The Indian Financial Advisor in the Robo Suit

Introduction

Financial advisory services have passed through phases of digitalisation and now embrace automation through artificial intelligence and machine learning. This shift started in the US and has spread around the globe. Startup companies initially developed the robo-advisors. Then, we saw the geographical expansion, acceptability, and never-ending concerns about this disruptive market innovation. This new avatar has gained popularity because of the low-cost model and customer profiling-based portfolio management services.

India\'s stock market has achieved a market capitalization of listed firms amounting to USD 3.99 trillion (CEIC Data, 2023). The world economy focuses on this developing country, which is predicted to be the fastest-growing economy (World Economic Forum, 2022). In developing financial markets like India, the people are not yet fully utilizing the existing financial advisory mechanisms owing to many issues like cost structure, conflict of interests, low personalization, lack of fiduciary duty, etc. The emergence of robo-advisory services promises to solve this situation (Ji, 2017). The current \"Account Aggregator\" framework of RBI widens the scope of robo-advisors in India. The total assets managed by robo-advisors are expected to reach USD 33.49 billion in India, by 2027 (Statista, 2023).

The question arises as to whether the existing financial advisory system in the country fails? Can it overcome these issues with the incorporation of technology? Can the newly emerged AI embedded systems elevate or resolve the issues in traditional services?

The traditional and AI based robo-advisory services are analysed based on the following five aspects: Conceptual, Functional, Technical, Emotional and Regulatory.

Conceptual differences

Robo-advisors are digital platforms that comprise interactive and intelligent user assistance components, using information technology to guide customers through an automated financial advisory process. Robo-advisors differ from traditional advisory services in two conceptual levels: customer assessment and customer portfolio management. Robo advisory services are based on the theoretical underpinnings of Joseph Schumpeter\'s (1942) Innovation Theory, Everette Roger\'s (1955) Diffusion of Innovation Theory, and Harry Markowitz\'s (1952) Modern Portfolio Theory (Clarke, 2020). The arrival of Robo advisory services as an alternative to traditional financial advisors promised to bring value addition through quality portfolio management, rebalancing, and added benefit of tax harvesting. This process is designed using the mean-variance analysis suggested by Markowitz.

Conceptually, the robo-advisors have evolved from generation 1.0 in 2008 to 4.0 in 2023. They have raised from suggesting pre-developed portfolios according to the risk profile of investors evaluated via an online questionnaire to sophisticated AI algorithms which can adjust investors\' asset class, in real-time (Hasanah et al., 2023). Robo-advice is an umbrella term that refers to a broad spectrum of online automated tools and algorithms to determine financial or investment decisions for an individual\'s portfolio (Lee, 2020).

Functional differences

a. Fully Automated Customer Profiling and Investment Process- The robo advisory system follows Markowitz\'s Modern Portfolio Management Theory while developing portfolios. It requires the advisor to obtain customer characteristics and develop a well-diversified portfolio to suit the risk and expected return. Also, the theory requires continuous monitoring and corresponding rebalancing to meet the changing market conditions (Clark, 2020).

For this, robo-advisors provide an online questionnaire to collect investor data about personal characteristics, risk profile, financial knowledge level, investment goals, investment horizon, expected return, tax conditions, etc. Then, inserting this information into the computer algorithm helps to develop a portfolio. AI-enabled systems ensure portfolio monitoring and rebalancing.

The above process is carried out by the traditional advisor via face-to-face interaction without following a standard questionnaire. Even though portfolios are developed, they fail to do rebalancing. Most research has pointed out the lack of monitoring and improper portfolio turnovers by human advisors.

b. Investment Psychology Investment strategies are often executed through Exchange Traded Funds (ETFs) which will ensure that costs are lower. Most robo-advisors follow a passive mode of investment. Hence, these products require no or less active portfolio management. A few invest in equities as well along with bonds or even gold. In India, the robo-advisors are primarily investing in mutual funds as the popularity of the same is more than ETFs.

c. Cost structure The most attractive feature of robo-advisors is its low-cost structure and no or low minimum investment requirements. Even though fees are charged as a percentage of assets managed in countries like the US, in India, either it is free or a flat annual fee with fixed charges per transaction is followed (Groww, 2023). Also, most of the robo-advisors invest in the ETFs which have a low-cost structure. Certain robo services keep their minimum investment as low as Rs. 400 or even without such a condition. All these make it a considerably lower-cost option.

In India, as the robo-advisors are in their evolution stage, they maintain either a free or flat annual fees along with fixed charges per transaction.

