Artificial intelligence (AI) has become ubiquitous in today’s digital landscape, revolutionizing various aspects of our daily interactions. This influence extends to digital payments, particularly in the accounts receivable (A/R) and accounts payable (A/P) processes.
In this article, we’ll explore how AI impacts digital payment practices, the technology involved, its uses, advantages, and challenges of AI in payments.
What is AI in payments?
AI in payments means using artificial intelligence technologies to streamline and enhance various aspects of financial transactions and payment processes. These technologies leverage algorithms, machine learning, and data analytics to automate tasks, improve accuracy, detect fraud, and optimize decision-making.
For instance, AI-powered systems can automate invoice processing, payment matching, and reconciliation, reducing manual errors and speeding up the overall payment cycle.
Common technologies behind AI in payments
Understanding some of the most commonly used technologies behind AI payments can help one gain a deeper understanding of how AI affects the digital payments landscape.
- Machine learning: Machine learning algorithms can analyze and learn from data, even when it’s unstructured and in its raw form. These algorithms can detect patterns that might not be obvious to humans and use them to make forecasts and related predictions. They’re often used in fraud detection and process optimization efforts to improve efficiency and accuracy.
- Natural language processing (NLP): NLP refers to systems that can understand either spoken or written language. These capabilities are typically integrated with customer service functions, supporting chatbots or interactive voice response (IVR) platforms to answer billing and payment questions with minimal human oversight.
- Predictive analytics: These statistical algorithms leverage historical data — often in large quantities — to build viable predictions of future performance, such as forecasting transaction volumes or predicting the likelihood of bad debt.
- Generative AI: Generative AI technology can create text, images, or other forms of output, often in response to user prompts. This conversational AI technology powers virtual agents and other customer service chatbots in the payments industry, cost-effectively delivering high-value support.
What is the use of AI in payment systems?
The application of artificial intelligence in digital payments can vary greatly across the different functions and platforms used by buyers and sellers to complete transactions. However, regardless of the specific operation, AI is consistently focused on automating processes and improving efficiency, aligning with best practices in accounts receivable and accounts payable.
AI for invoice management
By leveraging AI in payment processing, you can dramatically streamline your A/P efforts. AI will automatically pull relevant information from incoming invoices and match these details against internal records (e.g., purchase orders and delivery receipts). Similarly, automated workflows can route these received payment requests through relevant approval processes, engage in payment reconciliation, and support reporting efforts.
AI for fraud prevention
Invoice fraud and related billing schemes pose a significant threat, capable of quickly eroding profits and potentially causing lasting harm to your business. However, AI-powered detection tools offer a considerable advantage in vetting the authenticity of incoming invoices. These tools can identify duplicate, padded, and outright fraudulent payment requests that might have previously slipped through undetected.
Additionally, these efforts can extend beyond individual invoices to uncover recurring or novel patterns of unusual buying or spending behaviors. Given the learning capabilities entrenched in most platforms, AI-driven anti-fraud measures can more easily keep up with criminals’ latest tactics and attack vectors.
AI for customer service
Perhaps the most common use case for AI or AI-adjacent technologies about payments is customer service chatbots, which help to resolve frequently asked questions without consuming your staff’s time or resources. These tools can routinely provide status updates regarding shipments or invoices, verify payment details and routing information, and even allow users to register disputes for further review.
AI for forecasting
As mentioned earlier, predictive analytics significantly streamline making informed forecasts about the future. AI excels at identifying previously unnoticed patterns within your historical sales and payment data. This valuable insight can enhance targeted marketing strategies for sellers, optimizing profit margins. Moreover, predictive capabilities regarding payment behaviors can inform credit extension decisions, allowing for more precise risk management.
On the buyer’s side, leveraging predictive analysis enables better planning and management of overall cash flow, improving financial stability and decision-making.
AI for process optimization
In process optimization, bottlenecks can swiftly accumulate, impeding payment workflows and even halting operations altogether. Pinpointing the root cause of these artificial delays can be difficult. Fortunately, AI can identify these underlying issues and offer recommendations on how to accommodate or adjust these workflows to accelerate payment efforts.
AI for security compliance
If you accept credit card payments — and want to continue — you need to ensure that these transactions remain secure and align with the Payment Card Industry Data Security Standard (PCI DSS). By integrating artificial intelligence into payment processes, you can enhance your internal security processes to mitigate the risk of fraudulent activities.
