From Private Banking to Concierge Banking Powered by Analytics

By: Ramaswamy Venkatachalam, Managing Director – India & South Asia, FIS

The hype cycle is dead!

Much has been written around how any technical breakthrough goes through a whole cycle of acceptance, rejection, refinement before becoming universal. These cycles are more or less obsolete when it comes to their usage in the BFSI sector. This is the age of rapid prototyping or a “let’s see if it works” phase for the uninitiated. This represents an aggregation of technologies, from a wide variety of disciplines, into making the banking experience for customers better. Technologies such as machine learning, artificial intelligence, motion and eye ball tracking, advanced biometrics, activity tracking, lifestyle data tracking, human machine interaction data, advanced photography, highly specialized mathematical algorithms – were perhaps earlier applied as part of artificial intelligence.

In this paradigm, one common thing which no one can deny is the gigantic rise of collected streaming and cold data. BFSI players have realized the importance of using data for competitive advantage and hence, are spending billions in storing them over in-house or cloud based storage. The first part of the puzzle is slowly taking shape. But what about the second part? The part where this data starts making each customer experience different, and helps put a healthy multiplier to the top and bottom line of the firm.

Imagine this: A customer is driving peacefully from town A to B, in his newly acquired self-driving all-electric car. His head up display automatically provides personalized greetings from his bank and a virtual concierge who helps him book tables for the lunch meeting, and get the last minute deal for a business lunch. Additionally, he is reminded of a new investment instruments which his idle money can be invested, with just one affirmation. He is automatically enrolled into a travel and breakdown insurance plan, which charges by the hour and adjusts the rates based on traffic, news feeds and his driving style. At the next pit stop it even connects to the coffee outlet and pre-orders his cappuccino.

Now let’s imagine the other end of the spectrum too. A migrant worker from UP reaches Mumbai for the first time. A virtual assistant connects with him and provides the top taxi hailing app recommendations. It also helps connect him to a few brokers who can either help him book a hotel room or help him find a rented property. It also starts automatically covering him for eventualities like theft of luggage, loss of health, travel, etc. rapidly readjusting the same, based on his pattern of spending and activities. Later on, when he receives his first salary, it reminds him of remittance options available for his brother’s college fees.

So what are we seeing here? An all pervasive experience which is not just a brash attempt at “selling” stuff to a customer, but a concierge based experience which is both friendly, intimate, accurate and seamless. This is over and above the mindless notifications that one gets on his phone that rarely help.

So what will it take to get this done? Frankly none of the touchpoints described above can do this alone (the car, fuel station, coffee outlet, insurance, the bank, telecom, etc.). There needs to be central intelligence which analyses every facet of a customer’s life, and rapidly identifies inflections of interventions which can be directly linked to either incremental goodwill (to induce stickiness) or revenue. This central intelligence would be able to ingest a wide variety of data, and rapidly build out interconnected data sets which can then be used for throwing out information, offers, and actions to the end customers. There also needs to be an interaction manager, which will continuously push out these across multiple channels, partners and apps. An example of the same would be identifying that while on a business trip, the customer prefers to book an 8 am flight, stay near the business district and prefers a non-smoking room in which he sleeps for a minimum of 7 hours, which improves his lifestyle and hence his insurance premium pay-out.

Banks around the world are trying to create such engagements with the customers. Some prime examples are mBank in Poland and Atom Bank in the UK. Closer to home DBS India is trying out AI based interactions with their customers for things like service and advisory. Multiple start-ups have sprung up in the country which promise to aggregate financial products and services around and intelligent AI engine. One of them even claims to be a virtual wealth advisor! I predict, these disparate services will soon be absorbed as standard offerings by banks. FIS is in the thick of creating that future.

The future is already here as banks have this collective data. Customers are already deploying products which can churn out risk assessments, key life style indicators, actuarial, marketing and promotional offers, CRM for managing partner orders, loyalty and tie it all with a robust multi-channel payment back bone, to provide a seamless experience to the customer. With the central intelligence system that’s at the heart of this endeavor; this includes an industry strength data hub, and open source big data churning engines which will pull out the nuggets of interest equivalent to a gold mine for the customer.

Whoever said knowledge is power, wasn’t way off!