Contrary to the above fee structure, traditional advisors, or full-service brokerages charge heavy fees ranging up to 2.5% of the transaction value or a flat fee on assets managed, not exceeding Rs.1,25,000. Hence, the use of robo-advisors can draw a large number of unreached investors who keep away due to burdensome charges.

d. Performance-Performance expectancy has a positive influence on the adoption of robo-advisors (Gan et al., 2021). The performance of robo-advisory services has been evaluated through the following elements:

• Return generation The portfolio performance of robo-advisors has shown varying results when compared to human advisors specifically during the crisis time periods (Harrison and Samaddar, 2020). The performance among robo-advisors also varies based on the portfolio management techniques employed (Puhle, 2019).
• Diversification Most of the investors do not have a proper diversified portfolio. A well-diversified portfolio helps to earn better returns and ensures a risk-adjusted portfolio. But in the traditional system, this benefit was enjoyed chiefly by the high-net-worth individuals. Robo-advisors are in a position to improve the diversification of these undiversified portfolios. Sometimes, using robo-advisors increases trading, resulting in bad performance (D\'Acunto et al., 2019).
• Portfolio rebalancing Robo-advisors continuously monitor both the investment accounts and market conditions and brings in the required reallocations considering the risk profile of investors. Clients of traditional financial advisors have the grievance that there is a lack of proper account monitoring mechanism resulting in missed opportunities.
• Debiasing-Robo-advisors do not work on emotions. It increases the cognitive capabilities of investors. Research has identified that robo-advisors can reduce biases like disposition effect. Unfortunately, these biases cannot be fully eliminated.
• Tax loss harvesting - In India, taxes are a concern to every investor affecting the returns. The long-term and short-term tax rates are at 30% and 15% respectively along with other charges like STT. Robo-advisors offer tax loss harvesting whereby the shares are sold at a loss, and the proceeds are used to buy new shares. The loss so generated would be set off against other capital gains considering the provisions of the Income Tax Act, 1961 and its regulations. Hence, the profit arises to investors as follows: The tax saving amount can be reinvested again, resulting in tax compounding and the differences in the tax rates enable tax rate arbitrage benefit. Tax loss harvesting benefits the investors but this feature is not available or is not fully explored in the traditional system. Only people who rely on their personal advisors like Chartered Accountants or tax consultants claim the tax benefits.
• Fiduciary duty Fiduciary duty mandates the advisor to act according to the clients\' best interest. The advisor should not focus on his/her own profit at the cost of the investor. The same principle is made applicable to the robo-advisors as well.
• Market upturns The robo-advisor systems in India failed multiple times to handle the crisis situations resulting in heavy losses to the investors. The experienced and cautious traditional advisors could drive their clients on the right path in such situations.

Technical differences

Robo-advisory services use AI-based portfolio construction and portfolio management. They also use it for portfolio rebalancing resulting in added benefits. By using big data analytics, robo-advisors can conduct advanced research and implement timely, informed decisions. The robo-advisors have a major duty to keep their system updated with the changing market conditions. This would necessitate robust modeling and decision systems which would upgrade with quick turnaround time.

On the other hand, traditional advisors use online platforms and mobile apps to digitalise their services. They are yet to utilise the advancements in technology.

Regulatory differences:

a. Regulatory structure available Currently, robo-advisors are treated at par with Investment Advisors and are governed by the SEBI (Investment Advisor) Regulations, 2014. Rules like execution of physical agreement and maintenance of records of risk profile and risk assessment, suitability of advice provided, and client interactions are mandatory for the robo-advisors as well. Quarterly reports submitted to the SEBI must include information on AI applications used for advice generation, cyber security controls, and other privacy protocols. The rules have made comprehensive system audit compulsory along with an audit of automated tools. But the lack of specific regulations for Robo-advisors raises many issues like liability concerns in a situation of investment losses or errors, or the extent of application of fiduciary obligations to algorithmic decision-making processes, etc. The SEBI regulations on robo-advisors are only in the nascent stage and it is high time that they introduce new guidelines or amendments to the existing regulations as this service embarks its growth journey.

b. Required regulations - Fees charged by the robo-advisors are not currently regulated by the authorities. They have the discretion to fix the same, unlike the traditional advisors who are constantly monitored by the SEBI. There is a higher chance that these services, which provide at low costs now, would hike their prices once the customer base has grown. Also, regulatory supervision is crucial in areas like fiduciary standards, disclosure of potential conflicts of interest, assumptions, and limitations of algorithms, etc. The SEBI (Investment Advisors) (Amendment) Regulations, 2020 require investment advisors to have professional qualifications or at least a 2-year PG diploma or degree in commerce and an experience of 5 years. But recommending this would require robo advisory services to hire human experts who will have to be paid higher salaries affecting the cost of operation of the service.

Emotional differences

a. Users of Robo-advisors - Investors who are young (Hasanah et al., 2023) with high subjective financial knowledge and a high level of risk tolerance utilise robo-financial advisors (David, 2019) in developed markets. However, a similar socio-demographic based study in India could not find a distinction between users and non-users of robo-advisory services. These users possess higher wealth and are more financially sophisticated. Trade behaviour of these users indicates active nature whereby they trade more, both in frequency and volume.

