Application of Artificial Intelligence in Payment Processing

Artificial Intelligence (AI) is here for quite some time and is successfully being used in banking applications like Fraud Analysis and Customer Risk Scoring but with a limited scope. The prominence of AI in decision making has augmented with the advent of data explosion, big data analysis and internet penetration. Chatbots, a prominent development in recent times, are gaining widespread acceptance and adoption. Being a perfect example of artificial intelligence at work, Chatbots are able to understand customer language, leverage back-end analytics to respond to queries on real-time basis and deliver a frictionless experience to customers.

Payment Industry is on the cusp of reforms and players are eager to implement AI for efficient payment processing, increased Straight Through Processing (STP) rates, drive incremental enhancements to user experience, and gain the early mover advantage. There are many areas within payment processing where AI has a great potential to succeed. From a holistic viewpoint, AI can be applied in payment processing at two levels.

  1. Modular – At individual application level such as Fraud Analysis, Payment Validation, Payment Enrichment, Payment Repair, Selection of “Method of Payment”, to name a few. Currently all these applications are rule based. They are a “set of rules” deciding the actions.  The advantage AI brings here is the power of seamless decision making backed by deep analysis of payment trends, payment behavior, and historical data. It can drastically reduce manual intervention in payment processing and enhance STP rates. Tactical solutions such as Robotic Process Automation (RPA) can leverage AI to effectively manage routine operations .
  2. Overarching System – AI systems can monitor payment transactions from the point payment message enters the bank till it leaves the payment gateway by monitoring actions at a process level and suggest intuitive services and offers. With the access to feeds from financial market on latest trends and process improvements in other banks etc., AI systems can suggest suitable payment product for customer in terms of processing time, payment charges, and payment usage customized to customer’s activity pattern. For example, if customer is sending detail advice information within the payment message, AI system may recommend payment product that offer advice as an attachment. Such prompt tailor-made suggestions go a long way in customer retention and satisfaction.

Although AI has tremendous advantages and possibilities to improve existing product offerings, it also poses a great risk not only to the service provider but also to humanity at a holistic level. Recently Facebook had to call-off one of its AI program . The reason being chatbots developed for customer communication, created their own language which is not recognized by humans. The issue highlighted the need to address potential risks that AI can pose. In the banking industry, risk weighs more than the opportunities as any loophole can lead to irrevocable damage and adverse impact. Nevertheless the downside of AI should not be a hindrance to the adoption of the technology, as AI has the potential to revolutionize the financial services industry. Hence, it is crucial to embrace this change with implementing proper boundaries and strict controls in place.

Can AI outwit humans? What are the key measures and guidelines should companies keep in mind for a successful implementation of innovative AI solution? Share your thoughts and don’t miss to read my next blog on this

Manoj Apte

Manoj is a subject matter expert in corporate payments and is part of Payments Practice group at Virtusa. He has 18+ years of experience in industry and worked with many Tier-I banks in capacity of senior business analyst, Functional designer role. He has good understanding of high and low value payments and also has exposure to real time payments.

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