Two Approaches to Design a Digital Two-Wheeler Loan Journey
With financial institutions constantly expanding their reach, the issuing of different and newer forms of credit became a necessity. In an effort to become popular among customers, advantages were given to those seeking this credit in the form of non conventional or targeted loans. Two- wheeler loans are one such example where, as the name specifies, are loans disbursed for a specific end-use. The loans are applicable to all segments of two-wheeler vehicles, ranging from scooters to motorcycles.
While loan products like these were created with the view of furthering expansion, many setbacks occurred during deployment and usage. Creating new loan products and their policies required entirely new systems and codes which resulted in a longer time for deployment. Similarly, to popularise niche products over their traditional counterparts, demanded overwhelming improvement in user experience of the former, to prevent customer drop-offs.
Lend.In, on noticing these pain-points, identified the areas of uncertainty in two- wheeler loans, which prevented its successful adoption:-
Complexities in user experiences: Since a two -wheeler loan can be applicable to a wide range of incomes based on the vehicle segment, the need arises to create a user experience that caters to each bracket. Difficulties in configuration arise while creating interfaces that are easily understood by the lower income classes but also appealing to the affluent.
Dealer associations: For products like auto loans and two-wheeler loans, financial institutions often benefit by having tie-ups with dealers. These tie-ups demand specifications in the product and complexities arise in creating separate applications for the dealer to carry out their own sales.
Collections and defaulting: Like any loan product, there is always a risk of non-payment, however, in the case of two-wheeler loans, financial institutions tend to be less stringent because of the ticket size of the loan. This becomes a greater problem especially if measures are not set in place to target repeated defaulters.
Calculating LTV: With different segments of two-wheelers available, there are many parameters that come into place while deciding the maximum loan offer. Besides the customer’s eligibility, the loan offer heavily depends on the specifications of the two wheeler to determine the loan to value ratio. To obtain an output after decision making warrants an agile system or component which can be easily configured to accommodate the changing market values.
Dynamic approaches to a single loan product across financial institutions
Lend.In’s robust omnichannel lending suite can create customised loan journeys based on the customer requirements. On analysing the current and future prospects of financial institutions with respect to two-wheeler loans, Lend.In supports two different methods to enable this loan journey:
- Assisted Journeys in collaboration with the vehicle dealer and
- Straight Through Process (STP) Journeys
In two-wheeler loans, this largely refers to the loan origination through any dealer, taking place in the showroom. The journey combines both the lending enterprise’s as well as the dealer’s interests according to their agreements. Lend.In through the use of robust systems caters to these demands by providing:
- Web Applications for Sales Representatives: Lend.In includes an application designed for operation by the sales representative of the dealer, to assist the customer and provide an easier experience. Individual credentials are created for operation and adequate measures of encryption and security are incorporated for the customer’s benefit while inputting confidential information.
- Third party integrations for customer verification: Lend.In through the use of its API Integration broker has a marketplace of trusted APIs that are integrated into the loan journey to ease the process of KYC verification and fraud detection. The use of APIs reduces the overall TAT by performing faster checks and cross verifying national databases in real time.
- Decision Tables: While deciding the Loan to Value ratio to use in the calculation of the final loan offer, the specifications of the vehicle are taken into consideration. These are parameters that cannot be hard-coded as they differ with the change in the market. Lend.In provides an easy solution for this through the creation of Decision Tables. These tables simply require the input of details considered for LTV calculation without the need for any code and can be configured in real time through Lend.In’s Digital Experience Manager.
Most individuals prefer to apply for loans without the hassle of visiting a dealer showroom or may even apply for loans before the purchase of the vehicle itself. In such an event, where the ticket size of the loan is small, it is necessary to maximise the utility of a digital loan process to give the customer a streamlined journey without the need for assistance. Lend.In through its powerful Product Configuration Platform, has built on top of it a number of modules and features that operate harmoniously to create an STP journey. These modules include:
Loan Management System: A comprehensive system to manage all the loans disbursed and individually customise the repayment options as per the requirements. The Master Product Configurator of LMS can handle any loan product irrespective of the ticket size and is built to flexibly integrate with existing bank systems.
Digital Collections: The collections module of Lend.In is the one stop solution to track repayments as well as potential defaulters. Lend.In’s Early Warning System uses an algorithm to predict NPAs and the Notification Engine helps in scheduling reminders to all customers for repayment.
Benefits of Lend.In digital two-wheeler loan journeys
Deployment across platforms: For these small ticket loan sizes, Lend.In supports the creation of remarkable interfaces on any platform be it a web or mobile application with any operating system. Moreover, changes made on any platform are reflected across all applications.
Agility: Small ticket loans require customizations for a wider audience appeal, this requires the use of a low-code agile system that allows real time configuration and testing of changes made to reduce time taken for deployment.
Reduction in TAT: Through Lend.In modules which are run on CMM framework, both assisted and non-assisted journeys are streamlined. Thus, we can create a quicker and accurate system to reduce the overall TAT drastically even in a non STP process.
Digital Process Automation: Automation of manual processes like document submission for KYC Verification and document collection can increase system reliability and minimize manual inputs required from the customer’s end by leveraging multiple 3rd party sources for authenticated information.