Banks to Lead Digital Transformation with AI

Money matters to people and businesses alike and banks are the institutions which help them sense, comprehend and act in terms of making monetary decisions wisely. Banks have been there for us in times of need and have evolved themselves from time to time, transforming from a traditional paper-ledger based to computerized core banking. Today, this industry has ushered in the facilities of the internet and mobile banking for the consumer.

There is no other sector that is more focused on adopting innovative technologies like Artificial Intelligence (AI), as much as banks. Literally, every consultancy has derived their own research citing how AI would be the next big thing in banking and they’re all bullish on its prospects. PricewaterhouseCoopers (PwC) in its Fintech India Report 2017 cited that over 36% of large financial institutions are already investing in these technologies while almost 70% reported that they are planning to do so in the near future. We see a bullish trend on AI being anticipated to drive the future dynamics of the banking landscape.

Virender Jeet Senior Vice President, Sales & Marketing / Products, Newgen Software

With AI’s pace of evolution growing exponentially in the past few years, banks are now trying to try out this technology that can not only work as a human but can also perceive, think and act like one. In other words, a system which can analyse situations, derive decisions and interact with data, processes, and humans and at the same time learn and evolve in the process. All the more reasons for AI to succeed is that it’s not just one technology but a beautiful amalgamation of natural language processing (NLP), deep learning, machine learning, neural networks, and the likes which back and are backed by each other.

Imagine a bank having a technology in place which churns humongous amount of data to anticipate the unique financial requirements of each customer and apart from usual daily transactions, also gives financial guidance to millions of customers. Not only would it help customers gaining smartly by meeting their financial goals, but also perform their banking operations with utmost ease.

Let’s see how AI can be put to use by the banking sector.

Bots and Virtual Assistants

Bots have quickly become the new industry standard worldwide. While they may not be able to perform multiple or difficult tasks, many have found them to be versatile, learning the tricks of the trade. Indian banks are not far behind. The State Bank of India (SBI) for instance, has SBI Intelligent Assistant (SIA) which is a smart chat assistant which will help customers with everyday banking tasks and resolve their queries just like any other bank representative. It’s as good as having a 24*7 Personal Banking Assistant. Similarly, other banks have also come up with their respective chat-bots or virtual assistants like ICICI’s iPal, HDFC’s EVA, YES Bank’s YES ROBOT, Bank of Baroda’s Baroda Brainy to name a few. Most of them assist customers not only on the website but also on their respective bank’s mobile application as well. Banks are even introducing these bots for self-service across multiple branches.

Digitization and Process Streamlining

Banks today are looking at handing over the mundane process which requires low human-intervention to be handled by AI. What this means is that all the digitization work such as scanning of various documents and parsing information to the server can be left to the machines, given that it’s still in the perceptual phase. This will bring in more efficiency in the back-office and also minimize the chances of errors. Now, we all know how Business Process Management (or BPM) helps bank achieve operational efficiency by orchestrating various processes and enhance collaboration by integrating departments. AI coupled with BPM can make processes cognitive in nature, which can improvise through constant iterations and machine learning. In the longer run, this would simplify and accelerate banking processes and also help banks deploy employees into doing more productive tasks, increasing overall efficacy.

Risk and Fraud Management

Banking is vulnerable to cybercrime and fraudulent activities. But given the availability of big data, AI can be leveraged to harness it and find specific patterns and identify anomalies in transactions. With deep learning technology, it can add a layer of security by detecting possible fraudulent activities and nipping them in the bud, helping banks and customers alike. Mastercard, for one, has deployed AI across its global network leverages machine learning technology to increase approvals for genuine transactions and deliver overall better consumer shopping experience. So we see that AI can be put to use by banks in monitoring and reporting fraudulent activities through swift assessment of large amounts of data and alerting any anomaly well in advance.

There can be multiple other instances or use cases where AI can possibly lend a helping hand to the banking sector. This technology makes it possible to cater to the unique demands of customers and also reduce churn by providing them with highly personalized offerings. Such an intelligent product needs an extensive understanding. Hence the financial sector should first develop the requisite expertise. That’s one aspect. The second being availability of data and its ease of access. Thirdly, executives need to have the know-how of potential uses, implications, and challenges of this technology and have a fresh outlook towards it. The rest can be left to AI.