The role of the chief financial officer (CFO) continues to evolve and expand into one of the most influential roles within an organization. All financial-related decisions, including technology investments, have to get the stamp of approval from the office of the CFO. Continued advancements in AI technology are making waves through the business world, and the CFOs most likely to lead growth are embracing the AI movement to supercharge business productivity and performance across the finance organization. And, according to the Vic.ai Maturity Gap Report, finance leaders identified accounts payable (AP) as the top priority finance function for implementing AI.
Invoice processing and payments are time-consuming and often manual, so they are a natural fits for the power of AI. But beyond eliminating repetitive data entry and mundane work, there are some appealing cash-centric trends on the rise for B2B payments when it comes to AI. Here, we highlight 5 interesting use cases that are already in practice and being adopted by progressive CFOs:
Cash flow forecasting and predictions for B2B payments
One of the most exciting benefits of using AI is cash flow forecasting. Because AI analyzes data and recognizes patterns, it can be leveraged to forecast cash flow and make future predictions. What’s even more interesting is how AI can adapt the forecasting models based on global events, economic trends, and business seasonality.
According to the Association of Finance Professionals, AI technologies are “excellent for doing scenario modeling organizations can act on with high levels of accuracy, or for predicting future trends or results with the greatest degree of probability.”
Data collection and analysis is a driving force behind an AI implementation, but the ability for the technology to process and make predictions from the data is what’s exciting. And because AI reduces manual errors and increases data accuracy, the cash flow forecast will be more accurate. The almost real-time nature of AI means information is readily available - which ultimately increases the speed of strategic decision making for financial leaders. What’s really interesting about using AI for cash flow forecasting is its ability to continuously learn and get “smarter” over time, the more data it consumes. This makes AI adaptable and scalable as the business grows and complexity increases over time, resulting in even cleaner prediction models and forecasts. And in current economic conditions where uncertainty thrives, reliable predictions are critical.
In a recent CFO Dive article Bernardo Miranda of Falconi writes, “AI algorithms can analyze vast amounts of financial data to predict trends, model budget scenarios, and provide actionable insights. This capability is invaluable in times of economic uncertainty, where predicting market dynamics and consumer behavior becomes crucial for financial planning.”
In B2B payment processing, AI can track and monitor invoice payment patterns and identify trends, predict change, but also act on that information. For example, let’s say you consistently pay a vendor for 5 months in a row, but then payments stop. AI will track these payments, notice the gap in payments, and then exclude the payments in future forecasting. Another example of this could be that you take advantage of an early payment discount on every invoice for a particular vendor over a period of time. AI will notice this pattern and the reduced outgoing payment, and will apply the discount to forecast your future cash flow.
Augmenting your B2B payment team
Challenging economic times, staff burnout, and manual, repetitive work are all contributing to talent shortages and exits in the AP space. And, less new accountants are entering the workforce. According to the IOFM Career Satisfaction Survey, 35% of AP professionals stated they are only moderately satisfied with their current jobs, with 11% only slightly satisfied. What’s interesting about the rise of AI in the business world, is the misconception that AI will only replace humans and eliminate jobs. On the contrary — AI is a strategic way to augment and enhance the team you already have. In the same IOFM survey, 44% of employees state that fully automated workflows (with no manual tasks) resulted in them being extremely satisfied with their role.
And CFOs agree. The Working Capital Tracker by PYMNTS.com found in a recent survey that 84% of business leaders believe that generative AI would have a positive impact on their workforces, and 97% said the technology would free their employees to take on a more thoughtful and creative role in the workplace.
Demystifying regulatory and compliance around B2B payments
Staying on top of all financial regulations and compliance rules is an ongoing challenge for CFOs and their teams. Since the financial crisis of 2008, compliance has become a serious matter, with a lot of scrutiny and requirements for organizations to adhere to. “Financial compliance is important in order to maintain the public’s trust in capital markets and the banking system,” notes the Corporate Finance Institute.
This means finance and accounting teams need to stay extremely knowledgeable of regulations and compliance requirements set by the Federal Reserve, the Security and Exchange Commission (SEC), and Federal Deposit Insurance Corporation (FDIC). They also have a duty to have Know Your Client (KYC) practices in place to prevent fraud, forgery, and money laundering.
This is where AI comes in for accounting teams. AI can help demystify regulatory and compliance by providing data-backed guidelines and in-process support. For example, AI can notice irregularities in financial data and flag anomalies for human review. AI can also consume regulatory documents, note changes, and notify team members for quick adherence to stay compliant.
In a recent article, Thomson Reuters identifies regulatory change management as a key opportunity for AI to make an impact for finance and accounting teams: “Many financial institutions receive hundreds of daily change alerts, which must be manually reviewed, prioritized, and delegated. AI can dramatically improve this process by improving reaction and adoption times, which could minimize fines and compliance risks.”
For B2B payments specifically, staying compliant in invoice processing is critical to reduce financial loss from fraud, prevent fines or penalty fees from mis-adherence, maintain trust to retain critical vendors, and quickly process digital payments.
B2B payment fraud detection
Payment fraud for B2B organizations is an ongoing and serious issue for B2B organizations. In a survey conducted by Trustpair, GIACT and Treasury & Risk, 56% of US companies were targeted by B2B payment fraud in 2022, and 82% of senior leaders considered fraud prevention a top priority in 2023.
Some accounting solutions have fraud detection capabilities that can identify abnormalities that could signal fraud, such as payment changes, new vendor payments, new bank accounts, inconsistent payments, unexpected international payments, and more. However, the points of fraud vulnerabilities can be technical with outdated or disparate systems, or related to process efficiencies, data accuracy, or human error.
AI applications for accounting can combat many of these challenges to make B2B payment fraud detection easier.
PYMNTs.com says it nicely, “The benefits of AI are hard to ignore. These systems improve payment speed and offer a superior tool for fraud detection. The technology can take customer-centricity to new heights and offer more accurate predictions than standard technologies.”
AI can handle many of the fraud detection capabilities previously mentioned, but works in real-time and consumes and analyzes data without setting up rules or templates. AI tracks payment transactions, compares data patterns, and identifies fraud signals. PaymentsJournal explains “AI keeps a continuous eye on the model to evaluate when adjustments might be necessary.”
Leveraging autonomous AI for B2B payment processing
Another trend in B2B payment processing is the concept of “AP autonomy”, or leveraging AI to work autonomously alongside the AP team. While basic automation can eliminate repetitive tasks and assists humans, it relies on template-driven software to define and conduct a prescribed series of detailed actions that are invoked manually. Automation cannot reason, is simplistic, and rules-based. On the other hand, autonomy is the next level of automation and is about adaptation. Autonomous technology is not hard-coded, and has the ability to apply logical reasoning, learns and then adapts, to remove humans from the process.
For B2B payments, autonomous AI solutions can process an invoice without human interaction from ingestion to payment, creating a true end-to-end workflow without intervention. Vic.ai offers an AI-powered AP platform that offers a true end-to-end workflow, allowing AP teams to work with a single vendor for maximum efficiency and accuracy. This also means a reduction in fraud risk with more electronic payments, a better ability to identify and leverage early payment discounts and increase cash flow through real-time AI data, and the option to pay invoices with check, ACH, and virtual cards — all from one platform. Less time processing and paying invoices also means more time to improve vendor relationships, negotiate better terms, and focus on more strategic initiatives for the finance team.