Thursday, September 29, 2022

Ways artificial intelligence is changing financial planning and analysis

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By Arleen Atienza

Artificial intelligence is increasingly penetrating various sectors of modern life. Financial planning and analysis is one segment where implementation of artificial intelligence is growing. How AI is shaping the segment?

Sixty years after John McCarthy came up with the term “artificial intelligence” to refer to the engineering and science of making machines think, we have seen an accelerated rate in technology, specifically the artificial intelligence-powered ones. Today, we live in a world where computers are able to process huge amounts of data and see patterns in it. These artificial intelligence-powered tools have made modern society revisit how we consolidate and analyze information, and use these insights to make decisions.

From small businesses to large enterprises, everyone is dealing with enormous amounts of data today. And the demand to analyze and understand the patterns in these data made way for the utilization of artificial intelligence in important processes, including those in finance — particularly financial planning and analytics (FP&A).

FP&A or the process of planning, budgeting, analyzing, and forecasting in support of the financial health and business strategies of a company, is heavily impacted by automation and digitization. Financial planning in the corporate setup uses both qualitative and quantitative analysis to determine whether an organization is well-positioned and on its way to achieving its business goals.

The processes involved in FP&A are complex and critical to making important business decisions. This and the fact that the competition in data-driven markets continues to tighten up over time, urge firms to adopt technologies that could give them a competitive advantage.

Artificial intelligence is currently changing the way FP&A teams work and will continue to do so in the years to come. Two of the most important trends in which artificial intelligence plays a critical role are Robotic Process Automation (RPA) and Financial Analytics.

Robotic process automation

RPA and artificial intelligence go hand-in-hand. When automating processes in the finance sector, there is a need to integrate finance robotics with other intelligent automation tools and technologies. RPA/artificial intelligence is referred to as the use of versatile tools for automating manual tasks that are crucial in the execution of business processes or the delivery of IT services.

Managing data in FP&A entails a lot of structured and rule-based processes, which is why RPA is highly applicable to FP&A teams. RPA software robots are able to handle reporting, data gathering, matching and reconciliation, even the more intricate and multifaceted processes, such as period-end review closes.

General processes in finance such as general and operational accounting, planning, budgeting, and forecasting, financial reporting, and treasury processes all greatly benefit from RPA/artificial intelligence today. Considering RPA/artificial intelligence’s benefit to several finance functions, we definitely see artificial intelligence continuing as a mainstay in FP&A in the years to come.

Financial analytics

Financial analytics aids in solving business-related problems and supporting decision-making through the application of statistical analysis frameworks and their corresponding data algorithms — data that are derived from various sources. The two facets of financial analytics are descriptive and predictive. Descriptive analytics tackles what has happened — whether it’s evaluating the success of the use of corporate cards or the effectiveness of an online financial wellness program — with the use of correlations, patterns, trends, and clusters.

Predictive analytics, on the other hand, talks about what could happen. It is definitely of more interest to those in charge of making important decisions for the business. Artificial intelligence-powered analytics tools are able to undertake this process by consolidating varied data sources and integrating information to generate practical insights. This will, in turn, help financial planners be more accurate, time-efficient, and productive. In the aspect of planning and reporting, artificial intelligence-powered predictive analytics is able to not only answer “what could happen?” but also the more important question, “how are we going to make it happen?”

Also Read: Farm Law controversy: How Indian farmers challenging problems and getting things done

(Arleen Atienza writes on a wide range of topics including finance, business, beauty, health and wellness, and law, to name a few.)

(Disclaimer: The views expressed in the article above are those of the author’s and do not necessarily represent or reflect the views of Autofintechs.com. Unless otherwise noted, the author is writing in his/her personal capacity. They are not intended and should not be thought to represent official ideas, attitudes, or policies of any agency or institution.)

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