INTRODUCTION:

In India, mutual fund product is at very infant stage we can say as across all different financial products and investable amount in India. As per one of the study of KPMG, they have studied that mutual fund penetration in India is below 5% which shows that distribution of mutual fund is a key challenge to regulator. Moreover as mutual fund is a financial product and related to investment of people’s hard earned money, it is also required that investor understand the product and then invest as per their need. In such scenario, distribution of mutual fund is a key activity.

SEBI, recognizing the important role of investor confidence plays in driving market sentiment is positive, has taken various normative work to assert the faith of investors. Some of them, introducing the concept of anchor investor, disclosure of rights proposal documents, a list of firms, the missing, lower fees, and issue of shares with superior voting rights.

Transparency in the process of downloading and payment of commissions was introduced to incentivize customers to stay invested for a longer period of time.

In August 2009, a limitation on the entry loads it was announced for mutual funds, where the Commission is to be paid directly by the investor to the distributor, depending on the delivery of services. It is expected that this will separate streams of payments for two roles distributor, as a point of sale of the asset management company and advisor to investors. Many mutual fund investors use the services of a distributor acting as financial adviser, who is expected to assist investors in the choice of schemes that meet their risk appetite returns, in addition to assist it in the application of the procedure.

For the protection of the mutual fund industry from often mix and protect the interests of investors, the step to restrict the entry loads. This is likely to lead to the provision of investor to accept the decision of the Commission should be paid to the distributor, ensuring transparency in fees, based on the quality of service.

Entry Load defined as a mutual fund company to collect the amount from investors when they join or leave scheme. This fee is usually referred to as the "Load". The entry load can be called the amount or fee from the investor, when logging in to the system or in the company as an investor.

Description As a rule, the load is to cover the cost of distributing company. The various mutual funds houses charge a variety of fees in the form of a record load. In India, this charge was usually about 2.25% of the value of the investment. In August 2009, however, SEBI has made away with the practice of charging the entry load for mutual funds which is knows as no-entry load regime.

Purpose of introduction of no entry load:

Securities and Exchange Board of India, Chairman of the Mr. Sinha, who earlier headed by UTI mutual fund, as well as the Association of Mutual Funds In India, or AMFI, decided not to lift the ban on entry load for mutual funds. Prior to the ban in August 2009, the Fund houses charged investors about 2.25 per cent of the amount invested as the entry load for distribution and marketing expenses, including commissions.

At the time of the ban on entry, SEBI allowed the means to collect a maximum of 1% of the total investment How to get out of the investors who sell, premature.

Its consequences:

a mutual fund industry has been reeling under the impact of the ban 2009, resulting in the redemptions net outflow of Rs 18 044 rupees as advisers on matters of wealth tell customers to go to other products. The ban also affected new proposals or NFOs, many of the funds. According To The AMFI, only 24 of the funds were launched in 2010, get some Rs 3 000 rupees, in comparison with 33 NFOs launched in 2009 that the mopped up Rs 7 284 rupees. In addition, the ban reduced revenue distributors, forcing them to advise clients or redeem them justice or to invest in insurance and term deposits that earn them higher commissions. Currently, distributors have the right to charge a fee from the investor, but they are required for the dual check system: Separate checks and commission.

Advantages:

The ban was aimed at ensuring greater transparency in the system, and its removal, have contributed to the mis-selling of products. Prior to the ban, the Fund houses pay a wide range of commissions for agents for the sale of their plans. Operators often contributes to the funds, which promised them the highest fee. Keeping the ban will lead to increased competition between distributors and deliver better customer service.

Alternative models:

Some believe that the SEBI went overboard in trying to correct the incorrect methods and ended up on the failure of the distributors sell mutual funds. "There are a lot of products on the market, but nobody sells them, and, therefore, there are no buyers," said Sanjay Matai, promoter, the richness of the architects, Pune wealth advisory firm. SEBI a group was established to develop a new incentive for distributors, in which investors may be asked to pay for the service, and commissions to distributors could be borne by asset management companies.

The world experience:

In developed countries such as the United States, Canada and the United Kingdom, mutual funds are divided into three categories: With a front-end load, the back-end load and no load. When buying a mutual fund with a front-end load, the investor pays in advance of the Commission. In the case of the back-end load, a fee is charged at the time of purchase. Without a load may, as a rule, purchase or exchange without charges.

