AI for CFOs

Nate Buchanan Director, Pathfindr

One of the most interesting parts of being a co-founder of a bootstrapped startup is that you have to - I mean “get” to - do many different jobs in the company that you might never have thought you’d need to do during your career. For example, as the COO of Pathfindr, I have a wide range of responsibilities. I’m primarily in charge of delivery, but I also look after our solutioning, SOPs, legal needs, and some sales and recruiting. The one area that I own that had the steepest learning curve was - you guessed it - accounting and finance.

For those who think about corporate financials all day, it’s tough out there right now. That won’t come as a surprise to CFOs, or people who work in a CFO’s organization, but it was certainly a wake up call for me as I started learning on the job at Pathfindr. Challenges abound, including:

• Global Economic Uncertainty - interest rate fluctuations, rising inflation, and unpredictable disruptions to supply chains can cause a ripple effect that impacts your bottom line
• Regulatory and Tax Requirements - minimizing your tax liability can be highly complex (particularly if you operate across multiple jurisdictions) and the proliferation of regulations for ESG compliance and data security is considerable
• Ongoing Digital Transformation - many organizations have been modernizing their tech stack to varying degrees over the last several years, a complex process that is complicated even further by the introduction of new technologies like cloud and blockchain

These elements would make the CFO’s job difficult enough but when you combine them with the “basics” of accounting and finance - balancing the books, forecasting cash flow, creating a company’s financial strategy, mitigating ongoing risk, and so on - it raises the stakes even further.

As with most things these days though…AI can help. However, it’s important to distinguish between AI that might be baked into an ERP system such as Hyperion or BPC, and bespoke solutions that use AI to solve discrete problems in the finance organization’s workflow. The former might be a good solution to optimize tasks done within the system itself, but there are many other things that need to be done that often require heavier lifting. Below are some ideas on how CFOs and their teams can leverage AI to get more done in less time.

1. Invoice data extraction and consolidation - AI can be used to extract critical information from invoices in different formats and import it into a wide range of systems to ensure that it’s recorded on the ledger, the supplier gets paid, and the invoice itself is saved for tax purposes. Some platforms offer these features natively, but if you don’t have a solution that can do this (or haven’t set yours up optimally) building an AI agent for it can be done fairly quickly and cost-effectively.
2. Regulatory report generation - creation of annual reports and other regulatory documentation can be highly time-consuming, particularly because they usually require someone to consolidate data from a wide range of sources, add editorial commentary in alignment with the company’s strategy and vision, and double-check the numbers and math to ensure compliance (it’s regulated, after all). AI can help with all of these elements.
3. Anomaly detection - looking for potential fraud or other issues across large volumes of financial data is a core responsibility of the CFO organization and is one that often requires a lot of manual effort. AI can use a set of instructions provided by a human - things like particular areas of risk and context from historical data - to evaluate a P&L and recommend follow ups based on where there might be a problem.
4. Market intelligence - for CFOs tasked with pricing a potential acquisition, AI can be an invaluable tool to comb through massive data sets and find obscure insights on the internet from the financial press, technology providers, social media and other sources. Manually evaluating inputs across all of these elements is often cost-prohibitive, and AI can help teams both source the data and understand its meaning.
5. Customer and supplier optimization - AI can be a great unlock for CMOs and CFOs who want to understand how to better market products and services to their customers or how to consolidate/improve supplier relationships to get the best possible terms for their companies. Analysis of customer demographics, purchase history, accounts payable data and supplier offerings is made much easier when you are able to use AI to source and analyse data, even if it’s just as a “second opinion” to human analysis.
6. Expense management - as a former consultant who spent far too much time itemizing and reporting travel expenses, I just want everyone to know that AI can help with this. There are a wide range of SaaS solutions that can do it, or you can build something bespoke. If you employ people who travel frequently for work, consider doing this for their sake. I beg you.

One important note on risk - CFOs tend to be (understandably) risk-averse, particularly when it comes to activities with regulatory or bottom-line implications. Relying too heavily on AI to create documents that will be reviewed by a regulator or to analyze numbers that will drive critical decisions for your company is unwise. However, there are many discrete use cases within those activities that AI is perfect for. Whether it’s doing research on market activity, proofreading an update to investors, or providing a second set of eyes on financial projections, AI can help CFOs and their teams spend more time on higher-order analysis and strategic planning, and less time doing mundane manual work.