The future of AI in payments is already here

The strongest case for bringing artificial intelligence-powered technology into the electronic bill payment and presentment (EBPP) space stems from the reality that, in some ways, it is already here. Many of the buzziest applications like machine learning-powered customer service chatbots and AI-written content are continually developing and still a ways off from being called perfected. But there are other ways AI tools are already quietly powering some facets of the EBPP industry.

The EBPP industry is still in the earliest stages of implementing these tools. By working to understand the reality of AI in the EBPP space today, executives seeking to find the most effective uses of AI and forecast the future of the industry can both reframe their current perspectives, and calibrate their expectations and strategies for what’s to come. The areas in which AI solutions can be most helpful as they grow more advanced may not be the most headline-grabbing, but they will make a significant impact on the industry.

EBPP companies are already leveraging AI

The conversation about harnessing AI has -- understandably -- been largely focused on and influenced by the most radical possibilities, which are either exciting or concerning, depending whom you ask. In the midst of all the chatter, it can be easy to forget that there are areas where AI is already in operation. Across the EBPP space, I am seeing increased implementation of AI-powered tools to support functions such as:

• Logging backend systems activity for record-keeping and reference purposes
• Monitoring that activity to note deviations that may indicate problems
• Alerting security teams to deviations in standard activity so they can assess what actions (if any) should be taken
• Analyzing the activity data collected in the lead-up to a problem, to understand what happened and prevent similar issues in the future

While many of the flashiest use cases for AI being discussed today are directly consumer-facing, multiple organizations in the EBPP space have thus far used these tools to help internally streamline the experience offered to customers. Unlike AI tools that operate on the frontend, these use cases are necessarily unnoticed by customers -- but even if they don’t notice the AI, they do notice the immense benefits these tools bring.

Investing in these areas allows companies to test and fortify the resiliency of their platforms. It also allows them to explore and hone AI implementation, training, and security measures. As AI tools continue to move to the forefront of the modern tech stack, companies must increase focus on AI research as well.

The AI solutions of the future

Creating an even more resilient platform

While EBPP organizations are already beginning to leverage AI tools to increase platform resiliency, there is opportunity for further development. This is especially true when it comes to the completion of tasks that are tedious, rote, and otherwise a strain on human attention and capability. Data collation and preliminary analysis is a realm ripe for AI optimization.

One example is invoice matching, which requires an immense level of attention to detail. Many organizations currently run this functionality on a homegrown algorithm that is built to meet the organization’s precise needs. But such organizations face limitations when it comes to the tool’s limited capacity for organic improvement. AI has the ability to not only accurately parse and rapidly cross-reference data, but also to improve itself in the process. In this way, it can simultaneously increase the speed and accuracy of the invoice matching process, along with other functions that require parsing a large swath of data.

The ability of AI to integrate new information into its operation can also make it a potentially useful tool for enhancing platform security, always a serious concern in the EBPP space where customer information privacy is paramount. Because AI can familiarize itself with ordinary customer behavior patterns, it will be able to notice and flag a transaction that appears out of the ordinary, more quickly and accurately than current systems.

Continuing to improve the customer experience

One of the most commonly discussed possibilities, the use of AI tools to manage customer service interactions, is popular for a reason -- customer support is often a stressful touchpoint for customers and companies alike. Powering the experience with AI is an extremely promising concept.

Many of us have had the experience of interacting with an automated chatbot on a customer service page that exchanges a few quick messages before quickly shunting us to a lengthy FAQ page, or connecting us to an overwhelmed human rep. More advanced AI tools will be able to provide more meaningful assistance, by parsing the relevant information available in an FAQ and helping a customer apply it directly to their issue. This use case can free up time and resources for team members to focus on innovation and problem-solving, and give consumers a less stressful experience of the occasionally fraught process of bill payment.

Centering humanity

The most exciting future applications for AI in payments are likely to proceed in the manner already established by current applications: They will be implemented strategically in ways that genuinely boost customer experience and improve team workload. Rather than focusing on the flashiest options, companies are likely to see benefits when they apply AI solutions to more rote and tedious tasks, and to those that allow them to save their team’s time for specialized tasks that require a human touch. Much like the current uses of AI in EBPP, future uses will support and complement human operations, rather than replacing them. An ideal future for AI technology in the EBPP space will look like the present, in that it will be about continued emphasis on humanity.

Image credit: BiancoBlue/depositphotos.com

Ramesh Kandukuri is Chief Technology Officer, Enterprise Solutions, InvoiceCloud.