through manual analysis. With deeper insight into data analytics and customer behaviors, AI tools can elevate and expedite strategic decision-making.

Anomaly Detection

Anomaly detection is ideal for identifying unusual patterns or behaviors that could indicate errors or other risks. AI tools for accounting and finance can analyze data in real-time, allowing finance professionals to detect and flag anomalies in datasets. These capabilities help maintain the integrity of the datasets.

Provide Real-Time Modeling

With cloud-based financial data and nearly unlimited processing power, multiple and complex scenarios can be generated instantly with AI. Armed with solid, reliable, and timely intelligence, the CFO and leadership team can look ahead, modify operations, and reconfigure the business model in response to fluctuating business and market conditions.

Risk Management

Machine learning models can evaluate the risk associated with different financial strategies, allowing financial planners to create strategies that minimize costs while maximizing potential returns.

Predictive Analytics

AI is used to analyze historical data and current financial conditions to predict future financial trends and identify potential financial risks, allowing businesses to take proactive measures to mitigate any uncertainties.

Examples of Organizations Using AI in Finance

Aurorium Used AI To Increase Order and Sales Forecast Accuracy
Aurorium produces specialty ingredients and performance-enhancing materials that help global manufacturers deliver value-added solutions. As a global business thriving with organic expansion and frequent acquisitions the company incorporated AI for a more transparent monthly close and financial consolidation processes, and also incorporated predictive AI software to improve sales forecasting and production planning.

Read the full story here.

Rocket Software Brings AI Into the Office of the CFO
Rocket Software offers IT modernization and IT automation solutions. The team began using AI software to pull finance, human resources, and its business leaders out of spreadsheets in order to streamline and improve its workforce planning processes. They used AI tools with native artificial intelligence (AI) and machine learning (ML) capabilities to spot potential errors and create hyper-accurate forecasts.

Read the full story here.

AI Use Cases in Finance Summary

AI is rapidly becoming an indispensable part of the finance team’s tech stack, offering powerful tools that enhance decision-making, optimize financial strategies, and provide financial predictions. From real-time modeling to anomaly detection and predictive analytics, AI is transforming how financial plans are developed and executed. As AI technology continues to evolve, its role in financial planning is expected to grow, providing even more sophisticated tools to help organizations achieve their financial goals with greater accuracy and confidence.

Does Planful Offer AI for Finance Professionals?

Yes, Planful delivers AI-enabled assistants as a service through our software, augmenting human effort, streamlining collaborative processes, accelerating cycles, and upskilling teams. With persona-based intelligence, Planful enables smarter decisions and drives financial and operational excellence.

Planful’s AI/ML capabilities slash FP&A cycle times, identifying anomalies in financial data, reducing manual effort, and increasing trust in the data. This confidence boost allows finance teams to focus on delivering insights and guiding high-level business.

Planful AI – Detect spots potential errors in data and creates hyper-accurate financial forecasts, allowing users to parse historical data and highlight anomalies where inputs and historical trends don’t match. With Planful in the trenches, finance teams can focus on supporting growth with strong financial planning decisions.

Ready to transform your FP&A processes with AI? Take a tour of our Planful AI Labs video series for insights into how cutting-edge AI advancements are reshaping financial processes, or register for our on-demand webinar, “AI’s Impact on FP&A,” in partnership with the CFO Leadership Council.

You can also get an interactive demo to see Planful in action.