AI and the art of the fintech possible

Artificial Intelligence (AI) will foster the most change of any technology Ravi Subramanian has seen in his 25 years in finance because it allows visionaries to dream big. Subramanian is the EVP and head of banking practice for Hexaware Technologies, a global technology and business process services company. Thanks to technological advancements like AI, what used to take four years to accomplish early in his career now takes four weeks.

That short development time frees creative minds to think of the possibilities that can transform industries. For Hexaware, that means applying data visualization and payment technologies in new and unique ways.

“It’s very exciting times because it’s been a while since I’ve seen a SaaS-based banking provider coming and becoming a mainstream player,” Subramanian began. “I’ve seen Mambu and Thought Machine occupying the thought processes of the CXOs in the banks. I’ve yet to see a full-blown implementation comparable to NFIS…, but still, it’s been ages since that part of the world was transformed, and I’m happy that I’m living in this era.”

AI and Payscopium, the three-stage future of payments

Compared to other technologies, Subramanian sees AI’s emergence as rapid. It will drive Payscopium, Hexaware’s three-stage vision for the future of payments. Today, we are in Payments as an Experience (PaaX). Coming as soon as 2024 in some places (likely a few years later in the USA) is Payments as a Lifestyle (PaaL). Money becomes programmable. Consumers decide how to apportion funds between housing, groceries and other necessities. Governments can program money through CBDCs. Only things the consumer wants will happen, with machines identifying our patterns and needs.

Invisible Payments is the final stage. Everything is done for us. As payments advance to this point, they will become more immersive across borders, businesses and consumers. The horizontal process will connect banking parts. 

The effects begin with unbanked and underbanked consumers being included because of their value, not out of sympathy. Financial and non-financial enterprises will be on the same level. That fosters business-led, people-focused transformations. The resulting payment democratization will bring 10X benefits to businesses.

“The Uberization of payments in the commercial payments area will be a decisive moment (for) the micro, small and medium enterprises,” Hexaware says in its Payscopium description. “Working capital will be replenished in real-time, increasing the pace and scale of innovation.

“Society is on the cusp of a sea change in experience, value creation and a betterment in the quality of life all around. Payments will be the driver for this transformed experience for a large segment of the population.”

AI’s fuel: The right data at the right time

Consumers sense the difference in service quality when they most need a credit card and their bank offers them a loan. They’re willing to commit if given the right product at that moment.

Subramanian said the problem boils down to the wrong data at the right time. Given the right data, a financial institution can offer young families college funds, holiday or home improvement loans or mortgages. If a customer is soon travelling to another country, they could be provided a Forex card.

The secret is connecting the bank’s structured data with user-permissioned access to social media sites, Amazon accounts and even Fitbits.

“If I combine the unstructured data which is out there on the Internet, which is publicly available or semi-publicly available, and tell the banker to superimpose it onto the structure data they have about me, like income and expenses, and give me something that I need,” Subramanian said.

AI is the glue in this process. It allows the bank to customize, but also score, the customer. The more reliable borrower gets a better rate.

Subramanian developed a model to test his vision, beginning by obtaining large data sets. He added bank data and spending information from credit cards and shopping accounts. The model gleans insights from exercise apps and even charitable donations. With this data trove, customers can approach their bank with a goal and receive the best product plan.

“This is what I feel is the power of AI when it is put into a business context,” Subramanian said. “Put to a business context and meshed with the right data, person and time, then AI is phenomenal.”

All roads lead to AI

Fearing aspects of AI, some banks take a different approach. They create proprietary machine-learning algorithms to assess credit risk and connect it to existing channels like mobile phones and websites. Slowly, they introduce AI because they’re scared someone will use that data and their competitive advantage will be erased.

These institutions focus on deep learning to derive intelligence from unstructured data. Generative AI will help them on the front end by collecting everything available and delivering actionable insights. Hexaware developed Pervasive AI in response. It synthesizes information from different areas of an institution to create new intelligence. 

In time, it combines with Generative AI to provide even more value. A system could automatically move products to save interest charges and inform the customer via an alert on their phone, watch, or whatever the gadget of choice is. Subramanian sees this as a reality in as soon as a decade.

Implementation obstacles

The transition can be hindered by silos preventing the structured data coalition throughout the institution. Departments compete against each other. Subramanian focuses on building bridges between these data islands in those instances by working with multiple departments independently. He brings that information together into an AI-based model that shows them how much differently data can be valued.

“That is when they realize the art of the possible,” Subramanian said.

Subramanian sees other factors holding some back from embracing AI. One is the importance of trust. They fear bringing AI into their network and then having information leak out.

Then, there is the lack of tangible results from big players embracing AI. Sure, there may be some early numbers from startups or digital entities, but some will remain gun-shy until some see positives from the higher levels.

The future is bright

Subramanian awaits the day when AI’s benefits filter down to the smaller entrepreneurs who need innovative banking the most. The big companies can afford to take risks like expanding product lines or adding locations. Most smaller businesses don’t have the cushion to do that.

AI can help make more calculated risks. Perhaps it’s working capital released on a real-time basis for a pizzeria from a bank with all their transaction information going back years. Based on that data, you lengthen the repayment period. That allows them to add a location or increase the menu size. Revenue increases and the business grows.

“That is what we are seeing that banks can do,” Subramanian said. “Private banking isn’t a niche thing anymore. Everyone needs private banking, and private banking at scale is the norm now.

“Hyperpersonalization is for anybody and everybody. It’s not just for the rich anymore.”

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