.png){kind=logo}
Banking has seen major changes over the past few decades. From traditional banking to digital services, cloud technology, and now artificial intelligence, banks have continued to adopt new technologies to improve their services and meet changing customer needs.
AI is now becoming the next major step in this journey. Unlike traditional software that follows fixed rules, AI can identify patterns, make predictions, and support different actions based on the information it receives.
In this episode of the Analytics Insight Podcast, Ranga Reddy, CEO and Co-founder of Maveric Systems, talks about his 25-year journey in banking technology and consulting. He explains why Maveric Systems has remained focused on banking and financial services, how AI-first banking is different from digital-first banking, and why banks need to connect AI adoption with clear business goals.
Ans: We started Maverick with a single objective of focusing on the banking and financial services vertical, and over the last 25 years, we held to our decision to be a single-vertical-focused firm. Apart from being similarly focused on banking, we also thought that we should actually be working largely on changing the bank because in banking technology you normally hear two terms: change the bank and run the bank.
So, singularly focused on banking, prioritizing transformation, operating both on the business side and technology side has been the kind of focus that we kept over the last 25 years, and in order to keep ourselves relevant to the customer that is the end-using bank, we normally thought that we should have a kind of a competency that is layered.
Ans: I worked in various consulting roles in India and in 2000 we thought that we have done enough of consulting wherein we advised others we thought that we should be in a position to use our own insights and experience to build a firm and by virtue of having similar like-minded people around me I was able to put together a five-member team primarily from consulting backgrounds and over the last 25 years five of us have been at the helm of affairs at Maverick taking various roles based on the context. At this point, I play the CEO role. Primarily, I look at the sales function, which is primarily the growth-oriented aspects with regard to existing accounts or new accounts.
Ans: At a high level, most software programming has been rule-based. That is, you code a rule into the software, and it follows those rules, and it's in a portion to deliver a certain outcome, and to a large extent those rules are sometimes hard-coded, sometimes are configurable. In the AI-first world, basically we have the ability to get the software to observe a pattern, and based on recognizing certain patterns, it can initiate different sets of actions.
Having said that in the AI first you have some kind of a predictive analytics is something that you've been hearing about that becomes far easier to execute or far more reliable in execution. So if I really need to be making it a little simpler in the beginning, we had what we call digital-first, which is almost in the dot com era that you were probably 20 years back.
Ans: Digital-first banking was all about channels, that is, how you can reach customers and how you can service customers in a seamless manner by digitizing the front-end systems, the middle office as well as sometimes even the back office. Then came your cloud-first or cloud computing maturity, and because of that you had certain other advantages with regard to actually not depending on on-prem but having a combination of on-prem as well as cloud. Now AI-first is feasible primarily because there is a certain degree of maturity in digital and cloud, and there is also a reasonable amount of maturity with regard to data.
Ans: For example, in lending, three parameters mean a lot to the business. One is the cost of customer acquisition. The second is the speed at which you can acquire customers. The third one is, in terms of how you actually service the customer, servicing the customer will include how you are in a position to manage delinquency.
So it will be a bunch of use cases that you need to put together in order to achieve one or two key business parameters or performance indicators. If you approach it from that angle and have a medium-term kind of plan, then you can see the real impact.
To know more, listen to the full podcast.
