With each passing day, the impact of Artificial Intelligence (AI) in our daily lives is on an exponential increase. The use of Chat GPT and tools like Perplexity are now as common as the use of google search engine was in the early 2000s. Both AI and its advanced version, Generative AI, conceptualized on creating original content, are a part of every function in an enterprise.
The modern Sales team relies on AI to generate qualified leads by identifying prospective customers using algorithms. The modern HR team uses AI to increase their reach by sourcing the most suitable candidates to work for the organization. The Marketing team uses AI to create effective and crisp digital content for campaigns. Likewise, there are plenty of AI use cases for the finance function of an organization that would lead to the modernization of the Office of Finance. . This Whitepaper focuses on the various financial use cases that can leverage the strong capabilities of AI. The diagram below depicts the broad categories where AI can be used. There are use cases in each category, which will be discussed in detail.
Predictive Analysis
AI can be used to make critical predictions by combining the vast amount of data available in the operation applications of an enterprise with past trends and historical behavior. This leverage can ensure that CFO’s take timely action when needed.
Prediction of cash flows, expenses and revenues
Liquidity is a crucial aspect of any organization. Too much liquid cash will result in losing money that can potentially be invested in money market funds and other investment avenues. At the same time, the organization must be able to fund for its immediate needs like employee payroll and vendor payments . Besides this, liquidity is important for capital expenditures as well.
Due to the importance of maintaining the right amount of liquidity, it would be very beneficial for organizations to have a view of their cash flow for the next 6 months based on the factors below:
Customer receivables based on the AR invoices. While deriving this, AI can consider past customer behavior and paying patterns.
Open Sales Orders
Vendor Payables
Open Purchase Requisitions and Orders
Projects – ongoing projects that would eventually give rise to payments, commitments and billing.
Subscriptions that would result in AR invoices and earnings. Past customer behaviour can be considered to make the predictions more accurate.
Above are examples of data that can be derived from the finance application in place. Besides these, there will be data that is not present in the application such as future, unplanned courses of action for example: dividend payouts, share repurchase, capex investments, increase in travel costs etc. Scenario planning will help to consider these and predict the cash flows. Scenario planning is explained later in this article.
Where AI can truly play a huge part is by considering some of the past trends in making the cash flow predictions. Past trends can be customer behaviour and payment patterns, for eg: there may be customers who would run their payment cycle on a particular day of the week and that can cause some delays in receipt of funds. For frequently delinquent customers, AI can help in determining the strategies to make the payment happen sooner and thereby result in an improved Days Sales Outstanding (DSO). Past trends can also be applicable, for example, . there is a particular period in the year where travel expenses or payroll expenses increase due to a salary hike given to employees. All these trends can be considered to make the cash flow prediction as accurate as possible.
Strategic and Operational Insights
Imagine having a virtual assistant with whom the CFO of an organization can ask the below questions (including open ended and abstract questions) and manage to get pertinent responses in a matter of seconds.
Can the balance sheet be dissected as on last month to give a view of where the organization has done well as compared to the same month last year?
Does the organization have the optimal financial leverage? How does the debt-to-equity ratio today compare to one year ago?
Based on history and future prediction, how much money can be invested in liquid funds with no impact on liquidity?
What the earnings per share that the organization can expect six months down the line?
Considering the volatility of exchange rate, is the organization’s forex exposure more than what it should be?
How much on-hand quantity of a particular raw material would the organization require in one month based on historical trends?
Are there any transactions that can cause in delay in the AP Period close?
The first five questions are strategic ones, which CFOs and finance controllers would be interested in, while the last two are more operational and personnel who manage the day-to-day operations like clerks, shop floor supervisors and operational managers would be interested in. Using the vast amount of data that the financial application of an enterprise would contain, AI can answer these questions with data points in a matter of seconds.
Narrative reporting, which guides finance personnel in translating data from financial reporting to plain language is another feature that AI can accomplish. Financial ratios like Return on Investment, Return on Equity, Debt to Equity ratio, Working Capital ratio can be determined easily by AI along with insights and suggestions to CFOs.
Intelligent Automation
The focus of any organization today is to minimize the amount of manual and repetitive work that is carried out by using automation. and have the employees focus on more productive tasks that can result in organization growth. Below are certain use cases where automation can intelligently reduce the amount of manual efforts.
1) Creation of vendor invoices – Vendor invoices are generally sent by email (or mail) to the organization. In the earlier days, an AP clerk would manually create an AP invoice in the financial application. Automation can help in scanning the email for vendor invoices, creating them in the application, and route it for approval based on the invoice amount. There are applications available in the market that read vendor invoices with an accuracy of 70-75%. Using Generative AI can further increase the accuracy to more than 95%.