Traditional financial advisers, though cater to all investor segments, do not consider the retail segment to be profitable. They offer customized services only to affluent high-net-worth retail investors through Portfolio Management Services. The retail investors\' segment has low returns per customer when compared with High-Net-worth Individuals (HNIs). With the rise of robo-advisory, retail investors can be better served and revenue generation can be improved (Warchlewska & Waliszewski, 2020). Also, by applying a behavioural approach to decisions, these robo-advisors impart more confidence in making investment decisions.

b. Customer support The robo-advisory services lack face-to-face interaction as well as a customer grievance handling mechanism. This lack of human touch affects the investors who always wish for emotional support.

c. Less emotional decision making In volatile market situations, retail investors make mistakes resulting in buying at higher prices and selling at lower prices. Robo-advisors perform well in such situations by integrating fintech and portfolio management processes.

d. Financial education - Robo-advisors provide online modules for investor education free of cost. This develops their investment knowledge and financial sophistication. The traditional advisors do not take much effort except due to pressure from the SEBI.

e. Conflict of interest and trust Robo-advisors owing to the investment modes chosen, do not possess conflicts of interest as compared to traditional investors. Also, they make disclosure of these interests to their clients. Traditional financial advisors are often criticized for possessing and never disclosing conflicts of interest. These affect clients\' trust levels. (Cruciani et al., 2021).

SWOT Analysis of ROBO Advisory System

While using robo advisory services, investors get the benefits of low costs, low influence of biases, proper customer profiling etc. However, investors must also caution themselves about the inability in handling new crises, data privacy and security concerns, prevailing regulatory structure, investment options available, fees charged, etc. Lower human interaction in these services can reduce care and emotional support. The following SWOT analysis will further help the investors before choosing among the two advisory services.

Suggestions for the Hybrid System

Placing the human advisors in the robo suit would give them these features:

a. The Trendsetter Advancements in technology in big data analytics, artificial intelligence, and natural language processing have to be incorporated to ensure further value addition to the services (Wipro, 2020). They can be used for technical analysis and in developing model portfolios. The system would facilitate informed decisions even during exceptional scenarios with the presence of humans, thereby ensuring the services are unaffected by algorithmic flaws. Human intervention should be focussed only on high-level strategic decisions, while AI should perform rapid data processing, quicker simulation of multiple scenarios, and execute operational decisions. This judicious use of the two systems can control any impact of human involvement in the fast-decision-making ability of robo advisory services.

b. The Penetrator - The cost models are gaining a lot of attention in India, especially among the affluent or retail investor groups. The zero brokerage records the highest number of users in the country due to this. But the lack of advisory feature in this model will not help the financially unsophisticated retail investors (Çera et al., 2021) in the future. A low-cost model of robo-advisors can be a way of serving them to generate returns than traditional investment advisors. Added personalization or features could be charged more to ensure quality recommendations.

c. The Market Predictor The hybrid system would help to incorporate the learning experiences of the human advisors which can be used as a knowledge base. The presence of experienced human beings will help to handle first-time scenarios such as COVID-19, failure of any financial products, or global war situations etc. as the robo-advisors do not have adaptive thinking or ability to synthesize information from different sources. The historical data specifically compiling the changes during these crises can be used to address similar situations in the future. This would enable the systems to manage downside risk and make investment reallocations as per the situation and the investors\' goals (Wipro, 2020).

d. The Performer The customer initiation, profiling, matching, and portfolio generation could be carried out as robo-advisors do. But the customers can be enquired as to whether they need human support, and they also need to be consulted regarding their suggestions in portfolio development. This would speed up the account opening, KYC, and risk profiling. Customer handling and relations management can also be taken care of. The lack of a customer grievance mechanism can also be an area where human intervention can be adopted. The tax harvesting feature of robo-advisors can be highlighted by traditional advisors to gain investors and ensure higher returns. Better tax planning can be carried out if they invest in direct equities rather than ETFs. Financial professionals like Chartered Accountants can play a decisive role in these areas.

e. The Caretaker - The Indian investors lack emotional trust with their advisors. They are interested in an advisor who would generate better returns at a low cost. Yet, a section of investors who are not tech-savvy still rely on human experts. To ensure that the clients stay with the advisor, high-end customer service on both the technical side and customer relation aspect are expected. The merged system can easily integrate these requirements.

f. The Researcher It is quite difficult to say who is a better researcher. Humans or the human developed AI-based Robo-advisors. What if both are joining? This splendid combo would offer the best of research. Data mining done by robo-advisors generates beneficial information on valuation, stock prices, etc. which, can be used to provide stock recommendations swiftly. This would elevate the investors to a superior position.

g. The Abider The robo-advisors must follow the amendments suggested in the SEBI (Investment Adviser) Regulations 2013 and the SEBI (Investment Adviser) Amendment Regulations 2020. This, along with other indispensable laws on security and fiduciary duty, has to be developed rapidly to ensure the legitimate functioning of the robo-advisors. At the same time, unnecessary compulsions like requiring physical agreement from the client, would result in increased cost of operation and further raise the fees charged by the robo-advisors. An explicit regulation is imperative at the current stage to gain maximum benefits from this service.

Conclusions and Implications

The evaluation of both systems recommends a hybrid mode of operation. This would generate a system combining their positive features. This co-existence would result in the growth of financial advisory services as it would help to incorporate the underserved markets at nominal costs. The hybrid model would ensure better returns to both the clients and the advisory services. This enhanced customer base would stay in the markets for long, once better services are obtained at affordable costs. A proper monitoring mechanism, both legal and technical, is the most vital development suggested in robo-advisory services so as to ensure investor protection.