LITERATURE REVIEW:

Indian Mutual Fund Industry has been continuously in changing phase since its birth. Simultaneously mutual fund industry in India has many opportunities also as there is low level of penetration in this industry. Some of the literatures studied are described herewith:

As described by the Centre for Research and Security Prices(CRSP), it is the ratio of the fund’s operating expenses paid by shareholders to the total investment (http://www.crsp.com/products/documentation/fund-style). These expenses include recordkeeping, custodial services, taxes, legal expenses, accounting and auditing fees and the marketing cost referred to as a 12b-1 fee. According to Securities and Exchange Commission, 12b-1 fee is an annual marketing or distribution fee on a mutual fund. It is considered as an operational expense and as such is included in a fund’s expense ratio. The maximum limit for this fee is 1 percent of a fund’s net assets. Droms and Walker(1994) and Grinblatt and Titman(1989) found that there is no relationship between expense ratio and mutual fund performance. According to their study, for mutual funds, expense ratio being high or low does not have any impact on their return. However, in an earlier study, Ippolito(1989) confirmed a positive relationship between mutual fund expenses and performance. Amphora and McLeod(1994) argued in favor of high expense ratio for the better performance of the mutual funds. They supported theRule12b-1expense of the mutual fund. According to this study, Rule 12b-1 expense includes additional growth and provides benefit to share holders from economies of scale. In some other studies done by Droms and Walker(1995,1996), it was found that the higher expense ratio results in higher returns. The logic given by the authors for their findings was that, the higher expenses are consistent with the higher risk within the portfolio and hence may result into higher returns. On the contrary, Philpot et al., (1998) found that mutual funds with higher expense ratios give lower returns. According to their study, mutual fund managers are not able to increase the returns of their portfolio by spending resources on active management i.e., analysis and trading activity, prediction of market efficiency etc. In another study, Jan and Hung (2003) found that, low expense mutual funds are giving better returns than the high expense mutual funds. Overall smaller funds with lower expenses ratios tend to generate consistently better performance and these results were consistent with Carhart (1997).

OBJECTIVES:

It is continuous effort of SEBI to increase penetration of mutual fund and taken a crucial step of eliminating entry load from the system. This led to may consequences like disappointment in distributors, entry of new comers decrease for a temporary period. Also due to this many things changed in distribution channels. So main goal is to understand impact of this change on to mutual fund distribution. In this context the research aims at,

1. Identify and examine the factors influencing distribution channel in Indian Mutual Fund Industry.

2. Classification of factors affecting overall effect on distributors.

3. Evaluation of relative significance of identified elements on overall effect on distribution channel.

METHODOLOGY:

Data Collection:

The primary and secondary sources of data collected were adopted in this research work.

Primary Data Source:

Primary data collected through personally administered questionnaire.

Secondary Data Source:

Secondary data in this research work were collected through books journals, magazines, and newspapers, Internet website etc.

For collection of data, IFAs (Independent Financial Advisors) from across major cities like Ahmedabad, Baroda, Surat and Rajkot were collected.

Sample Size:

Primary data collected from 1004 distributors in more than 6 months

Sampling Techniques:

Sample selection was done through non-probability convenience sampling method.

Sampling Tool and Technique:

 SPSS

 MS Excel

RESEARCH FRAMEWORK:

The impact of no entry load on mutual fund distribution was checked on different factors as; 1) Investment Flow – This factor shows how much investment flow is affected due to no entry load regime, 2) Return of Distributor – shows how distributors’ income is affected due to this regulation of no entry load. 3) Distribution Expenses – this factor checks if distributor expenses are increased or decreased due to no entry load regime. 4) Advisory – refers to the role of distributor changed to advisory or not. 5) Number of Investors – checks how much investors flow is affected due to regulations. 6) Overall Effect on Distributors- checks overall impact on distributors due to no entry load regulations. These 6 construct were further divided in to 33 elements impacting mutual fund distribution channel. The responses were taken on likert scale ((5) Strongly Agree (4) Agree (3) Neutral (2) Disagree (1) Strongly Disagree)

DATA STATISTICS:

		Frequency	Percent
Age	LESS THAN 30	100	9.9
	31-50	503	50
	ABOVE 50	404	40.1
	Total	1007	100
Marital Status	MARRIED	907	90.1
	UNMARRIED	100	9.9
	Total	1007	100
Education	COMMMERCE	603	59.9
	SCIENCE	200	19.9
	ARTS	204	20.3
	Total	1007	100

As we can see in the above mentioned table that majority of distributors i.e. 503 (50%) are in age group of 31-50, followed by 404 (40.1%) in the age group of above 50 years and 100 (9.9%) of respondents are from age group of less than 30 years.

When we talk about marital status of these respondents, 907 (90.1%) are married while 100 (9.9%) of respondents are unmarried.

Talking about education qualification, 603 (59.9%) respondents are from commerce background, 200 (19.9%) are from science background and rest 204 (20.3%) are from arts background.

