Artificial Intelligence is easily applicable in anything that has a standardized system and less or no discrepancy or deviation. First, as an organized industry, banking runs on a set of regulatory guidelines and deals with numbers, it was only about time that it would board the AI bus. Secondly, there is this deviation angle.
As we fully realize the fact that anything handled by a human is prone to deviation or personal discretion; so to be vigilant, all inputs are to be taken with a generous pinch of salt. In other words, everything must undergo a reviewing pair of eyes. How about implementing a system that can auto-understand and auto-function and auto-verify without or with minimal human intervention (barring some very delicate cases)?
The research by Digital Banking Report that surveyed over 500 financial institutions globally showed that improving the digital experience for customers emerges as the top priority for about 71% of total respondents. Enhancing data analytics capabilities to identify customer needs (50%) comes second in the priority list. And finding ways to reduce operational costs (41%) comes on the third position.
Let’s focus on the area that is most crucial to banks in the age of cutthroat competition: Quick and reliable customer service that gives improved digital experience.
Robots Getting in the Race to be Brilliant Bankers and Astute Advisors!
In an age when our finger tips have taken over our communications, when starting from Hi to Bye and the entire in-between spectrum of trivial to serious exchanges depend on chat, I think it’s time for us to welcome them. I think even if we don’t welcome, they have anyway arrived, and arrived with a great deal of bang and bustle. Meet chatbots and robo-advisors.
Chatbots are text-based messaging systems that enable B2C interactions. Bots being agile, customizable, easily programmable, all-time available, and yet more economical than fully loaded banking apps, are winning the confidence with quite a pace. Well-executed and duly-monitored robots are assigned repetitive, basic, and time-consuming tasks. They are then gauged on their effectiveness and efficiency against their human predecessors who now will have a good time building and maintaining client relationship and solving more complex issues.
Though consumers from both emerging and developed nations are still wary of paying for anything with their mobile phones, as per Kantar TNS’s Connected Life 2017, the bright side however is: 44% people from emerging countries and 29% from developed countries have shown a thumbs-up to chatbots. 36% Indians say they are happy to interact with chatbots online.
Robo-advisors are ready to team up with their domain masters and about to present you bionic advices on how you should distribute your wallet share to gain deeper pockets! They too are AI agents raring to bring you real benefits. Here in banking parlance, benefits include real ROIs apart from those soft benefits like convenience, speed, and ease. These recent experts are ready to serve you with data-based advice on your long term investment plans and answer your short term investment doubts.
Banks are Gearing up to Make a Shift
One close look to see what has already been done. As per PwC’s 2016 Global Data and Analytics Survey of US financial services, in Banking and capital markets the use of Machine Learning algorithms have reached to 34% whereas in Asset and wealth management it has reached to 26%.
Most noted banks have already stretched out a hand to shake with AI. Needless to say that deployment of AI is no longer a question of why but only a discussion of when and more importantly a brainstorming of how, which can fit into their business strategy.
Last year Swedbank launched both on its website and mobile app Nuance’s NINA that could help quickly answer customer queries using intuitive analysis.
Bank of America uses a digital assistant called ERICA. It provides its users with financial propositions based on their transaction patterns through predictive analytics and cognitive messaging. From checking balances to making payments to saving money to lowering debt — she is all set to answer and advise.
Yes bank on the other hand came up with YES Pay Bot that allows financial transactions over a friendly chat with the customer along with answering queries and requests. It also has YES mPower bot taking care of loan products.
JPMorgan Chase has come up with COIN, Contract Intelligence, which would analyze legal documents and extract important data points and clauses. This would reduce the work of 360,000 hours to seconds.
Wells Fargo piloted AI-driven chatbot through Facebook Messenger platform and allowed users to provide their account information and reset their passwords.
Citi bank has invested into Feedzai, a global data science enterprise, which works in real time to spot and destroy possibilities of fraud both in online and branch banking.
State Bank of India extended a digital platform called SBI inTouch that uses AI such as IBM Watson.
HDFC Bank’s EVA chatbot is capable of answering millions of customer queries across multiple channels.
Over to You, Robots
Robots apart from handling operational processes have begun to yield cost reduction and enhanced customer experience with spot-on service and faster turn-around time.
In many banks they have been elevated to cater to other areas namely deciding on hiring and retaining staff, predicting probable delinquencies or defaults and devising measures for preventing them, recommending products for a specific customer base, forming marketing strategies based on certain preferences etc.
Banks know that adoption of algorithms is no longer a strategic move but only a survival one. In this space, the ones who swing the game away are the players who are either measured risk takers or early adopters; ideally both.
We bank on banks. Banks bank on robots. And to complete the loop, robots bank on us. Taking a leaf out of Louis Pasteur’s book, Fortune favors the prepared mind, I wish all the banks the power of real preparedness and not the half-hearted jump on the bandwagon.
Pratik works as a Senior data scientist at AtoS Syntel. Involved in various innovative projects and concepts, he applies a range of Machine Learning and Deep Learning algorithms to create and deliver strategic insights. As part of his wide range of assignments, he pieces together new technology trends with shifting business demands to bring about cutting-edge applications. Previously he was a Data Scientist at Synechron and a Consulting Staff Principal at Oracle. For over 12 years, he has been blending his analytical prowess and people skills to tap into the unexplored and less-explored business dimensions and convert them into value creators. Passionate about sharing his continual learnings, he is also a corporate trainer and a speaker at events. Pratik holds an MBA in Finance with Information Technology and a bachelor’s degree in Industrial engineering.