Artificial Intelligence (AI) will eventually redefine Banking, Financial Services and Insurance (BFSI) sectors.
Today, the inexhaustible growth in transactions and data from various touch points at any time makes business more complicated. The need to promptly process data and to act, react or decide in response, makes automation pivotal to business operations. In due course, even mere automation will cease to impart a competitive edge. Artificial Intelligence (AI) has stepped in as an important factor in strategic planning, governance and innovation and will eventually go on to be a significant contributor to growth. AI, undoubtedly, can stimulate demand because of its disruptive capabilities in enabling personalization, quality enhancement, productivity and time-saving.
AI platforms judiciously collect, track and analyze historical data, decipher patterns and then recommend relevant decisions. For the BFSI sector, which is plagued by shrinking margins, cyber threats, fraud, bad loans, regulatory pressures, and rising customer expectations, AI can help reinvent business models and bridge current gaps in productivity. There are case studies which are redefining the sector. AI has found application across various functions in BFSI - customer service, financial crime detection, loans management, credit scoring, investments management, claims processing, market forecast, to name just a few. Specifically, in banking, AI plays an important role in front-office (conversational banking, AI biometrics, personalized insights), middle-office (anti-fraud & risk, anti-money-laundering, eKYC), as well as in back-office (credit underwriting, smart contracts).
AI tools can identify sales opportunities based on customer interactions or behaviour patterns and can also facilitate cross-selling. Equipped with past information, payment platforms can encourage customers to choose their preferred payment method or one based on the highest reward points. AI applications now include personalized buy and sell investments decisions and also help reduce uncertainty, thereby presenting more accurate returns expectations. It is also helping build stronger fraud detection strategies to check financial crime, working across structured and unstructured data.
With conversations in natural language, Conversational AI has pushed the bar higher. AI with its conversational variant enables further personalization. It has elevated “conversation” to an omnichannel, common human-like interface across web portals, mobile apps, smart speakers, social media and third-party messengers, thereby enabling customers to interact with businesses either through chatbots or smart speakers or in-app assistants. These “Conversational Chatbots” serve customers 24/7/365 and enable conversations outside business hours. Transactions at customer’s pace and convenience is a prized differentiator today. It also frees employees from mundane and repetitive jobs. Automation streamlines routine tasks saving time and adding consistency and accuracy. Today’s automation platforms are more intelligent, bringing cognitive & machine learning technologies together. This is clear evidence of the unique value proposition that AI offers for the BFSI sector. In my opinion, banks need to scale up their AI investments.
The result of the above is that the business models in the BFSI sector will inevitably change, mandating Enterprises to reinvent processes and create a productive ecosystem. Cost efficiencies, ability to adapt to customer needs and niche offerings, will shape business. However, the roadmap to AI adoption is not without obstacles. Amongst various challenges, access to skilled talent, the right vendor, choosing the right use cases and models and the moral issue of jobs elimination due to AI adoption - need to be addressed. Finally, prioritizing AI investments over other business requirements will remain an uphill task.