Big-Data Driven Cross-Selling for Retail Lenders
Indian retail lending customers are growing at 24% y-o-y. Entry of non-traditional lenders, especially technology conglomerates like Google, Amazon, Xiaomi etc. in the space further validates the attractiveness of the business.
With new customers and different lenders entering the market, the market dynamics are changing at an unprecedented pace. Each lender is trying to increase their share of the pie, consolidate and then push for profitability.
Focus on Customer Acquisition
Lenders are facing an increasing cost of customer acquisition driven by escalating competition and recent Supreme Court verdict on Aadhaar, increasing cost of KYC from Rs. 15 to Rs. 100 per customer.
The lack of data at an individual level makes customer profiling difficult. Hence lenders are driving customer acquisition through instant, zero-interest, small-ticket size and flexi-repayment loans. These acquisition products offer the following benefits to the lenders -
· Minimizing Risk — Lenders can acquire more customers at smaller exposure, allowing aggressive customer acquisition at minimal risk
· Generating Customer Insights — Lenders further use the engagement and loan repayment data to derive insights about the customer
These loans are very effective in risk assessment of the customer but due to increasing costs and competition, lenders do not make much profit on them. Hence cross-selling to already existing customer with a good repayment behavior is super-critical for profitability of lenders.
But Cross-Selling is CHALLENGING!!
Challenges in Cross-Selling
Some of the prominent challenges faced by lenders for successfully cross-selling are —
1. One-size-fits-all Product Design
Due to lack of individual level insights, lenders are forced to offer standard credit products, which don’t meet the exact needs of the individual borrower hence diminishing their propensity to buy.
2. Inefficient Communication
Success of a cross-sell initiatives is heavily dependent on the content and the time of offer communication. Inaccurate insights can shoot up the cost of cross-sell efforts and reduce overall efficiency.
eg. Outbound calling a night-shift employee during the day-time will reduce the chance of a response from the customer.
3. Cut-Throat Competition
Majority of Indians are New-To-Credit customers, without any credit record. Many lenders acquire such customers, taking all the risk, creating the customers’ credit records, while the customers are lured away by cheaper alternatives of competitors at the time of a cross-sell . Loss of a customer with a perfect payment record can only be avoided by generating more granular insights at the personal level.
In a highly-informal economy like India, traditional data sources remain scarce with very poor fill-rates (eg. Credit Bureaus cover only 40% of the Indian population). Lenders must deploy alternative data sources like customers’ smartphones, GSTN databases etc. to develop comprehensive customer profile for improved cross-sell efficiency.
Leverage Alternative Data for Cross Sell
Alternative data consists of information that enables comprehensive customer profiling and is not covered by traditional data sources like application forms, salary slip etc. Retail lenders can deploy alternative data technology for better customer service delivery, enhanced product-customer fit and improved risk assessment.
With an almost 450% rise in the number of smartphone users the last three years and with internet penetration increasing by 10 million every month, there has been a steep rise in customer-generated digital footprint in India, which in itself is a rich source of alternative data.
Alternative data is rapidly turning mainstream as even incumbents like State Bank of India (SBI) launched SBI e-Smart SME, a working capital loan offering in partnership with Snapdeal which uses proprietary platform data and alternative data from public domain to assess the customer’s creditworthiness for loan sanctioning.
Alternative data boosts cross-sell by facilitating the lenders in —
1. Target Customer Identification
Not all customers are in need of a credit product. The absence of real-time, personalized data forces the lenders to spam their customers with irrelevant offerings.
Focus must be on consuming insights including the customer’s propensity to purchase a product and the value she expects to derive from the product.
eg. A high-saving salaried customer would be more interested in tax-free investment products like PPF or Mutual Funds than a customer with outstanding credit card bills.
2. Personalized Offering
Cross-selling is much more likely if the lender’s offers fit the need of the customer. Micro segmentation is the key to identify the perfect customer-offer fit.
Customers must be segmented on the basis of their individual profiles (nature of employment, academic qualifications etc.), consumption & investment patterns (invests in stock market, dines-out regularly etc.) and social behavior (living in an apartment, makes many outgoing calls during working hours etc.) to generate personalized offerings.
eg. A self-employed individual, requiring weekly travel would prefer better Frequent-Flyer bonuses on her credit card over card discounts on movie tickets.
3. Communication
Communicating with the customer has moved much beyond mass media and prime-time ad slots. Lenders must focus on personalizing the following aspects of communication, to generate maximum traction.
a. Content (what?)
Lenders must curate the content of offer communications to resonate with customer’s aspirations and plans. Eg. Customer searching for smartphones on Amazon must be offered an interest-free EMI offer on purchase of smartphones.
b. Channel (where?)
Lenders can choose between multiple communication channels, eg. Mass Media, SMS, Outbound Call, Social Media, In-app notifications, Email etc.
c. Timing (when?)
Lenders must establish communication at the preferred time of the day (first half, second half, late evening etc.), day(s) of the week (weekends, Tuesday only etc.), week(s) of the month (salary receipt week, month end etc.), month(s) of the year (Quarter 1, End of monsoon etc.)
Conclusion
Indian Retail Lending market is very competitive. With onboarding costs further rising post Supreme Court’s verdict on Aadhaar, acquiring customers is difficult, risky and costly.
In order to minimize risk, lenders offer small-ticket loans to customers. While these loans allow lenders to assess the customers’ repayment behavior, they do not make profits for lenders. Hence cross-selling to qualified credit-worthy customers is supremely important to maintain profitability.
Cross-selling is difficult due to the lack of data. The cross-sell initiatives can be made much more efficient if the lender offers the right product at the right time over the right medium to the customer.
Alternative data sources like customer’s digital footprint, utility bills payment history etc. can boost cross-sell by generating highly accurate, real-time insights about the customer. These insights will answer the three most critical questions of cross-sell
1. What?
2. Where?
3. When?
To read more about applications of Alternative Data for Risk Assessment by Retail Lenders, click here.
To power your organisation with Alternative Data, reach out to us at query@finbox.in.
