Optimize Credit Risk Management by Leveraging Lending Analytics Solution
Banks and lending institutions must storm through many challenges to grow their business and one of the inherent risks in lending business is Credit risk. Mitigating such risks can be a cumbersome task. But with the use of data analytics and business intelligence solutions, credit risk can be handled well, decisions can be made faster and disastrous situations can be averted.
What is Credit Risk?
One of the most common types of risks that banks, financial and lending institutions have to face is credit risk. Simply put, credit risk is about a customer’s inability to repay the loan amount to the lender.
Before a bank or lending institution issues a loan, they do a thorough credit risk assessment on various parameters of the customers. They may check their credit score, net worth, past loan or credit history, etc.
Even then, there are chances that a customer may default on the loan’s principal and interest and may or may not have the ability to repay the principal and interest, fully.
How Do Lenders Mitigate Risk?
Over the years, lending institutions have adopted various strategies to manage risk and avoid a disastrous situation for their business. Stress testing, setting deadlines, and worst-case scenario plans are some ways lenders try to keep bad debts at bay.
Another strategy that banks and lending institutions have adopted to mitigate risk is the 5 C’s Credit Framework. This framework helps to provide a holistic view of the customer and analyses each individual’s repayment capabilities on various parameters before a loan is issued to them. The assets they own, their credit re-pay behaviour, economic conditions, everything is taken into consideration under this credit risk mitigating strategy.
Different Types of Analysis to Mitigate Credit Risks
Credit risks are analysed by lending institutions broadly on two bases: Customer-Centric Analyses & Market-Centric Analysis.
1. Customer-Centric Analysis:
a. Individual Lending Analysis: A person’s financial health, debt to income ratio, credit score and past credit history is analysed.
b. Corporate Lending Analysis: Industry sector, current economic situation (domestic as well as global), income statements, cashflow statements, balance sheets, intellectual property, a purchase order for the future and so on are analysed for a business entity before a loan is issued.
Lending institutions use scoring mechanisms and proprietary solutions to understand the financial health of the customer.
2. Market-Centric Analysis:
In this type of analysis, the market conditions impacting the lending capacity are evaluated and assessed. Interest rate and customer segment analysis are certain types of analysis that are tracked here. This can be further broken down into three categories: Credit Structure Analysis, Sensitivity Analysis and Portfolio Analysis.
a. Credit Structure Analysis: Loan to value, quality of collateral security, lien and primary mortgage insurance and so on are analysed.
b. Sensitivity Analysis: Dynamic variables such as interest rates, estimated collateral damage, loan tenure and so on are analysed by lending institutions.
c. Portfolio Analysis: Customer segments of the lending institutions are analysed on various metrics such as average loan amount per customer, percentage of loans that could be at risk.
Intellify’s lending analytics solution can enable your lending institution understanding the credit risks and perform the above-mentioned analysis. With more than 100 KPIs and 1000+ data points, the data analytics solution pulls information from various sources and showcases it on an interactive & visually appealing dashboard.
Challenges in Credit Risk Management
Inefficient Data Management:
Lending institutions need to analyse lot of different data sets from various sources. If the right dataset is not available at the right time, it can cause delays in getting warnings or indications on Credit Risk. It will impact on financials substantially.
Absence of Risk Modelling Framework:
Unless the lending institutions have Risk modelling framework and monitoring mechanism in place, it’s very difficult to manage the Credit Risk. This is where Intellify Lending Analytics Solution helps in get the birds eye view of portfolio.
One of the most common challenges that becomes a hurdle in proper risk assessment of customers is manual reporting. Spreadsheet-based data analyses are prone to many errors. This can lead to a false risk assessment that can cause massive damage to the lending institutions.
Best Practices in Credit Risk Management
Well Defined Processes:
Having a well-defined process of loan approval helps lending businesses to be thorough in analysing each and every customer before their loan is approved. By recording and collecting data in a step-by-step way, lending businesses can organize and store data in a proper manner and at the same time, assess the credit worthiness of a customer properly.
Real-Time Portfolio Monitoring:
Having a real-time data monitoring solution that displays the customer’s profiles and credit history, helps lending businesses interpret data swiftly and make decisions based on the collected data, promptly. This helps lending businesses to get warnings and alerts to mitigate & manage risk more efficiently.
Business Intelligence Solution:
Business intelligence solutions help to summarize various datasets. You can constantly track these datasets on visually interactive dashboards and asses the credit risk associated with the portfolio.
Click here to get in touch with our experts and schedule a free live demo of Intellify’s Lending Analytics Solution.