For organizations, transforming finance and accounting function via adoption of topical technology means improving how they pre-empt red flags around the financial transactions within the organizations.
In fact, prudent finance and accounting operability represents the single biggest challenge firms have to deliver on their priorities, according to a survey by Econsultancy.
What’s more, 45% of respondents indicated that embedding analytics &AI relevant as possible in the finance and accounting function is their key focus.
CFOs around the world are not asking if digital disruption will occur, but instead, what it means for their function. So the question asked in this article, is how can CFO’s leverage digital transformation wave using AI to advance their organization’s competitive position and improve performance of their function ?
With business around the world undergoing digital transformation, the roles of the c-suite is also changing. Perhaps most significantly, the role of the chief financial officer is moving from simply counting pennies to being a major driver of change within companies.
In the past, the role of the CFO was all about getting the numbers. That was 90 per cent of their time, but that is changing and now it’s about understanding the source of the number, understanding what created the number, and understanding the business drivers behind the number. A CFO then needs to try to make sense of the business drivers, and be able to present to the board what the outlook for the organization is, what the costs are, and what actions need to be taken.
This means that the CFO has to have a solid handle on data and analytics, and once they have that in their arsenal, they can become a strategic adviser to the business and they are able to tell the CEO things like what impact customer satisfaction has on the business.
I want to further highlight a few use cases showing how disruptive technologies such as artificial intelligence (AI) and machine learning will be used in the office of the CFO to increase productivity, simplify processes, and support decision-making, and aid in digital finance evolution:
Digital chatbots : Digital assistants for CFOs could impact analytics and the way they handle them. Today, almost everybody in Financial Planning & Analysis (FP&A) receives countless calls asking for information like, “What was our revenue in Q3 last year for this product? What has our growth been over the last three years for this line of business?”
Smart assistants like Amazon’s Alexa and Apple’s Siri can already answer questions on weather forecasts, stock quotes, and so forth, but what if they could provide the latest financial results and give decision makers instant access to information? A CFO could have a conversation with his or her ERP system using a digital assistant to get an immediate response or a clarifying question, without having to open a dashboard or dig into a database.
Risk assessments: When we assess commercial proposals for our services projects, we evaluate each project individually based on the customer characteristics – maturity, industry, size, current system landscape, and so on – as well as the complexity of the products to be implemented. To qualify this assessment, we depend on managers who have previously worked on similar projects. That can limit us to the individual perspective of those managers.
Machine learning could give finance teams and executives the power to access decades’ worth of projects, around the world, at the touch of a button. In levering these insights, teams could then develop a better-informed risk assessment, mapping the project against a much larger database of historical projects.
Invoice clearing: In finance departments today, accounts receivable or treasury clerks can often be challenged in clearing invoice payments, as customers often combine invoices in one payment, pay incorrect amounts, or forget to include invoice numbers with their payments. To clear the invoice, the employee then has two options: manually add up various invoices that could possibly match the payment amount, or reach out to the customer to clarify. In the case of short payment, the employee either has to ask for approvals to accept the short payment or request the remaining amount from the customer.
What if an intelligent system could help streamline this process by suggesting invoices in real time that might match the paid amount and, based on established thresholds, automatically clear the short payments or automatically generate a delta invoice?
Expense-claim auditing: Expense-claim auditing is another routine, transactional finance task. Finance teams are tasked with ensuring that receipts are genuine, match claimed amounts, and are in line with company policy. While state-of-the-art travel-and-expense solutions can simplify the process, a manual audit still needs to be performed.
Machine learning and AI technologies could improve this process, auditing 100% of all claims, and sending only questionable claims to a manager for approval. The machine could read receipts – regardless of language – to ensure that they are genuine, and match them against the policy.
Accruals: Artificial intelligence and machine learning also offer promise when it comes to determining bonus accruals. Today, teams have a myriad of factors to consider when determining bonus accruals. CFO teams look at current headcount salaries and bonus plans, and try to forecast all KPIs in compensation plans. From there, teams try to calculate the most accurate accrual (likely adding a buffer, to be safe). However, oftentimes, accuracy ends of being a matter of luck more than anything else.
By applying machine learning to these calculations, predictive analytics could serve as a valuable tool to generate unbiased accrual figures, leaving finance teams more time during closing periods for other activities that require human review and judgment.
Customer Journey: This is an area where the CFO is ideally placed to play a greater role in contributing to company growth and profits. His perspective on new customer acquisition, retention activities, customer development and predictive customer behavior models is crucial.
AI is what’s making all of this possible. With his new 360° vision and customer knowledge, the CFO can become a strategic business leader. Via AI and the breaking down of old company silos, the customer journey becomes everyone’s concern. And customer engagement wins its rightful place at the heart of business strategy.
The overall impact on jobs in finance: As these advanced technologies continue to penetrate the finance function, a new crop of skills are rising to the forefront when it comes to hiring finance talent. Routine, transactional roles will become less prevalent, while the need for strategic thinkers with cross-functional knowledge and technology prowess will be critical. Additionally, while transactional tasks will be fewer, digital transformation will require additional finance resources to be developed and supported, creating an opportunity to redefine processes and roles.
CFO’s, like everyone else, will have to adopt AI
In the future, it will be the companies that can harness AI that will set themselves apart. They will become fully digital businesses. Forward-thinking CFOs will help this happen. Because, by making AI accessible company-wide, they now have the power to unleash infinite company value.
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