How can MFs make hay with Analytics

Most industry pundits agree that the Mutual fund industry is at the cusp of a significant growth period. In an interview to one of the business dailies, Reliance MF CEO said that the mutual fund industry is set to achieve an investor base of 10 crore accounts in the next five years. The overall asset base of mutual funds can reach Rs 20 trillion by 2018, from about Rs 12 trillion now. Average assets under management (AUM) of fund houses touched the Rs 13-lakh-crore mark in the July-Sept 2015 quarter as investors continued to enter mutual funds despite volatile equity markets. At present, the number of folios or investor accounts across the industry stands at a little over four crore.

Obviously a large part of this is going to be due to the macro factors such as positive sentiments, economic growth, middle-income class participation, younger population willing to invest, etc. How will it pan out from a fund house perspective? How will they scale? The obvious answer seems to be a multi-fold increase in the no. of active distributors, substantial extension to Tier-III towns, and more acceptance of the online/direct channel. We are already seeing fund houses relying on technology – platform for distributors, mobile apps, CRM systems, etc. What else is at the disposal of the fund houses which can help them with this objective?
Let us explore how data and analytics can assist in each of the above endeavours. While most top ranked fund houses have 10-15K empanelled distributors, about 30-35% of them are active at any point in time. Thus the natural action is to get more distributors active on a regular basis. This leads to the questions – which are those distributors one should go after? Should revenue be the criterion? If one considers only no. of folios, shouldn’t the avg ticket size also matter? AUM? Geographical reach? What about Y-o-Y business growth – a relatively dormant distributor may be growing at a faster clip, by addressing untapped territory/segment. Do I hear you say all of these and more. Analytics can help you develop a multi-parameter distributor score that reflects the distributor comprehensive value to you. Other capabilities include – segmentation, product classification, and attrition.

Banks and telecom organisations have led the way in leveraging their existing customer base for improving revenues. Most top fund houses have an existing customer base of 0.5 – 1 mn. Relative to Banks or Telcos, fund houses have a higher opportunity to sell more products (read schemes). However majority of the new selling to this base is determined by the distributor relationship and new scheme introductions, not investor interest. This deters the potential investors and also returns poor conversion for the fund houses/distributors. Instead, if the fund houses track their customers’ investment/ redemption records in terms of the size/type/frequency/category/channel, it can help better pitch only the relevant schemes. Find out which customers to pitch equity schemes, which ones to pitch debt. All you need is couple of years’ detailed transaction data. And you can do more – customers most likely to subscribe to a NFO, customers likely to stop SIPs etc.

Heard before? Not easy to execute? Of course it requires a bit of data discipline and statistical capability but without it, can only brute expansion (force) in distributorships/advertising or selling initiatives help. Enrich those initiatives with analytical insights. See the efficacy .. tweak .. redo. The window of opportunity, as the pundits say, is now.

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