Webinar: Regulatory Reforms in Mutual Funds: Impact on Investor Behavior


Webinar: Regulatory Reforms in Mutual Funds: Impact on Investor Behavior

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Dr. Tirthankar Patnaik is the Chief Economist at the National Stock Exchange of India with over two decades of experience in the Indian capital markets, academic research, credit research in macro and sector strategy, quantitative finance, and consumer banking. Marzban Irani is the Chief Investment Officer – Debt Funds at LIC Mutual Funds. He has been with funds since 2016, has a long career in the asset management industry and has worked with Tata Asset Management. Rajesh Krishnamoorthy is an Independent Director-AMC at PGIM India Asset Management Pvt. Ltd. Prof. Joshy Jacob is an Associate Professor in the Finance and Accounting Area at IIMA

There are a few factors that must be considered in order to comprehend the regulatory reforms in mutual funds and their effect on investor behavior. In this webinar, Prof. Joshy Jacob discussed the effect of the risk-o-meter on investor behavior. The color code scheme was implemented from July 01, 2013 wherein it was mandated to use colors to ensure that people are aware about the risks. However, there were limited colors and the prints were in greyscale and hence, it was not particularly effective at cautioning investors against the danger involved.

The risk-o-meter was introduced on July 01, 2015. Instead of three colors, five different risk categories were introduced i.e., low, moderately low, moderate, moderately high and high. The risk is shown wherever the needle stops. Thus, brown color was split into high and moderately high categories. This resulted in more precise and obvious risk labelling. It was discovered that employing the risk-o-meter regime resulted in lower investment in high-risk funds whereas using the color code regime increased investment in high-risk funds. Investors could then distinguish between funds that previously fell into the same category because this helped them comprehend the risk associated.

Marzban Irani talked about the October 01, 2021 implementation of, ‘Skin in the Game.’ The goal was to better ensure accountability by balancing the interests of Asset Management Firms (AMCs) Key Employees and mutual fund scheme unitholders. SITG investing, mandated by the Securities and Exchange Board of India (SEBI) for Designated Employees (DEs) of AMCs — C-class executives, fund managers, compliance officers, etc.— completed its first year in September 2022. As a result of this decision, these workers were required to invest 20% of their gross pay in mutual fund (MF) schemes that fall under their direct supervision or administration. These units are locked in for a period of three years and subject to claw-back in case of violation of the model code of conduct prescribed by AMCs and AMFI (Association of mutual funds in India).

Dr. Tirthankar Patnaik spoke on the subject of benchmarking. In India, SEBI mandated the declaration of a benchmark index by fund firms in 2012 in accordance with the regulatory rules it had put in place. Setting the appropriate baseline for performance assessment is essential for streamlining mutual fund investments. There are several ways to calculate an index's returns, but the two most popular ones are the Price Return Index (PRI) and the Total Return Index (TRI). According to SEBI, using PRI to gauge the success of mutual fund schemes might be deceptive because it does not give investors a full picture. SEBI instructed investment houses to solely utilize TRI to benchmark schemes in January 2018. Unequal comparisons were caused by many benchmarks. Despite the uniformity of scheme classification introduced by the regulator in 2018, a CRISIL review of significant equity and debt-oriented schemes revealed that dispersion has persisted in terms of benchmarking by funds within a category. The benchmarking rules for the two-tiered structure were established by SEBI in October 2021 and went into effect on January 01, 2022, with the goal of standardizing and bringing uniformity to the benchmarks of the MF schemes.

The panellists concluded the discussion by agreeing upon the fact that categorization learning, grouping schema, and bucketing are crucial. Although it may not be enough, the risk-o-meter is a positive step. A risk-o-meter deals with anchoring, recency bias, cognitive error, etc and in choosing investments, there are many cognitive biases at play. One does not always develop one’s skills in the same way when it comes to processing and scaling up that knowledge. There are more marketplaces in India and yet, there is a noticeable difference in the ability to evaluate the information coming from these markets.