Today, the lending landscape is promising for ambitious lenders. For instance, the estimated credit gap of INR 33 trillion in Micro, Small, and Medium Enterprises (MSMEs) presents an opportunity for lenders to service this sector more efficiently. However, existing systems cannot accurately underwrite MSME businesses due to their unique needs and lack of credit history. Adopting automated loan management systems is helping lenders scale up while bringing efficiency to the entire lending workflow.
In this blog, we decode loan management solutions, key advantages, and their impact on lending operations.
What is a Loan Management System?
The lending cycle generally includes several steps, such as:
- Pre-qualifying the Loan Applicant
- Submitting the Loan Application
- Loan Origination (processing and preparing the loan)
- Undergoing the Underwriting Process (evaluating the borrower’s creditworthiness)
- Disbursing the Loan (releasing the funds to the borrower)
- Collecting the Loan (regularly scheduled payments from the borrower)
- Recovering the Debt (actions taken in case of missed payments)
- Closing the Loan (finalising the account after full repayment)
A loan management system is software that enables lenders to automate the lending workflow, end to end, through a cloud-based, unified interface.
The system aims to bring efficiency, accuracy, customisation, and scalability to lending operations by reducing manual interventions. Key technologies used in this solution include Artificial intelligence (AI), Machine Learning (ML), cloud computing, Optical Character Recognition (OCR), and robotic automation.
Innovative Capabilities of a Loan Management System
Automating the entire lending life cycle with the adoption of a loan management system helps lenders address critical challenges as follows:
Reducing Inefficiency
Manual lending processes can result in data errors, omissions, and extended back and forth between borrowers and lenders.
An automated loan management solution brings efficiency to the entire lending life cycle. Here are two examples:
- Error-Free Data Extraction
Processes such as data entry and extraction are completely automated. A loan management system can recognise and extract data from over 700 file formats, thus eliminating the scope of errors
- Comprehensive Data Integration
Such a system can also pull data from external sources such as account aggregators, credit bureaus, and the Goods & Service Tax portal, thus closing information gaps quickly.
Data-driven Underwriting Process
Underwriting is one of the most important in the lending cycle. One key outcome is assessing the risks of offering a loan to a borrower. However, assessing risks with manual underwriting processes is challenging due to the sheer volume of data that needs analysis.
Data types generally include bank statements, income/ revenues statements, credit history, invoices, and GST returns.
A loan management system automates the process, segregating all data into 50 to 60 inflow and outflow categories, thus accounting for every financial transaction a borrower makes.
This process paints a holistic picture of a borrower’s finances, and the system also produces a data-driven credit score to aid lending decisions.
Reducing the Potential for Loan Fraud
The growth of loan fraud poses a real threat to a lender’s ability to be a sustainable, profitable business. The incidence of fake documents, inflated financial accounts, and identity theft are three potential activities that can lead to loan fraud.
To counter this threat:
- A superior loan management system can flag unusual patterns in transactions.
- It spots minute inconsistencies in documents, which could be a sign of fake documents.
- It can also detect inconsistencies in information related to the borrowers’ identities. For instance, inconsistencies in spelling, addresses, and other identifiers can raise alarms about potential impersonation by a borrower.
The ability to detect loan fraud early on can help lenders avoid lending to fraudulent borrowers. Lenders can avoid being investigated for lack of compliance. They can safeguard the business and prevent a potential shutdown in the future.
Emphasis on Customised Solutions
Every borrower has unique needs. Based on the financial analysis of a borrower’s data, the loan management system recommends customised solutions for borrowers. Here are some examples:
- It can recommend loan products that are relevant to the borrower rather than cookie-clutter products that make loans more expensive and challenging to repay.
- Debt recovery is another area where loan management software adds value. The system customises debt recovery strategies based on the borrower’s real-time financial data, including personalised communication, payment reminders, and multiple payment modes.
Predicting Future Trends
The rapid access to so much consumer data puts lenders in a position to understand borrower behaviour and patterns in depth.
AI-based loan management systems, in particular, enable lenders to predict the repayment potential and needs of individual borrowers, as well as those belonging to a similar target audience. For example, small businesses owned by women entrepreneurs in rural Maharashtra.
Using customised dashboards, lenders can slice and dice data to their advantage. In turn, they can act upon these predictions by innovating their product lines and offering relevant services and products to their customers.
Impact of a Loan Management System
Here is what an agile loan management system can deliver:
Quick Turnaround on Loan Applications
Today, borrowers seek quick approvals on their loan applications. Adoption of a loan management system expedites the entire process.
Quicker turnarounds improve businesses’ potential to turn leads into customers and repeat customers. They also prevent leads from taking their businesses to rival lenders.
Higher Return on Investment (ROI)
Lenders can function with lean, collaborative teams and run cost-effective operations. They can reduce expenditures in areas such as debt recovery and collections.
Enhancing risk assessment and fraud detection can help them comply with regulations and reduce the number of Non-Performing Assets. These factors collectively drive higher ROI.
Bring Scalability to The Business
Ambitious businesses looking to scale quickly can do so efficiently, securely and cost-effectively with the use of a loan management system. They can:
- Tap diverse markets by effectively filling credit gaps
- Deliver more value to a spectrum of borrowers’ profiles and personas
- Expand their product lines quickly
- Diversify and offer loans across the education, housing, automobile, business loan, and personal loan spectrum.
Key Takeaway
Lending companies looking to drive more revenues and profitability must automate and improve efficiency throughout the lending workflow, from the time a borrower applies for a loan to the completion of repayment.
The adoption of an automated loan management system is helping to optimise operations, offer relevant solutions, and stay competitive in a fast-growing, disruptive lending landscape.
Finezza offers comprehensive tools and solutions to manage your lending portfolio. Our end-to-end lending management solutions are trusted by brands like ftcash, Hiranandani Financial Services, Gromor Finance, and UC Inclusive Credit, to name a few.
Finezza’s intuitive bank statement analysis software analyses bank statements quickly and accurately and detects potential fraud.
Book a demo to know more.
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