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How to streamline and enhance critical F&A functions with generative AI

23 June 2023

3 min read

Author

Juan Jimenez

Senior Product Marketing Manager, Finance Transformation

IBM Consulting

Honor Sherlock

Product Marketing Manager, Data & Technology Transformation (Data, AI and Automation)

IBM Consulting

Lucas Juarez

Partner, Global Finance Transformation

IBM Consulting

Shobhit Varshney

VP & Sr. Partner, AI, Data & Automation Leader, Americas

IBM

Vasanti Pillutla

Associate Partner, Global Finance Transformation

IBM Consulting

Imagine the future of Finance and Accounting (F&A). In this future, your F&A function is cutting edge. Perhaps you are using a next-gen Enterprise Resource Planning (ERP) system and an unmatched F&A planning platform that delivers advanced predictive analytics. You may have also deployed the latest cloud-native innovations and improved your operating expenses in the process. Your forward-looking, strategic CFO is driving AI efforts to enable proactive business insights across the enterprise, while streamlining business processes and optimizing financial performance. You’re equipped with holistic and unvarnished data, giving F&A an end-to-end view of your company’s full value chain (customers, suppliers, competitors, and front- and back-office operations). You sit at the forefront of innovation within your organization and are a catalyst for change. But now you’re tasked with driving enterprise-wide growth and driving digital transformation to help ensure your organization achieves operational excellence.

IBM Consulting brings industry expertise to help you understand how to derive value in specific workflows (such as record-to-report, lead-to-cash, procure-to-pay and others) by augmenting these processes with new AI capabilities. We can drive meaningful impact with the technology in core finance processes by streamlining tasks and revolutionizing the way F&A professionals work going forward. A recent IBV study about modernizing record-to-report with AI indicated that “organizations infusing AI into record-to-report generate 66% faster cycle time to process journal entries.”

Moreover, some Large Language Models (LLMs) can already research and summarize, translate and interpret, generate and create, comprehend and report, converse and engage based on the knowledge gained from massive datasets used by F&A. And there’s much more to consider (like regulatory constraints) in the process of rolling out generative AI.

Augmenting benefits in F&A use cases

Generative AI can benefit the record-to-report function and plan-to-insights subfunctions. The following are several tasks where we see clear opportunities to leverage generative AI (as well as conversational AI capabilities) to streamline and enhance these highly critical F&A functions:

  • Research and summarize: Generative AI can research large data sets, extract key insights, and summarize complex texts (such as research and accounting standards, Generally Accepted Accounting Principles (GAAP), guidance notes, briefs and publications). AI can then synthesize the information and summarize insights for appropriate treatment to the company’s financial transactions, assess impact and answer critical technical accounting questions and disclosure requirements.
  • Translate and interpret: Generative AI can translate and interpret data into a narrative that can provide insights and guidance for internal or external reporting with recommended actions. For example, generative AI can translate accounting policy and interpret it into a sequence of transactional accounting journals, along with a detailed explanation to help accounting professionals.
  • Generate and create: Generative AI can generate reports with fine commentary, draft emails and create new content. Generative AI can be trained on historical financial data, reporting templates and regulatory requirements to generate standardized financial reports (and create customized reports tailored to specific stakeholder needs).
  • Comprehend and report: Generative AI can comprehend and report financial data to provide valuable insights and support decision-making process. For example, it can comprehend financial data such as revenue, expenses, profitability, cash flow, working capital and other relevant financial data to report key trends and insights, along with easy-to-understand commentary and narrative.
  • Converse and engage: Generative AI can engage in real-time, interactive dialogue to provide instant responses and explanations, allowing for timely decision making. For example, by combining conversational capabilities, generative AI can provide dynamic, interactive and insightful financial commentary that accelerates the speed, accuracy and engagement needed for professionals to make decisions.

IBM’s Center of Excellence for generative AI transforms core business processes, experiences and IT operations and benefits from learnings from our AI client engagements. Our full-stack approach provides a portfolio of AI products for building and deploying traditional machine learning and new generative AI capabilities powered by foundation models.

Explore more posts in this blog series, The Future of Finance with Generative AI, to learn more about how generative AI can help F&A professionals and how you can improve your finance operation’s efficiency with generative AI.

 
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