The financial services sector is one of the biggest sectors to benefit extensively from AI. Availability of large and varied datasets, an existing technology-driven infrastructure for Banking & Financial Services and of course, a billion-strong market makes India a hugely exciting prospect for any kind of financial innovation. India is now one of the world’s leading destinations for fintech deals in Asia and houses the second largest number of fintech startups after the USA. As of 2020, India has 2,174 fintech startups, with payments and lending gaining the highest share, followed by wealth management and personal finance management.

Largely, fintech’s early days in India were marked by digitized payments and e-wallets. Banks and other established financial institutions remained wary of largescale deployments but couldn’t turn away from the allure of data science for too long. Presumably, there were more service providers, experts, developers and technology companies that were keen on taking offerings in the financial services space to the next level as emerging technologies like AI gained more popularity. Soon, credit underwriting, fraud detection and loan disbursement among other pertinent use cases started gaining traction as fintechs began experimenting with innovative financial solutions with a population that was clearly ready to elevate their customer experience quotient.

And today, wealth management is poised to benefit from the transformative power of AI.

Typically, asset or wealth management in India is a deeply personal activity. Indians have long preferred a personal touch when it comes to financial planning and investments – a generation of Indians made their wealth working as LIC agents, and personal wealth advisory was a forte of old-school bankers whom generations of Indians developed deeply personal bonds with and trusted with their life savings with. These aren’t relationships to take lightly, and casually replace with robot agents.

But India is truly a breakout market when it comes to financial services. The strides being made in payments and lending has bolstered the sector to push the boundaries further. A NASSCOM-KPMG report states that the Indian fintech software market could double to $2.4 billion by 2020. Global AI spend in 2018 would touch $19bn, and banking alone would account for 17% of this share. Specifically, entrenched financial institutions are extending their AI capabilities to provide predictive, prescriptive and descriptive analytics, driven by machine learning models and cross-pollinating different kinds of data.

Why is AI vital to wealth management?

As mentioned earlier, it is hard to replace a deeply personal bond with a wealth advisor and blatantly trust a machine to make hefty decisions on money. But humans have their limitations too. Today’s customer has multiple data points – Aadhaar, financial statements, bills, loan documents, tax statements – which etch a detailed picture of his financial health. It is impossible for human agents to keep track of all these data points, parse and process them intelligently, and make informed suggestions for investments – and for multiple customers.

Enter AI. Indian companies – from fintechs to banks and investment management houses – are keenly aware of this personal element to finance and are working on models that can eliminate human intervention in monotonous data processing tasks and focus their energies on the actual task of managing relationships. With markets having opened up investment options including stock options, mutual funds, health and life insurance schemes, bonds, as well as the government offering lucrative investment options with tax breaks – the average advisor has a lot of keep track of as his customer portfolio keeps growing exponentially.

Now, the value of AI has progressed from data parsing and processing to augmented advisory through conversational chatbots, prescriptive and descriptive analytics to make accurate, detailed predictions, automate portfolios and provide recommendations to balance out one’s portfolio.

Scanning the wealth management landscape

There is no dearth of solutions in the personal management sector, and there is an element of AI and machine learning being applied across the spectrum. Startups are geared to leverage this under-served sector of AI-based personal wealth management. Portfolio management service Upside AI that relies on artificial intelligence and machine learning (AI/ML) algorithms to invest in the Indian stock markets. The company claims to have delivered about 71% cumulative returns to the investors registered on the platform since its official launch. It further claims that its assets under management (AUM) has grown over 10 times in the last one year to over ₹55 crore with funds from several high networth individuals (HNI) and family offices. Walnut App, acquired by Bangalore-based Capital Float, is a personal finance management app that uses AI to ascertain user expenditure behaviour and spending patterns. Coverfox uses AI algorithm-based insights to allow users to compare and choose from a range of plans across top insurance companies.

Meanwhile, legacy financial institutions too have made some commendable progress with AI. A report by MIT Sloan Management Review outlines some standout examples of companies leveraging AI for financial planning. US-based Wealthfront has offered only digital interactions since its founding in late 2011. The company’s digital-only focus is consistent with fairly extensive use of AI, says the report. Based on one analysis, Wealthfront uses AI in some ways that other robos don’t. The client’s answers to a risk assessment questionnaire are translated into a customized investment portfolio of cash and exchange-traded funds (ETFs) via AI. Its algorithms track client spending and saving behaviors and provide personalized recommendations to help them achieve their financial goals. Vanguard’s Personal Advisor Services isn’t very gung-ho on AI, but does utilize AI to conduct risk assessments on portfolios – however, not without a human agent involved in these transactions. For over 10 years, Morgan Stanley has been working on its Next Best Action system to provide its financial advisers (FAs) with insights to present to clients. This system uses machine learning to identify investments of interest and relevance to particular client. Jeff McMillan, chief analytics officer at the company, put it in an interview, “We have a very sophisticated machine learning algorithm to identify topics of interest to clients. But in the end, financial advising is a human-based game. If all the system does is remind them that the adviser is there and looking out for them, that is often enough.” McMillan said that financial advisors who use it are more efficient — because coming up with relevant investing ideas is much quicker with the system — and clients are more engaged.

It’s a new world in finance and there is no escaping the allure of AI. For companies, this is the next billion-dollar opportunity and benefits are tremendous to pioneer digital financial services and solutions. For customers like you and me, this is the definitive banking experience, very unlike what generations prior were accustomed to. It brings with it a slew of benefits but like any new technology, there will be some initial hiccups – ranging from inclusion to implementation. Either way, there’s no turning back.