Credit cards are an essential component of the lending landscape that bless borrowers with incredible financial convenience. It helps them navigate through occasional short terms of financial distress.
The criteria for lending decisions vary from lender to lender. Credit analysts often grapple with factors like multiple credit scores, absence of credit history, frequency of bill payment, past delinquencies, and many others to estimate if an applicant is a health risk for the credit card company. It becomes hard to judge an applicant’s ability, stability, and willingness to pay a loan through legacy processes that most credit card companies have in place.
Analysing Credit Risk
Credit analysts must delve deep into a card applicant’s ability to pay back based on the income information provided. They probe credit reports for any additional expenses that aren’t disclosed in the card application. Companies also ascertain that the applicant’s debt level is in line with others in the income band listed on their application.
Further, analysts are responsible for checking if an applicant has a consistent source of income, even in the future. They analyse if an applicant is a tenant, a homeowner, and the nature of their employment. Late payments incur a lot of expenditure on the part of the credit card company and are better avoided. Credit card companies are also counting the timeliness of previous repayments by an applicant while deciding if they want to issue a credit card to a particular applicant.
Finezza’s Solution to Credit Card Evaluation Process
Here is how Finezza’s technology can help a credit card company in the Credit Evaluation Process:
Credit Card Vendors can verify KYC through Finezza’s Advanced AI Tech.
Artificial Intelligence (AI) is revolutionising the way businesses and industries function. It is time that legacy industries like Banking and Financial Lending Services graduate from manually managed processes and embrace the many perks of automation. Letting go off the paper-heavy processes and time-consuming workflows helps credit card vendors avert data breaches and security risks. Most businesses indeed hesitate from adopting newer technologies due to concerns around their effectiveness, change management and sensitivity of the data involved.
Finezza offers a solution that mitigates the scepticism that surrounds automation. It is a framework designed to help Indian lenders like credit card vendors in digitising the creditworthiness evaluation process. It is a unique tool designed to address the business and compliance concerns of the industry, in the process of garnering better returns.
Credit card vendors often duel the data extraction challenge. For example, documents like KYC make it challenging to extract data even for digital lenders. The run of the mill process is to collect and physically submit the KYC form, followed by manual processes like scanning, uploading, verification and tagging before being stored into the database. Clearly, manual data extraction is inadequate when it comes to error-free accuracy and consistently growing demand for credit cards.
Finezza offers an OCR-based solution for document recognition and data extraction. The OCR API Finezza leverages excellence in terms of accuracy of data extraction from fields like name, date of birth and address etc. The software helps increase operational efficiency and reduce customer onboarding time for the business, polishing their ROIs.
Credit Card Vendors can Compare Credit Scores Using Finezza’s Lending Management Software.
Credit scores can be described as a pictographic view of the creditworthiness of a person. Most commonly, a credit score ranges from 300-900. A score above 750 is considered good and creditworthy. The more the score proceeds towards the 900 range mark, the better are the chances of an applicant getting a credit card.
As per the RBI mandate, credit card vendors rely heavily on credit scores of card applicants when they evaluate their applications. While different credit card vendors rely on different models for calculating credit scores, factors like payment history, duration of credit history, hard pulls, negative factors, public factors etc. count when determining an individual’s credit scores.
At the same time, there are different credit bureaus in India including, Experian, TransUnion CIBIL, CRIF High Mark and Equifax. Consequently, scoring models of all the four credit bureaus differ slightly in their computation manner. The difference is due to differences in weight factors given to various aspects like credit history, settlements and write-offs, the income: loan proportion etc. While it is true that no two scores can be the same ever, credit card vendors that rely on multiple credit scores help to offset one lower score with another excellent rating.
Finezza comes with a Credit Analysis solution that generates several reports which evaluate many combinations of various data points that aggregate scores from multiple credit bureaus. It caters detailed insights into the creditworthiness of an applicant. Credit card companies benefit from an overall credit score, which in turn allows them to provide a broader range of clients. Further, it significantly reduces the time taken to process a loan application, leading to streamlined card sanctioning of credit cards.
Credit Card Companies can Reduce NPAs Through Finezza’s Efficient Credit Risk Management.
Advancements in computing power and advanced analytics or even the rise of big data helps businesses improve their processes and outcomes. Data helps decision-makers gain a comprehensive view of their companies and make profitable decisions.
The term ‘credit risk’ defines the potential for loss due to the failure of a borrower to make a repayment. Such uncertainty can lead to a complete or partial loss of principal, loss of interest, and disruption of cash flow for a credit card business. This makes it even more critical to identify, measure, and mitigate risk. Risk analytics powered with ML algorithms can provide actionable insights from the massive amount of data generated from various sources. Credit card companies have risk management teams to evaluate the risk associated with card sanctioning in real-time.
Finezza’s NBFC software comes equipped with ML backed risk analytics that shoots real-time alerts to risk managers when anomaly surfaces. Risk management teams at a credit card company can monitor client portfolios in real-time and evaluate performance across critical parameters. Machine learning capabilities help credit card vendors identify high-risk customers and conduct critical screening to reduce future losses.
All in all, Finezza unique framework provides an end-to-end solution to credit card vendors who struggle with hardships of creditworthiness assessment and face resultant losses. Use of Finezza’s state of the art technology allows credit analysts at credit card companies to streamline their decision-making process, making it error-free and risk proof and improving customer satisfaction in the long run.