At the same time, AI can strengthen common know-your-customer (KYC) efforts by automating verification processes. This ensures that customers, agents, consultants, and distributors operate ethically and accurately verify their identities.
Benefits of AI in payments
1. Requires fewer resources
AI and associated automation are much more efficient than traditional, manually-driven processes. As the technology handles the repetitive tasks common in billing and payments, you can routinely cut labor costs by redirecting these workers to more strategic or profitable initiatives while reducing process timelines. At the same time, by isolating and removing potential bottlenecks, you can further accelerate efforts, doing more with less.
2. Enhances security
Detecting obvious fraudulent activity is relatively straightforward, but identifying subtle scams can be challenging. AI’s pattern recognition offered by AI can significantly improve the ability to pinpoint and address payment and billing anomalies promptly.
3. Boosts accuracy
The fewer people handling an invoice, the lower the risk of human errors occurring — whether transcription, calculation or otherwise. AI-driven process workflows can automatically extract data from invoices and compare invoices against purchase orders and receipts to ensure accuracy, reducing the need for manual entry.
4. Improves decision making
Accelerated processes, predictive analytics, and pattern detection capabilities make it much easier to consolidate, analyze, and distribute data in real-time. With this more nuanced and contextualized information, key stakeholders can minimize guesswork and make data-driven decisions to plan for the present and the future.
5. Strengthens relationships
Responding swiftly and creating a personalized experience for customers and suppliers is important. With AI-backed processes, you can often address support needs more quickly and with less labor. This frees up your staff for situations that require more nuanced care. This technology can also recognize customer buying patterns to put together targeted offers and product recommendations that better align with the needs and expectations of your shoppers, personalizing their experience.
Challenges of AI in payments
1. Still requires oversight
While you can offload mundane tasks to AI, humans must still review and approve any substantive decisions the technology suggests. Similarly, AI may sometimes fail to properly distinguish whether an error is due to an innocent mistake or a blatant fraud attempt, and you wouldn’t want to undertake the cost and potential customer alienation of a full-blown fraud investigation for a simple typo.
2. Invites regulatory challenges
The adoption of AI in payments poses a significant regulatory challenge. Due to AI technologies’ transformative potential and associated data privacy concerns, governments worldwide, alongside private industry groups, are implementing measures to regulate and standardize these platforms. According to the 2023 AI Index Report assembled by Stanford University, among 127 monitored countries, 123 AI-related bills were passed between 2016 and 2022 — with 37 enacted in 2022 alone. In the United States, 88 bills in total were proposed to the U.S. Congress over that same year.
These trends indicate a growing compliance burden for AI, necessitating vigilance in selecting platforms or tools that adhere to established guidelines. It’s crucial to ensure that any AI-powered solution you choose remains abreast of evolving regulatory requirements to mitigate risks and maintain operational integrity.
3. Varying costs
The cost of implementing AI in payments can vary significantly depending on the complexity and capabilities of the solution. AI encompasses many technologies, from basic conversational chatbots to sophisticated neural networks modeled after the human mind. Platforms may differ in their ability to understand context, handle technical language, or even mimic human interaction convincingly.
Regardless of the AI solution you choose, direct costs and expenses for integration, training, and automation are involved. One approach to managing costs is adopting a service-based model like Invoiced, which allows you to access AI tools without investing in and maintaining infrastructure. This strategy can help keep expenses down while still benefiting from AI technologies’ innovative capabilities.
Leverage AI in B2B payments with Invoiced
AI will be a game changer in business-to-business (B2B) payments, from automating the simplest verification process to guiding overarching enterprise strategies. Invoiced’s Accounts Receivable Automation software introduces a cutting-edge solution with automated payment matching powered by our proprietary CashMatch AI algorithm.
Integrated seamlessly with your bank feed, CashMatch instantly matches incoming wire, ACH, and EFT payments to corresponding invoices or balances, aligning them accurately with corresponding invoices or balances. This functionality ensures swift and error-free matches between unapplied customer payments and the correct account balances, enhancing efficiency and accuracy in payment processing workflows.
Schedule a demo today to see how AI can accelerate and transform your digital payments.