2) Creation of accrual entries – During the month end, organizations reach out to all their vendors asking for amounts pertaining to any unbilled services performed. Based on this, the accrual amount is derived, and journals are created. This whole process can be handled by automation and the manual effort can be reduced by over 90%. Automation would scan through the email, look for responses from the vendor, create journal entries automatically and send it for approval before the journals are posted.
3) Creation of Minimum Commitment invoices – Organizations have agreement with certain customers to have minimum amount of trade for a period. Discounts are offered to customers based on the minimum commitment value. There are cases when customers buy less than the minimum commitment amount for a period that needs AR invoices to be created manually. Automation can eliminate this manual effort by automatically creating these minimum commitment invoices basis the agreement with customers and send notifications to the customers.
Scenario Planning
Deriving the financial health of an organization based on multiple scenarios will help in planning and strategizing for better organization growth. Let’s us look at a few of these such scenarios. Scenarios can be of two types, external and external. External scenarios can arise due to political, legal, social, environmental and economic changes while internal scenarios are more to do with organizational policies and changes. Below are a few external scenarios.
Due to the prevailing political situation, if my sales from a particular region is reduced by 30%, what would my financial statements look like? (many companies had stopped servicing Russia customers during the Russia-Ukraine war and this can be a classic example for scenario planning).
Due to prevailing economic situation, if the reserve bank increases the interest rate, how would the increased borrowing cost impact the income statement and cash flow statement?
If corporate taxes are increased by x% as per predictions by most economic experts, how much would the organization stand to gain/lose?
There can be certain legal changes like government mandating new tests as part of climate change laws, which could impact manufacturing organizations and increase the overall cost. How will this impact in the various financial statements?
Examples of internal scenarios are as below:
If payment term for the organization’s unmanaged customers is changed from N60 days to N30 days, what would be the impact on cash flows, DSOs and receivables aging?
If there is a capex investment of $500,000 made in the month of Aug, what would the organization’s balance sheet and cash flow statement look like?
What will be the impact on my balance sheet if the organization decides to go for a stock buyback option, whereby the company would repurchase its own stock, after 6 months?
AI can play an important role in simulating financial statements and giving a viewpoint on financial ratios when one or more of these scenarios are considered. A comparison of cash flow predictions in the current state vs predictions when one or more of these scenarios are applied would give a CFO a very good idea of the impact of such scenarios and enable them to make an informed decision.
Fraud and anomaly detection
While technology has made rapid strides in taking organizations forward, the downside is it has given rise to fraudsters and people who misuse technology for personal gains. Statistics report that there is a victim of cybercrime every 37 seconds in the world and 2 internet users have their data leaked every second. These statistics are scary and prove there is a need to have fool proof cyber security in place. While most organizations have a dedicated IT system administrator team to configure firewalls and put in place steps to keep their data safe, AI can play a big role in detecting frauds and reporting anomalies.
In the earlier example of vendors sending their accrual details, if the accrual for a particular vendor is significantly higher than normal, then AI can bring this to the notice of the finance controller, who can then check and ensure that it is indeed the right value.
It is a common practice to have a separate portal for suppliers and customers, wherein suppliers can create purchase orders and invoices for themselves after going through an approval process. Any abnormal number or amount of such purchase orders or invoices must be brought to the notice of the organization’s procurement manager, who will analyze it and take corrective steps, if required. Vendors also correspond with the organization over emails and any phishing attempt using a seemingly similar vendor email can be detected by AI and reported.
ASC 606 mandates revenue to be recognized based on the satisfaction events rather than based on what has been billed. Organizations have different policies of recognizing revenue with different variations. For eg: in case of an annual subscription, revenue can be either distributed equally between periods or it can take the number of days in a month into consideration, which would result in a slight difference between say April (30 days) and May (31 days). Due to immaterial changes (like an addition of a new product in the subscription bundle), the changes in revenue recognition can be either retrospective or prospective. All these scenarios can have anomalies, where the revenue is not recognized in accordance with the organization policy. AI can detect these anomalies and report it to the revenue manager, who would then have the IT team check the configurations and correct it.
Conclusion:
In this world where change in the only constant, a forward-thinking CFO must take the plunge into AI and leverage modern technology in order to manage the finances of the enterprise and to avoid being left behind by competitors. AI is here to stay and will rapidly continue to modernize the office of Finance.
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