How artificial intelligence is changing the face of banking in India?

In this age of machines, traditional banks find themselves competing with tech-savvy players, moving to adopt newer technologies like artificial intelligence to keep up. Artificial intelligence will empower banking organisations to completely redefine how they operate, establish innovative products and services, and most importantly impact customer experience interventions. In this second machine age, banks will find themselves competing with upstart firms leveraging advanced technologies that augment or even replace human workers with sophisticated algorithms. To maintain a sharp competitive edge, banking corporations will need to embrace AI and weave it into their business strategy.AI’s potential can be looked at through multiple lenses in the banking sector, particularly its implications across the operating landscape of banking. Focusing on some of the key artificial intelligence technology systems like: robotics, computer vision, language, virtual agents, and machine learning that underline many recent advances made in this sector.

Banks entering the intelligence age are under intense pressure on multiple fronts. Rapid advances in 

AI are coming at a time of widespread technological and digital disruption. To manage this impact, many changes are being triggered. Leading banks are aggressively hiring Chief AI Officers while investing in AI labs and incubators.  AI-powered banking bots are being used on the customer experience front. Intelligent personal investment products are available at scale.Multiple banks are moving towards custom in-house solutions that leverage sophisticated ontologies, natural language processing, machine learning, pattern recognition, and probabilistic reasoning algorithms to aid skilled employees and robots with complex decisions.

Banks today are struggling to reduce costs, meet margins, and exceed customer expectations through personal experience. To enable this, implementing AI is particularly important. And banks have started embracing AI and related technologies worldwide. According to a survey by the National Business Research Institute, over 32% of financial institutions use AI through voice recognition and predictive analysis. The dawn of mobile technology, data availability and the explosion of open-source software provides artificial intelligence huge playing field in the banking sector. The changing dynamics of an app-driven world is enabling the banking sector to leverage AI and integrate it tightly with the business imperatives.

Digital personal assistants and chatbots have transformed customer experience and communication. They are powerful enablers in freeing routine daily tasks and ensuring a personalised experience for customers. Virtual assistants and chatbots have many applications. Automated AI-powered customer service is gaining strong traction. Using data gathered from user’s devices, AI-based relay information using machine learning by redirecting users to the source. AI-related features also enable services, offers, and insights in line with the user’s behaviour and requirements. The cognitive machine is trained to advise and communicate by analysing users’ data. Online wealth management services and other services are powered by integrating AI advancements to the app by capturing relevant data.

Personalised wealth planning is revolutionised using AI. For example, if a customer is looking to buy a new car, the app will provide guidance for the proposed outlay and loan approval limits based on current expenditure and income. Chatbots too can be “employed” to act as customer service agents and serve customers continuously throughout a day. The tested example of answering simple questions that the users have and redirecting them to the relevant resource has proven successful. Routine and basic operations i.e. opening or closing the account, transfer of funds, can be enabled with the help of chatbots.

Online fraud is an area of massive concern for businesses as they happen on a large scale. Risk management at internet scale cannot be managed manually or by using legacy information systems. Most banks are looking to position machines or deep learning and predictive analytics to examine all transactions in real-time. Machine learning can play an extremely critical role in the bank’s middle office.The primary uses include moderating fraud by scanning transactions for suspicious patterns in real-time, measuring clients for creditworthiness, and enabling risk analysts with right recommendations for curbing risk.

Lending is a critical business for banks, which directly and indirectly touches almost all parts of the economy. At its core, lending can be seen as a big data problem. This makes it an effective case for machine learning. One of the critical aspects is the validation of creditworthiness of individuals or businesses seeking such loans. The more data available about the borrower, the better you can assess their creditworthiness.Banks are increasingly relying on machine learning to make smarter, real-time investment decisions on behalf of their investors and clients.These Algorithms can progress across distinct ways. Databecome an integral part of their decision-making tree, this enables them to experiment with different strategies and to broaden their focus to consider a more diverse range of assets. But one thing everyone in the Indian banking sector can agree on is that we need to utilize artificial intelligence to make banking functions easy and efficient.