Credit risk analysis is a vital process that helps lenders assess the possibility of the borrower defaulting and the loss they may incur if the borrower fails to repay the contractual loan obligations. It often goes beyond credit analysis, primarily focusing on the borrower’s creditworthiness. In contrast, credit risk analysis assists a lender in achieving their business goals by evaluating the cost and benefit of taking credit risk.
A GlobeNewswire report suggests that the global corporate lending market, growing at a CAGR of 9.6%, will reach $11,285.05 billion by 2026, which further stresses the need to manage credit risk effectively for lenders. Moreover, the global financial crisis in 2008-09 emphasised the risks lenders face when they extend credit to customers with poor credit histories.
One effective approach could be adopting the automation of traditional banking activities, including risk analysis and scoring, using lending management software that relies heavily on machine learning, artificial intelligence, and data analytics. These solutions enable lenders to manage their risks more effectively.
In this blog, we focus on the role of lending management software in credit risk management.
Lending Management Software: Role of Credit Risk Analysis and Scoring
Credit risk analysis helps lenders determine a borrower’s capability to meet their loan obligations and evaluate the probability that they will default.
With smart Lending Management Software, assessing credit risk helps lenders take on an acceptable level of risk which helps them achieve their business goals. They can use the results to develop policies. It can help them reach specific goals while protecting themselves from potential losses.
Additionally, credit analysis can help lenders formulate policies regarding interest rates. Lenders can set interest rates in line with the risk profile of a borrower. They may set higher rates for applicants posing a higher risk to protect themselves from the loss if a borrower defaults.
How Lending Management Software Aids Credit Risk Analysis and Scoring?
Credit risk analysis and scoring help lenders make informed decisions and mitigate risk. Manual risk assessment is lengthy and time-consuming, resulting in delays for borrowers and is prone to errors and human biases.
Automating credit risk analysis and scoring using lending management software helps deal with these issues and offers additional benefits.
For example, the Bank Statement Analysis tool from Finezza is an automated tool that helps lenders develop a more practical index to reduce NPAs and bad credit decisions.
Automating credit risk analysis using loan management solutions allows lenders to concentrate on more viable loan applications and price risk more precisely based on a more holistic picture of the applicants’ credit health.
5 Benefits of Using a Lending Management Software
Lending management software offers lenders the following benefits:
1. Improved Accuracy
Lending management software uses sophisticated algorithms to analyse data and identify risk factors to improve the accuracy of credit risk analysis and scoring. The use of advanced data analytics and rule-based decision-making reduces bias and human error.
Also, the machine learning algorithms and analytics factor in current market trends and borrower behaviour because of real-time data visibility and help build more comprehensive borrower profiles.
Consequently, the loan management software offers a more accurate evaluation of creditworthiness as it analyses large volumes of data and helps lenders enhance their loan portfolio quality and foresee potential contingencies.
2. Increased Efficiency
Lending management software increases the efficiency of the credit risk analysis and scoring processes. Automation helps in quicker credit risk assessment without compromising accuracy.
It also expedites and simplifies risk assessment lending operations by harnessing the power of artificial intelligence. Features like customised credit analysis based on data from multiple institutions and a view of loan history, repayment history, a summary of borrowings, and an ‘Enquiry to Success’ ratio are readily available, which aid faster decision-making.
3. Comprehensive View
Traditionally credit scoring models focus on a few metrics like the debt-to-income ratio, repayment history and credit utilisation ratios for assessing an applicant’s creditworthiness.
However, in current times lenders want to look beyond these parameters to assess an applicant’s ability to repay loans. Alternative data points help provide a more comprehensive picture of the applicant and can help in better risk assessment.
Bank transactions provide valuable insights into an applicant’s income, expenses and spending pattern. This combined with GST returns data of a business, gives a multidimensional insight into an individual’s or a business’s financial health and the future outlook.
4. Better Fraud Detection
Loan management software with analytics-aided features, digital credit assessment credit-collection analytics, and early-warning systems help devise a robust fraud detection system.
Finezza’s Collection Delinquency Management leverages Artificial Intelligence to protect lenders from risks of fraudulent activities. The system can detect suspicious activities and prevent potential fraud by analysing patterns, historical data and outliers.
Features integrated into the loan management software help identify anomalies and trends that point to fraudulent conduct and risky loan applications. Minimising the risk of granting fraudulent loans helps save time and resources that may have to be used if there is fraud.
5. Manage Risk Proactively
The borrower’s credit health, a focal point at the start of the lending cycle, which can sometimes deteriorate during the loan lifecycle, is often ignored after loan disbursal.
Continuous monitoring can help identify early warning signs of the deteriorating financial health of borrowers. Lenders can protect their interests better and take the required steps to manage credit risk more effectively.
Real-time loan monitoring with loan management software can help lenders be proactive and have a forward-looking approach toward risk management.
Conclusion
Credit risk management is crucial for a lender’s success and growth. To accelerate this process, lending management software improves the accuracy and efficiency of risk analysis and fraud detection, ultimately enabling lenders to manage risks better and protect their interests.
As a cloud-based platform, Finezza offers a diverse array of solutions like the Loan management system, Collection Delinquency Management and more to allow lenders to manage risk in a more intelligent, data-driven and effective manner.
Reach out to us to learn more about our solutions and how they can assist you!
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