Payroll APIs will be the next frontier for lending
Borrowing has always been fuelling the growth of developing economies as corporates and even retail borrowers’ take out loans to fund expansion or other such big purchases. In India, lending by banks and NBFCs has become organized with multiple checks and balances before sanctioning the loan. This is due to rising NPAs, and thus borrowers are facing difficulty in getting a loan. There are multiple stages discussed below which the borrower has to go through during the loan application stage, right from applying for a loan to submitting his income proofs.
The loan process usually starts with the borrower applying for a loan by filling a loan application form to finance his purchase. After this, he has to submit all the necessary documents which the lender asks for. After which, the lender will analyze all the documents and check your credit score to take an approval or rejection decision on your loan application.
One of the most critical stages in this process is credit underwriting, which involves assessing the borrower’s creditworthiness. In this stage, the lender checks the borrower’s credit score, current debt levels, any financial frauds they have committed in the past, income, credit length, etc.
Problems With the Lending System in India
After doing an in-depth analysis, the lender judges the borrower’s ability to repay the loan amount they have applied. Underwriting is a cumbersome process that takes a few days, even sometimes weeks or months.
Out of all the aforementioned factors, the borrower’s credit score is given priority by the lenders. This is because this score tells a lot about your money management habits in the world of finance. The maximum credit score in India is 900, and one has to have a credit score of at least 700 to be eligible to get the loan. If you have a credit score below 500, then there are high chances that you will face difficulty in getting a loan. This is why many borrowers are denied credit by established banks and other financial institutions in India.
Also, there is a concept in loans, which is the ‘intent to pay’ and the ‘ability to pay’. The lender can judge the ability to pay based on an analysis of your credit profile and income proof documents. However, the intent to pay is a pretty abstract concept that cannot be really quantified in finance.
How is the FinTech Revolution changing the Ecosystem?
You have a fair idea now about the traditional process of underwriting that is cumbersome in this fast-paced world. FinTech companies are now unleashing the potential of payroll data with open banking via APIs (Application Programming Interface). The lenders are now getting this data and other employment information to make informed decisions on the loan application to curb NPA frauds.
Application of Payroll Data
This confidential data is accessed after taking consent from the borrower as it has his salary and work-related data. It also helps the lenders design a repayment schedule based on the payroll data of the borrower so that repayment becomes easy for him. The existing processes are becoming efficient with the advent and rapid adoption of these modern technologies.
Updated and Reliable Data
When the lender asks for banking data from the borrower, there are chances that the data will not be recent. It can be a month old or a quarter old. On the contrary, the payroll API-based data is precise and updated to the latest minute. This accuracy and reliability of data help in credit underwriting decisions.
Increased Lead Conversion
The lead conversion ratio is much higher in cases where payroll data is involved compared to borrowers’ banking data. Many studies conducted show that borrowers are more comfortable sharing their payroll-related information instead of their banking-related data.
Assessing ‘Ability to Pay’ information
Income data is not available in credit score reports given to lenders by credit bureaus like Experian, TransUnion CIBIL, Equifax, CRIF Highmark, etc. The credit score only gives you the historical repayment habits of the borrowers, which only reflects their willingness or intent to pay.
But, what about his ability to pay?
Income data can be extracted from APIs based on payroll data to determine the borrower’s ability to pay. Assessing the ability to pay is equally important as assessing the intent to pay. This is because, let’s say, both Mukesh Ambani and you have a credit score of 850, indicating a very high intent to pay. However, your and Mukesh Ambani’s income levels are completely different, and thus your ability to pay will also be different. We need income proof documents to assess this ability to pay that can be taken from payroll APIs.
Fintech companies have changed the game’s dynamics completely with innovation in risk assessment during lending in the past few years. To provide the best services to their customers, these Fintech companies automated the entire underwriting process with data fed into machine learning algorithms that are super quick. Thus, there is better transparency and no human intervention, as decision-making is data-driven and free from bias. This new technology-driven lending landscape is here to stay and rule going forward. Traditional banks are now collaborating with Fintech players to harness this limitless potential of data and technology to use that data to make informed decisions.
Tartan bringing the change
Innovation in the payroll space is booming, proving it as the next frontier in the FinTech landscape. Payroll attached APIs are fast, secure, reliable, efficient, and help FinTech innovators explore other use cases that deliver value to customers.
Tartan is pioneering user consent-driven payroll data exchange in India, which plays different roles in people’s daily lives behind the scenes, making their financial lives easier. Tartan’s solution strengthens the gap by providing a payroll API solution to smoothen the process of Income and employment verification. If you’re interested in seeing a demo get in touch.
We hope you now have a fair understanding of how Payroll APIs help in making lending decisions. To know more, read our previous blog on Payroll APIs.
P.S. Borrowers with no credit history now stand a decent chance at getting a loan from banks.