		Frequency	Percent
ASOOCIATION WITH MUTUALFUND IND	LESS THAN 5 YEARS	200	19.9
	5-10 YEARS	292	29
	ABOVE 10	515	51.1
	Total	1007	100
AVEREGE AUM OF FIRM	LESS THAN 10 CRORES	53	5.3
	11-25 CRORES	150	14.9
	26-50 CRORES	350	34.8
	51-100 CRORES	404	40.1
	ABOVE 100 CRORES	50	5
	Total	1007	100
NO OF CLIENT ASSOCIATE WITH FIRM	LESS THAN 100	42	4.2
	101-500	211	21
	501-2000	504	50
	2001-5000	200	19.9
	ABOVE 5000	50	5
	Total	1007	100
SIP INPUT VALUE BY CLIENT	LESS THAN 10 LACS	53	5.3
	11-25 LACS	200	19.9
	26-50 LACS	504	50
	51-100 LACS	200	19.9
	ABOVE 100 LACS	50	5
	Total	1007	100

As presented in above table, out of 1007 respondents, 200 (19.9%) respondents have spent less than 5 years in mutual fund industry, 292 (29%) respondents have spent 6-10 years in industry while 515 (51.1%) respondents have spent more than 10 years in the mutual fund industry.

As presented in above table, out of 1007 respondents, 53 (5.3%) are managing less than 10 crores of AUM, 150 (14.9%) of respondents are managing between 11-25 Crores of AUM, 350 (34.8%) respondents manages average AUM of 26-50 Crores, 404 (40.1%) of respondents manages AUM between 51-100 Crores while 50 (5%) of respondents manages AUM above 100 Crores.

As presented in table, out of 1007 respondents, 42 (4.2%) respondents have less than 100 clients associated with their firm while 211 (21%) respondents have 101-500 clients, 504 (50%) of respondents have 501 to 2000 clients associated with their firm, 200 (19.9%) respondents have 2001-5000 clients associated with their firm while 50 (5%) of respondents having more than 5000 clients associated with their firm.

As the above table shows, 53 (5.3%) of respondents have less than 10 lacs SIP Input Value, 200 (19.9%) of respondents have SIP input value of 11-25 Lacs, 504 (50%) of respondents have SIP Input Value of 26-50 Lacs, 200 (19.9%) respondents have SIP input value of 51-100 Lacs while 50 (5%) of respondents have sip input value of above 100 lacs.

TEST AND RESULTS:

Reliability:

To check the scale reliability of the factors for internal consistency we have used cronbach’s Aplha. Scores of α > 0.50 is acceptable and α > 0.70 is desirable. We have for scores above 0.700 for all the constructs proving internal consistency of all constructs.

	Cronbach's Alpha	No. of Items
Investment Flow	0.835	6
Return of Distributor	0.937	4
Distributor Expenses	0.729	3
No. Of Investors	0.727	4
Advisory	0.936	4
Overall Effect on Distributors	0.837	11

PEARSON COREELATION ANALYSIS:

The Pearson Correlation Analyses was used among variables to correlations between variables. The correlation analyses among all factors affecting distribution channel are shown in below mentioned table “Correlation”. The results shows that there are positive correlations between Investment flow and overall effect on distributors (r=0.717, p<0.01), return of distributors and overall effect on distributors (r=0.810, p<0.01), distributors expenses and overall effect on distributors (r=0.578, p<0.01), advisory and overall effect on distributors (r=0.808, p<0.01) and number of investors and overall effect on distributors (r=0.357, p<0.01).

Correlations
	OIF	ORD	ODE	OAD	OCD	CNI
OIF	1	0.621	0.207	0.62	0.717	0.398
ORD	0.621	1	0.375	0.999	0.81	0.365
ODE	0.207	0.375	1	0.373	0.578	0.041
OAD	0.62	0.999	0.373	1	0.808	0.365
OCD	0.717	0.81	0.578	0.808	1	0.357
CNI	0.398	0.365	0.041	0.365	0.357	1

REGRESSION ANALYSIS:

Regression analysis gives the understanding and estimation of the relationships among variables. It helps in understanding how the distinctive value of dependent variable changes with the change in one of the independent variable when other independent variables are unchanged. Now when we have established the linear relationship among the dependent variable and independent variables, we wish to estimate the degree of change in the value of dependent variable due to change in independent variable. Further, we also need to know the most influencing factor out of all five independent variables. As we are developing a new model which is being used for the first time, we need to confirm the fitness of the model and relative contribution of each of the predictors to the total variance explained.

To understand how much impact of each factor on distribution channel the multiple regression model is derived. In above mentioned table, Investment flow, return of distributor, distributor expenses and number of investors are very much significant on distribution channel with respect to no entry load regime. It is also showing the greater impact on dependent variable of distribution channel. The most influencing factor is investment flow with ß=0.43 with sig. value of 0.000 followed by Distributor expenses with ß=0.327 and sig. value of 0.000, return of distributor with ß=0.270 and sig. value of 0.000 and number of investors with ß=0.025 and sig. value of 0.015. All the tolerance values and VIF values are less than 10 that indicates there is no issues of multi co-linearity in deriving the impact of no entry load on distribution channel of Indian mutual fund industry.

