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A Private Banker For Every Customer
With technology becoming more sophisticated, interactions are becoming intuitive and simple
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Digital banking is fast attracting interest and investment. An environment ripe for intelligent automation has emerged through technological advances in Natural Language Processing (NLP), Machine Learning (ML), and Artificial intelligence (AI), and the rapid transition to services accessed via published APIs. Interactions with consumers and back office processes alike are benefiting from phenomenal compute capacity and pervasive network speed, making consumer banking intuitive and accessible from anywhere.
Let’s rewind to the turn of the 19th century. Banks in the US were in their early days, and their customers enjoyed first class service. Picture a wealthy cattle ranch owner riding his autonomous vehicle, i.e., his horse to the bank, sauntering in, and then requesting the banker to transfer some of his funds to his daughter’s account. The banker instantly recognizes him and carries out the request. With that out of the way, the rancher thanks his personal banker and rides home.
Technological developments enabled banks to start automating record keeping and business processes, and then move on to improving the quality of interactions. Over the past 70 years, computers have grown in capacity and number. Initially, they were used for heavy compute operations. They began to perform simple banking transactions when Electronic Recording Machine for Accounting (EMRA) was introduced in 1955. In time, computers started processing both customer-facing and operational transactions. Lower cost and higher speeds made more sophisticated interfaces possible. The first browser, Mosaic, and Windows 3.1 entered the market in 1993, creating an opportunity to automate call center, self-service, and internal processing.
In the last 20 years, technological growth has driven the rapid increase of compute capacity and connectivity. Cellular service became widely available, with its speed increasing 40,000 times from 1G to 4G networks. At the forefront of the smartphone revolution were BlackBerry (2006) and iPhone (2007). The processing speed from the first models to iPhone 8 increased over 40 times. Computer networks supporting the Internet went from 100 kbps to 100 Gbps. In 2009, WeChat introduced interactive communication with automated systems, and then came Siri and Watson.
This convergence of technology advancements created a foundation for disruption in banking, because it can support almost all functions of a bank. Lead by ML, AI, and NLP, automation has gone from basic banking to business functions, and is now entering customer-bank interactions. The transition from rigid paper/screen to intelligent interface, and from reports to predictions and decisions is accelerating. This is made possible by the growing capacity of networks and computers, which helped us move beyond simply doing things faster. We are using this capacity to add intelligence, make interactions less brittle, and use cognitive processing in decision making. This is digital banking.
The pillars of traditional banking – the pre-defined structures and rigid processes – are gradually being knocked down to make way for agile architecture. By embracing new technologies, digital banking can bring back the straightforward exchange that once existed only between a customer and a private banker. The combination of APIs, Machine Learning (ML), chatbots, and Artificial Intelligence (AI) is driving this shift; one that calls up a less bureaucratic time.
Digital banking can help us bring back rich interactions, provided it can get past some hurdles. Many banks are still running on code from 50 years ago, and many customers are still wary of modern banking. Going from a more regimented traditional bank to an intelligent digital bank is a real journey. Banks can embark on it by examining their system architecture, and then seeing how it can be augmented in line with their business priorities. This will allow banks to interact with customers in a very different way, which is where the disruption is happening.
It all comes back to the one-on-one interaction we like to think the rancher enjoyed. Instead of a report on the numbers, you have customized guidance, where individual financial behavior is matched against individual financial goals. With voice to text functionality and sentiment analysis, the system can act as a private banker, helping customers with account opening, credit validation, loan offer selection, and other services. Banks are investing in digital banking to retain their customers, who are increasingly looking for the banking experience the rancher had.
With technology becoming more sophisticated, interactions are becoming intuitive and simple. The opportunity for disruption is in the return of that trust-based and easy way of banking. Only this time, the rancher will not be going to the bank. Instead, the bank is coming to the rancher, offering the same quality, personal service and trust.