by Rajesh Shashikant Renukdas, on Apr 6, 2021 4:55:38 PM
Lending Businesses have seen several improvements in their operations with technology, yet remain susceptible to risks given the innate nature of the business. On top of this, manual or siloed digital analysis, and the absence of instant customer data access, delay the loan disbursals to the point that negatively affects both lending and borrowing parties.
However, the rise of smartphones has managed to mitigate these risks to an extent by offering instant user data access to lenders, and single-tap on-the-go facilities for loan applications and payments to the borrowers. So, while there is no surefire way to make accurate predictions and eliminate the risk altogether, a framework for accessing customer credit data on the go, automating front-end interactions, and integrating back and middle offices of lending enterprises through a loan default prediction system can significantly help in offsetting the losses inflicted through improved efficiencies and costs reduced. In this blog, we will take a look at some of the highly useful functionalities that a loan prediction system can offer financial institutions and how they work.
How does default loan prediction work?
A default prediction functionality is achieved by feeding the machine learning algorithms data on historical loans and their status of payback. The algorithms then try to capture the structure underlying the characteristics of the loans and their relation to the default status. This data is then processed to drive insights on existing or incoming data and lets the lenders lay down an action matrix on the front end through a mobile or web interface.
Here are some functional features of a lending Mobile/Web application that can help lenders to minimize risk and leverage requisite insights for an enhanced customer experience:
Application and Agents Tracking
A functional web or mobile interface makes it possible for the lenders to initiate streamlined loan processing, real-time tracking of field collection agents appointed for a party, track interest payments made, etc. This lets stakeholders predict closure and take in-time actions for loan recovery. Taking into account various data sets to create a realistic view of the prospective creditor, the app can also offer workflow customization according to the vertical being catered. Datamatics built a field collections mobile app for an NBFC to streamline the collection process for their field agents to perform real-time tracking of the agent and payment made by customers. This also led to an increase in field agent’s efficiency and improved authority control over the processes.
Prospect Evaluation
Lending processes usually excessively rely on error-prone manual collection and analysis of prospect data becoming one of the primary causes of NPA accumulation in a bank’s lending history. Numerous reports on credit scores, account transaction statements, along other details of the client need to be closely scrutinized to approve an application, delaying the process of credit analysis.
A mobile/web application for Loan disbursals can help evaluators have a comprehensive view of the prospect by setting in place an AI-based data-analysis functionality to assess the prospect’s bank statement, previous credit payments, term of the loan, size of the company, and data from credit rating Bureaus. In addition to this, a feature for GST analytics can use portals for tax filings as a point of source for data. A unification of these functionalities can help build an accurate Loan Eligibility checker with reduced false positives that can help lenders assess the credibility of the borrower and have a comprehensive view of a customer’s previous credit data.
Custom Business Analysis on Smartphone data
The data gathered through mobile apps and various regulatory website APIs can help lending institutions channel key trends, conduct in-app surveys, capitalize on high-ROI opportunities, and give specific next-step recommendations to smartphone users. An app also enables institutions to cross-sell multiple products aligned with user buying personas. Lenddo is one such company that claims to have processed instant loans to over 5 million people through credit scoring users on data like job history, spending habits, previous credits, etc. gathered through mobile data. The company claims to have looked into more than 12,000 variables that include social media usage, internet browsing, history geolocation, and other smartphone-linked information, just by getting people to use their mobile apps.
Automated KYC
Customer onboarding is a time-consuming process given the burden of manual KYC, routine paperwork, error-prone evaluation, and verification of the customer details. This incurs considerable opportunity costs on providers who lose out in customers, due to lack of scalability and customer data. With the integration of automated KYC through a mobile app, lenders can get pre-approved access to critical user information such as location, digital marketplace spending, contacts saved, emails, etc. cutting down on iterations for asking permissions or manual data entering. Datamatics developed an android Customer Loan Financing App for a leading Indian NBFC that had multi-factor authentication, automated KYC with UIDAI, NSDL & Bureau API integrations, along with advanced calculation features through business rules.
Debt Recovery Reports
Lending institutions usually remain in a conundrum due to bad debts or NPAs adding consistently to their liabilities. To minimize the risk posed by NPAs, it is critical that lenders' company enhance their debt recovery strategy. A lending software can help lenders by creating automated bad debt statements, and sending consistent reminders of repayment to the client. Lenders can also integrate a UPI payment method into due payment notifications, enabling quicker loan recollection.
Analyzing existing NPAs
A feature to map the borrower’s collateral value to the market value can help lenders drive significant insights on amortization and cost overheads of the assets in cases the borrower defaults on repayments. This feature allows easy integration of contacts and behavioral analysis, to locate willful defaulters of interest payments through an effective tracing service. A dashboard to focus on the high-level view of accounts receivable cycles with a list of recovery approaches using analytics, a lending institution can significantly reduce and write off their NPAs.
Alternative Credit Scoring Integration
Often, credit data from credit bureaus with unregulated entities make transparent access to credit histories of the borrowers, especially the ones with thin to no credit files, bank accounts, or collaterals almost impossible, thereby hindering loan disbursals to under-served segments of the population. However, technology enables lenders to use borrower's digital footprints across smartphones and the internet to assess the financial health of an individual or enterprise.
Alternative scoring on credit can be achieved through data from mobile app cookies, online buying behavior, social activity, kind of contacts or followers, their business goals, etc. A mobile app can be designed to leverage these new data sources to enhance the manual underwriting mechanisms of the lenders. Datamatics developed a responsive banking mobile app for an Indian Financial Institution using advanced architecture and smart data capture technology. This helped us reduce the app size from 24 MB to 3 MB and auto-save all necessary user data to offer a seamless customer experience
Conclusion
Despite being highly unpredictable, and veiled with unprecedented risks, a number of NBFCs and micro-financing institutions today have managed to successfully penetrate the market. They have established themselves amongst a cohort of large fintech players and Banks, owing to the next-gen technologies for secure loan origination, closure, and an enhanced customer experience and satisfaction throughout.
It is therefore critical for them to ally up with loan lending mobile app development firms that have a proven record of success in the industry and have a relevant technology stack for attaining set cost efficiencies and business goals.