CONCLUSION:

As per out analysis, Return of Distributor, Distributor Expenses, Investment flow and Number of Investor were the factors having maximum impact on overall effect on distributor and distribution channel. Whereas advisory have moderate impact as discovered by study.

As per our finding from ANOVA, we can conclude that different AUM Group, different number of clients group and different SIP book group distributors have different beliefs regarding no entry load regime so distributors having higher AUM, Number of Clients and Higher SIP input value are finding no entry load as positive impact despite their return, expenses, number of investors and investment flows have affected. Vis a vis distributors with less AUM, Less number of clients and less sip book look this regulation as negative.

As per our findings from correlations, we can conclude that as all the variables have strong positive correlation and so overall distribution channel is impacted but this regulation is taken as positive impact in terms of Market expansion as AUM of industry is growing positively.

Moreover, despite of there is an increase in AUM of Mutual Fund Industry, penetration of mutual fund still is at around 5% which says there needs to be more focus on distribution channel of this industry by regulator. As mutual fund is a product which requires understanding of financial products well, this industry needs to have more focus on IFA (Independent Financial Advisors) and regulator need to understand the key aspect like return of distributor and then decide upon changes in the industry as this factor most affect this industry.

Also the effect of no entry load regime is major on return of distributor but industry is in shape where the existing no entry load regime still do not have impact on AUM on the industry and recent regulations of T30 (Top30 Cities) and B30 (Beyond Top30 Cities) locations justify regulators intention of penetrating mutual fund in rural market.

REFERENCES:

1. SEBI Circular: June 30, 2009, Circular No.: SEBI/IMD/CIR No. 4/ 168230/09

2. Article: Morning Start, 08-02-16, “How Fund Distribution is Evolving in India”

3. Book: Bhole, L., & Mahakud, Jitendra. (2009), Financial Institutions and Markets. New Delhi: Tata McGraw Hill

4. Article: www.fisdom.com, 07-02-2017, “Mutual fund Distribution in India 2017”

5. Book: Gupta, Amitabh. (2002). Mutual Funds in India: A Study of Investment Management. New Delhi: Anmol Publications Pvt. Ltd

6. Book: Gupta, N. K. & Chopra, Monika (2010). Financial Markets, Institutions and Services. New Delhi: Ane Books Pvt. Ltd.

7. SEBI Circular: February 02, 2018, Circular No.: SEBI/HO/IMD/DF2/CIR/P/2018/16

8. Book: Gurusamy, S. (2009). Essentials of Financial Services, 2nd Edition, New Delhi: Tata Mc-Graw Hill Publishing Company.

9. Website: www.amfiindia.com, www.sebi.gov.in, www.moneycontrol.com

10. Survey Analytics:KPMG-CII. (2009). Indian Mutual Fund Industry- Future in a Dynamic Environment: Outlook for 2015. Delhi: KPMG-CII.

11. Survey Analytics:KPMG–Confederation of Indian Industry (CII). 2009, June), Indian Mutual Fund Industry – Future in a Dynamic Environment: Outlook for 2015. New Delhi: KPMG-CII.

12. Book: Kothari C. R. – Vishwa Prakashan (1990), Research Methodology – Methods and Techniques 2^nd ed., New Delhi

Received on 08.01.2019 Modified on 14.01.2019

Res. J. Humanities and Social Sciences. 2019; 10(2):691-696.

DOI: 10.5958/2321-5828.2019.00114.1

Model Summary
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	Change Statistics		Change Statistics
Model	R	R Square	Adjusted R Square	Std. Error of the Estimate	R Square Change	F Change	df1	df2	Sig. F Change	Durbin-Watson
1	.909^a	0.826	0.826	0.18623	0.826	1188.8	4	999	0	1.8

ANOVA^a
Model		Sum of Squares	df	Mean Square	F	Sig.
1	Regression	164.917	4	41.229	1188.788	.000^b
	Residual	34.647	999	0.035
	Total	199.564	1003

Coefficients^a
Model		Unstandardized Coefficients		Standardized Coefficients	t	Sig.	Correlations			Collinearity Statistics
Model		ß	Std. Error	Beta	t	Sig.	Zero-order	Partial	Part	Tolerance	VIF
1	(Constant)	-0.188	0.087		-2.149	0.032
	OIF	0.430	0.021	0.355	20.51	0.000	0.719	0.544	0.27	0.58	1.72
	ORD	0.270	0.011	0.451	24.94	0.000	0.810	0.620	0.33	0.532	1.88
	ODE	0.327	0.014	0.334	23.34	0.000	0.579	0.594	0.31	0.848	1.18
	CNI	0.025	0.01	0.036	2.448	0.015	0.357	0.077	0.03	0.806	1.24