By Milan Ganatra, CEO and Co-founder, 1Silver Bullet
Ray Kurzweil, a famed American inventor and futurist who is most known for his Law of Accelerating Return, once said that the 21st century will not experience 100 years of progress, instead, it will be more like 20,000 years of progress. With the unprecedented advancement of technology 4.0 of the fourth industrial revolution, as it is known, this estimation is not a hyperbole. Cutting-edge tech such as the internet of things (IoT), Artificial Intelligence, automation and cloud computing are changing our world, this includes the financial services sector that is seeing a seismic revolution in the way it functions.
From banking to insurance and loans to stocks, technology 4.0 has been leveraging the power of automation and AI to bring about positive disruptions across all parts of the globe. In fact, according to global management consulting firm McKinsey, there is an impending second wave of automation and AI yet to hit the financial services world wherein machines and software bots will execute 10 per cent to 25 per cent of tasks across the banking sector.
One of the primary examples of the tech 4.0 led revolution in the financial arena would be Robotic
Process Automation (RPA) in banking. The primary aim of RPA in banking is to assist making the repetitive tasks in banking easier and more streamlined. It also effectively frees up the workforce from mundane and monotonous tasks and gives people an opportunity to focus on higher-value tasks and projects. So whether it is on-boarding customers through KYC processes or generating fraudulent transaction reports, RPA can help make all these processes easier. It has the capability to peer through lengthy compliance documents, extract information, spot errors through character recognition, cross-reference information and much more.
What’s next for AI in finance?
The goal of artificial intelligence, no matter what field it is applied to, is to create uniquely personalised experiences for consumers that are attentive and almost tailor made to an individual’s need. To this effect, the next step for AI in the world of finance will be to create seamless digital experiences for users through intelligent UI and UX platforms and much more. User interface platforms for mobile banking apps do not just need to be easy to use and basic in nature, but need to constantly learn from their user’s behavior. Learning with the help of deep learning AI models has the potential to make digital banking technologies almost sentient, thereby making an interface perfectly suited to each and every person.
Take for example a mobile banking app being used by a first-time elderly user, if the UI/UX is created intelligently enough to process this customer’s details, then the app goes into a default customisation mode and offers options such as audio assistance, enlarged keyboard icons and much more. Similarly, even though a large part of stock trading today is determined by computer algorithms, not all money advice platforms are designed in a gradient manner to assist users with varying levels of financial knowledge. Imagine if an investment advisory app could know whether a user is a novice investor or a seasoned one; financial advice, stock options and much more could all be tapered according to a particular user’s level of financial understanding.
In addition to formulating intelligent interfaces for banking services, technology 4.0 can assist in the creation of much-needed common protocols. When the National Payments Corporation of India introduced the Unique Payments Interface (UPI) in 2016, it was a novel experiment in integrating financial services in India, and it worked! UPI today functions as an efficient umbrella under which thousands of real-time and inter-bank transactions take place. A similar tech-driven common protocol can be extended beyond the payments sector and be applied to lending, insurance and investments.
With the novel coronavirus pandemic raging on and ancillary health services being stretched to their limits, integrated protocol creations between pathology labs, hospitals and insurance companies for example, could help streamline processes. Instead of customers being swirled back and forth between path labs and insurance companies, test results could directly be uploaded on a common server that an insurance company could access using Health ID, relieving customers of tireless rounds of email communication. Such an integration of services could also facilitate better risk analysis for insurance companies wanting to comply with norms for pre-existing conditions etc.
Tech 4.0 is thus poised to fuel a myriad of changes in the financial sector because there is a real possibility for better and more personalised customer engagement, and it is most important to remember that what makes automation more appealing is its minimal additional infrastructure requirements and low-code approach.
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