The lending industry has grown exponentially in the last few years. A mix of automated loan processing system, banks, and Non-Banking Financial Companies (NBFCs) are aggressively growing their loan verticals. On top of that, several payment platforms and eCommerce companies are also entering the highly competitive lending space.
In the third quarter of 2023, digital lenders disbursed approximately 18 million loans worth INR 18,537 crore. This figure was up by 147 % in terms of year-on-year volume and 118 % in terms of the total value. By 2030, the digital lending market is expected to be worth $ 5.5 billion, growing at a compound annual growth rate of 33.5 %.
While this growth is commendable, the industry is becoming increasingly competitive. As a result, companies are investing more in customer acquisition costs. Adding to the woe, several additional costs prevent them from scaling quickly and remaining profitable.
Let’s understand the source of these fund leakages and the role of automated loan processing systems in reducing these additional costs.
What Is An Automated Loan Processing System?
The automated loan process system is a cloud-based, AI-enabled solution that automates all stages of the loan processing workflow. This solution comes with several advantages. For instance:
- It eliminates the need for paperwork or physical engagement between borrowers and lenders.
- The software also leverages optical character recognition (OCR) and machine learning to read borrower financial data and segregate it into categories such as balance sheets, income, loan repayments, expenses, and cash flow.
- The entire lending process is completely streamlined, from identifying loan applications that qualify and efficient underwriting to funding the loan.
Therefore, the automated loan process system addresses a wide range of challenges that impact the business outcomes of lenders.
Key Factors Triggering Higher Costs
The following challenges often translate into higher costs for lenders:
1. A Labour-intensive Process
Many lending businesses still process large parts of the lending cycle manually. For instance, lending teams still depend on massive human intervention to review financial documents. This is an unsustainable solution, which results in errors, duplications, and higher labour costs.
2. Large-scale Loan Applicant Drop-offs
Lenders with a more considerable loan processing turnaround time have higher drop-offs. In a competitive market, borrowers favour lenders who respond the fastest. Hence, low turnarounds result in a high opportunity cost.
3. Poor Fraud Detection Capabilities
The human eye cannot always catch hidden financial data in financial documentation. It may also find it challenging to recognise fraudulent documents with minor edits. Hence, lenders are at risk of processing loans that can result in loan fraud, which comes with substantial financial and reputation damage.
4. Inability to Assess Creditworthiness Accurately
Lenders cannot extract enough data points to determine creditworthiness without access to the right technology accurately.
Let’s take an example. Traditionally, loans are given based on a credit score. So, the lender may reject the application despite the business’ healthy balance sheet. On the other hand, the lender may accept a loan application for a business which looks healthy on paper but is, in fact, in massive debt.
The inability to assess creditworthiness raises the potential for a rise in non-performing assets. There’s also an opportunity cost attached to rejecting potentially good customers.
5. Lack of Compliance
Regulatory authorities such as the Reserve Bank of India continuously change the rules based on real-time shifts in the financial markets. Legacy loan systems are unable to implement the changes so quickly. Hence, lenders are at risk of incurring higher costs due to the inability to be compliant.
How Automated Loan Processing System Facilitate Cost-cutting
Here’s a snapshot of how automated loan processing systems help streamline the entire loan management cycle and drive superior business outcomes.
1. Automates Key Processes, Reduces Errors
The entire loan management workflow is automated, thus reducing human intervention and errors and oversights. This solution can read documents in over 700 formats, categorise all transactions, and develop a financial creditworthiness score based on the data.
Consequently, with automated loan processing systems, businesses can run lean teams and utilise team bandwidth in relevant ways.
2. Raises Ability to Detect Potential Fraud
Loan frauds cost companies millions. With the volume of financial information increasing, the ability to detect potential fraud at scale is a valuable asset for businesses. Automated loan processing systems are equipped to detect unusual patterns and recognise inconsistencies in financial data. This solution also leverages technology to identify fraudulent documents and detect identity fraud.
3. Make data-driven decisions
Automated loan processing systems can analyse several data points to create a more authentic and accurate financial creditworthiness score. This functionality levels the playing field for first-borrowers while scrutinising established businesses more closely.
Lenders can also customise dashboards based on data that can help them make informed decisions. These benefits help businesses bring down the number of non-performing assets. They can also identify first-time borrowers in good financial health and turn them into long-term customers.
4. Quicker Loan Turnaround
Lenders that can reduce loan application turnaround time have the best chance of increasing their market share. Adopting an automated loan processing system increases the potential for lenders to bring efficiency, accuracy, and speed to their operations.
In the process, they can reduce the cost of customer acquisition and turn leads into customers.
5. Offer More Relevant Products
Accessing data in-depth and at scale helps businesses understand customers better and predict their needs. They can customise products rather than offering standardised products.
Hence, with automated loan processing systems, they will be able to serve customers of all sectors and scale more effectively, thus increasing the chances of repeat business.
Takeaway
Cutting costs is vital to becoming sustainable and profitable for lending businesses. The lack of access to the right technology prevents them from scaling rapidly.
This is where adopting automated lending process systems can transform this reality. It can help lending businesses reduce opportunity costs, detect potential fraud, deliver customised, relevant products, and accurately predict creditworthiness.
As a cloud-based lending lifecycle management platform, 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 is geared to analyse bank statements with speed and accuracy and detect potential fraud.
Book a demo to know more.
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