How new-age banking solution geared with AI can help make wise investment decisions
By Suman Gandham
Traditional banks have always been notoriously known for gathering user data on a mammoth scale, but not quite being able to put it to good use. Decades have passed since the digital revolution swept over the banking world and these banks are dealing with information at a tremendous scale which is waiting to be tapped into. But besides for some basic digital features, these solutions do not yield much, more so from a cognitive perspective.
However, today, it is safe to say that a financial revolution is under works. Married blissfully with high end technology, machine learning, artificial intelligence, Big Data analytics and statistically derived cognitive behavioural patterns, neobanks are setting out to change the way the world experiences money and what it does with it. With the new RBI regulations and guidelines for Account Aggregator (AA) licenses, the power of consent to data now rests with a customer. With AA acting as a conduit between the FIUs and FIPs, the tables are turning in favour of non banks to fully utilise customer approved data in a more propitious way.
Artificial intelligence sits atop this search of digital transformation as a catalyst offering a facelift for these traditional banking systems through scalability, automation, ease of use, risk analysis and decision making assistance which can lead to a banking experience tailored to each individual’s requirements.
Many financial management apps have been mushrooming around the world, with sky-high promises. Plenty of them offer to help users manage expenses, set daily budgets, incentivise bill-paying habits, recommend the most suitable investment plans and much more.
When talking about investment decisions, the data used by these existing financial apps is perhaps only the tip of the iceberg. Neobanks like Finin, in the meantime, plan to deep dive into the data stream and approach the problem from the bottom up. The sheer scale and quality of data allows such neobanks to draw highly intelligent market conclusions. These market metrics when juxtaposed with additional intelligence surrounding personality types, behaviour patterns, financial history, lifestyle patterns and all the other metrics that can be acquired using techniques in Artificial Intelligence and Big Data analytics – these neobanks are raising the bar very high with hyper-personalised investment suggestions and solutions that are not only derived from understanding a user’s spend history alone but by understanding his or her personality traits and lifestyle needs as well.
Investment fund frameworks combine rule engines along with predictive models to create investment portfolios that are aimed at maximizing returns during an up-trend in the market and to minimize losses during a down-trend. Artificial intelligence and machine learning offers the added edge of mimicking human judgement while retaining the disciplines of rule-based investing. Investment strategies employing such grounds to leverage market opportunities tend to perform better while reducing bias errors.
Neobanks are changing the way users will approach cliff-hanger questions such as ‘where to invest their money’ with smart recommendations that are ideal and best suited for their lifestyle, financial potential and future goals. Moreover, by taking scope of a customer’s investment potentials in advance, fund managers can now focus on high yielding engagements with them right from the word go.
In an era where data is king, neobanks promise to make the best possible use of all the user information available to reinvent investments and financial freedom like never before.
(Suman Gandham is the Founder and CEO of Finin. The views expressed are the author’s own. Financial Express Online does not bear any responsibility for their investment advice. Please consult your investment advisor before investing.)