Artificial Intelligence (AI) has been here for quite some time and is used successfully, but with a limited scope, in banking applications such as Fraud Analysis and Customer Risk Scoring. With the advent of data explosions, big data analysis and internet penetration, AI ‘s prominence in decision-making has increased.
Chatbots are gaining widespread acceptance and adoption, a prominent development in recent times. Chatbots can understand customer language as a perfect example of artificial intelligence at work, leverage back-end analytics to respond to queries on a real-time basis and deliver customers a frictionless experience.
The payment industry is at the height of reforms and players are eager to implement Artificial Intelligence for effective payment processing, increase Straight Through Processing (STP) rates, drive incremental improvements to user experience, and gain the advantage of the early mover. In payment processing, there are many areas where AI has a great capacity to succeed. AI can be applied in payment processing at two levels from a holistic viewpoint;
- Modular – At the level of the individual application, such as fraud analysis, payment validation, payment enrichment, payment repair, “payment method” selection, to name a few. All these applications are currently rule-based. They are a “set of rules” that decide the acts.
The benefit AI brings here is the ability to make seamless decisions supported by a thorough analysis of payment trends, payment behaviour, and historical data. It can reduce manual intervention in payment processing dramatically and improve STP rates. To effectively manage routine operations, tactical solutions such as Robotic Process Automation ( RPA) can leverage AI.
- Overarching System – AI systems can track payment transactions from the point of payment message entering the bank until it leaves the payment gateway by tracking process-level actions and suggesting intuitive services and offers. With access to financial market feeds on latest trends and process improvements in other banks, etc., AI systems can suggest customer appropriate payment product in terms of processing time, payment charges, and payment usage tailored to the activity pattern of the customer.
For example, if the customer sends detailed information about advice within the payment message, the AI system may recommend a payment product that provides advice as an attachment. Such prompt tailor-made suggestions go a long way in retaining and satisfying customers.
Although AI has tremendous advantages and opportunities to enhance existing product offerings, it also poses a great risk to humanity at a holistic level, not only to the service provider.
Facebook had to call off one of its AI programmes. The reason for the development of chatbots for customer communication was to create their own language that is not recognised by humans. The problem highlighted the need to address potential risks that could be posed by AI. Risk weighs more than the opportunities in the banking industry as any loophole can lead to irrevocable damage and adverse impact.
Nevertheless, as AI has the potential to revolutionise the financial services industry, the downside of AI should not be an impediment to the adoption of technology. Therefore, with the implementation of proper limits and strict controls in place, it is crucial to embrace this change.