How AI and Machine Learning are transforming finance

Who’s crunching your numbers?

She’s super smart, works extremely long hours, picks up on patterns and trends, knows and uses all the latest tools, makes great predictions, is extremely accurate, and incorporates feedback and constructive criticism well. She’s also on guard for bias all the time and ingests large amounts of operational, financial, and third-party data with ease. Meet Ali. She may just be the key to transforming your company’s finance function.

Ali could also be yours. She’s “available” as an agent of innovation–she’s artificial intelligence (AI) in action. AI is well out of its early adopter phase. More importantly, CFOs are ready to explore AI’s potential–“accelerated business digitization,” including AI, was one of the top strategic shifts CFOs said their companies were making in response to a turbulent economic environment brought on by the pandemic. Already, 67% of respondents in our State of AI survey said they are currently using machine learning, and almost 97% plan to use it in the near future. Among executives whose companies have adopted AI, many envision it transforming not only businesses, but also entire industries in the next five years.

Recently, AI has transcended industries and sectors with explosive growth. It is now a powerful tool for CFOs and executives to address key challenges they face, including automation of processes, optimization of outcomes, and transformed engagement with tools and data. How should you be thinking about AI for the finance function? What should your goals be? And how can finance’s use of AI contribute to your company’s differentiation?

Within the finance function, AI can be applied to replace repetitive and labor-intensive tasks, performing such transactional work with increased speed and accuracy. Moreover, with its capacity to learn from large data sets, the technology can also be used to improve accuracy in such areas as budgeting and forecasting to enhance companywide decision-making. Take a look at three solid use-cases:

1. Financial planning: Want more precise predictive information for your organization? Use AI. It can help with the identification of critical performance drivers, improve your forecasting outcomes, and increase speeds to execute an accurate forecast. AI can also eliminate the human bias that goes into a forecast. This doesn’t mean that humans are cut out of the process; rather it means that a solid baseline can be produced for finance staff to review, tweak, and adjust drivers if needed. How does AI do this? It leverages financial, operational, and third-party data and learns from patterns to apply reason to future projections.
2. Financial close: Typically, a financial close required a lot of human power to get the job done. AI can receive thousands of transactions and make decisions on how to categorize them: whether it should be booked immediately or spread over multiple periods. AI can also automatically make required journal entries, generate financial statements, and provide commentary on how the company performed relative to budget and relative to the prior year. AI can eliminate bottlenecks and do the grunt work so finance teams just have to validate it. In essence, AI can help eliminate the scramble to get the books closed on time and without errors—making it a less tedious and stressful process.
3. Financial risk sensing: Not all transactions are good ones. Let’s take the case of a bank–are there suspicious deposits or withdrawals? AI’s models can analyze customer data, look for behavior patterns in transactions, and flag those that fall outside certain parameters. This learning from historical data is then applied for the future, providing foresight to potential risks. AI can be a powerful tool for the risk and compliance requirements of your finance function.

Optimally, AI can help finance departments shift human focus to activities that add real strategic value. “Ownership” of AI for finance can be inside finance, or elsewhere. We’ve heard from CFOs that they don’t want to become data scientists. (Nor, we might add, do data scientists want to become finance executives.) The foundation of a good result for AI in finance is to build cross-functional teams as you plan for AI. Some organizations are creating a Center of Excellence for AI applications. Discuss with stakeholders the universe of use cases and how they can apply to finance, then prioritize the ones that have the potential for providing the greatest value or the greatest risk mitigation. The benefits of using AI in finance can be numerous:

• Cost reduction
• Speed to execution
• Reduced complexity
• Transformed engagement
• Fueled innovation
• Fortified trust

CFOs and the entire finance function can be transformative agents of innovation by using AI. The results can not only inform the finance team with better, faster information, it can influence the strategic thinking of the entire organization. That should be the driver.

Authors

Max Troitsky
Managing Director
Deloitte Consulting LLP

Adrian Tay
Managing Director
Deloitte Consulting LLP