Identifying Cross Selling and Up Selling Opportunities with Lending Business Intelligence

Acquiring new customer is always a challenge for any type of business. Be it B2B or B2C, enterprises prefer to increase the wallet size of existing customers than spending enormous amount of money on acquiring new customers.

The average customer acquisition cost (CAC) for companies that offer financial services is more than USD 300. Apart from high CAC, a study by Wipro suggests that a mortgage loan takes 30-45 days to close. A lengthy loan origination process for new customers may lead to higher operational inefficiencies for lending institutions.

Another issue with acquiring new customer is having a lower conversion rate. For lower conversion rate, there are several reasons like Incomplete documentation, a poor credit score of the applicant, and better loan products from competitors.

Therefore Cross-selling and up-selling, becomes an attractive way of generating revenue from existing customers for your lending institution.

Importance of Cross Selling & Up Selling for Lending Institutions

There are plenty of reasons why cross-selling and up-selling are highly important for lending business. A few of those reasons are listed below:

1. Efficient Way of Generating Additional Revenue:

Since these are customers who have already experienced your service, it is easier to sell another loan product from your lending institution. Marketing Costs for your organization in business development will be zero which will boost revenue. This in turn increases the profitability of your lending institution.

2. Strong Customer Relationships:

Cross-selling and up-selling help lending businesses build better and stronger bonds with their clientele. Trust is the name of the game. Once trust is earned, repeat purchases from the existing customers are bound to increase. And if the customers are satisfied with the customer service, they are bound to refer your service to others as well. This way, your business acquires a new customer with little expenses on marketing.

3. Increased Customer Lifetime Value:

Lending businesses need to focus on retaining customers as much as they focus on acquiring new customers. Having a client who has a high customer lifetime value (CLV) is an indication that the client is loyal to your brand and business.

The formula to calculate CLV is:

Average Purchase Value * Purchase Frequency Rate * Customer Lifespan

Say a borrower takes a loan for an average amount of 200,000 USD once in three years for the next 10 years, making it on average 3 transactions in a decade. The CLV of this customer will be 200,000 *3* 10 = USD 60 Million (60,000,000).

CLV enables businesses to predict how much business they may gain from a customer if they frequently do transactions with them. Therefore Cross-selling and up-selling helps lending businesses to retain borrowers who not only repay the loan amount on time but are also loyal to the lending institution.

How Can Business Intelligence Help Your Lending Institution

Now Let’s understand how Business Intelligence (BI) can be utilized for cross-selling and up-selling for your lending institution:

1. Analyse and Segment Customers:

BI solutions allow lending businesses to create customer segments based on static features (e.g., family size, family income, customer demographics etc) and dynamic features like change in past transactions, financial status, change in jobs profile, etc.

Segmentation of customers enables lending businesses to understand the persona of their customers so that other loan products can be offered.

Once these segments are created it helps lending businesses understand what kind of loans they may be further interested in and when they may purchase it.

Analyzing these segments, customers who have higher credit score and who are salaried employees, are the best set of customers who should be targeted from cross-selling and up-selling opportunities in regard to loans.

On the other hand, customers who have a credit score lower than 700 and are a self-employed or are politically exposed people, these may not be an ideal target group for cross-selling or up-selling.

2. Modelling BI for Upliftment:

One of the important goals that need to be achieved through a BI solution is the implementation of Net Lift Modelling. Based on this, lending businesses will understand the likelihood of whether their existing borrower may purchase another loan or not.

The uplift modelling is a randomized scientific control to measure the effectiveness of marketing initiatives as well as to develop a predictive model.

3. Product Customization:

After the customers are segmented and analyzed, attractive products should be offered to the existing clients for up-selling or cross-selling. Loan products need to be customized based on the behavior of the borrower. This provides a feeling of exclusivity, and the requirements of clients are kept in mind based on historical data. Loan terms & conditions, interest rates, payment schedules and so on could be customized.

4. Market-Basket Analysis:

Market-Basket Analysis is a historic analysis of customer data that focuses on combination of goods or services bought by a customer. This type of analysis is mainly used to understand what type of loan offerings can be combined as they are frequently taken by the borrowers. People who take a home loan, for example, may also go for furniture loan as per the data. An offering can be made wherein these loans are combined with existing customers and offered to them.

Intellify’s Lending Analytics Solution

Using Lending Analytics solution, Business users will be able to select a pool of customers who have certain characteristics regards to Region, Age, Income group, Credit Score and repayment patterns to offer loan products for cross sell or up sell opportunities.

We at Intellify have developed a Lending Analytics Solution wherein 100+ KPIS are ready on day 1 for 3 major Business Processes viz Loan Origination, Loan Servicing and Delinquency Management. The interactive dashboards help Business users drill down on different hierarchies and get the exact cause of good or bad business.

Watch our Lending Analytics Solution Overview

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