UTI Mutual Fund Working on Predictive Analytics; Plans to leverage it for Cross-Sell and Up-Sell Opportunities

UTI Mutual Fund is currently in the process of building its sales datamart and is looking at predictive analytics as the next stage. It is expected to go live by the end of 2017. The company has outlined several use cases, including identifying cross-sell and up-sell opportunities, identifying likely redemption cases, doing market analysis, etc.


Through predictive analytics the company will try to understand customer behavior, which will help identify those customer segments that are more likely to invest and in what products. It will then, accordingly, design its campaigns, target them to the right segment and pitch the right product to the right customer.


“In any business one would want to sell more to your existing customers, acquire new customers and stop the customer from exiting you. These are the three key business imperatives where we would like to leverage predictive analytics,” explains S Raghunatha Reddy, Executive Vice President, UTI Mutual Fund.


Talking about cross-sell and up-sell opportunities, Reddy explains how predictive analytics will enable that. To begin with, it will help understand the co-relation between the stock market movement and equity investors as well as the patterns that are there when the market goes up or down. For instance, when the market goes down there are certain set of investors/customers who start redeeming and when it goes up there are certain set of investors/customers who put in more money.


Being able to identify the set of customers who more likely to invest, the company can target them for focused campaigns, thus enhancing the effectiveness of cross-sell and up-sell opportunities.


Another use case for predictive analytics for most of the financial services industry and especially insurance and mutual funds is helping stop the redemptions. Customer behavior analysis can help the company identify in advance the customers who are likely to redeem during the month/quarter/year. These customers can then be targeted through sales staff or intermediaries or through a focused campaign to retain them.


Reddy believes that while one cannot stop redemption in all cases, but at least, the churn – moving from one fund to another fund – can be reduced through persuasive discussions in a lot of cases. Thus, helping reduce the money going out.


According to Reddy, the key to the success of analytics will lie in building the right model that draws data not only from internal but also external sources. “How good is your model to predict depends on how much data you feed into it. One needs to give a lot of information so that the model is able to predict accurately,” he explains.


The company is currently working on building the model for predictive analytics and will be able to roll it out by the year end.

(Image Courtesy: Pixabay.com)

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