Credit Risk Management-How to Manage Credit Risk Effectively?-Credit Risk

How to Manage Credit Risk Effectively?

Credit risk is likely to lose money due to the lender's debt repayment or failure to meet contract obligations. Credit Risk Management Understanding the abundance of a bank's capital and debt loss reserves, as well as understanding the credibility of its customers 1, such losses There is a reduction process.

Credit risk management is not only a regulatory requirement, but also a business opportunity. By handling credit risk properly, banks can improve their profits, reduce their capital costs, and gain a competitive advantage in the market.

In this blog post, we will discuss some of the best ways and challenges of credit risk management. And how banks can benefit data and analytics to enhance their credit risk models and decisions.

Credit risk management measures

Credit risk management includes a number of measures to ensure that reliable borrowers are lent and potential losses are reduced. Steps are 2:

•Identity

This includes identifying sources and types of credit risk facing the bank, such as individual borrowers, corporate clients, sectors, regions ، Products etc.

•Measurement

Using different methods such as credit scoring, rating systems, portfolio models ، Includes credit risk exposure and fixing the amount of potential losses associated with each source and risk type, etc.

•Spending

This includes tracking and reviewing the exposure and performance of each borrower and portfolio credit risk over time ، Which uses indicators such as default rates, crime rates, recovery rates, etc.

•Reduction:

This includes taking steps to show credit risk and reduce losses, such as diversifying portfolio, setting boundaries and thresholds ، Imposing contracts and suicide attack requirements, restructuring or refinancing loans, etc.

•Reporting:

This includes delivering credit risk information and analysis to relevant stakeholders, such as senior management, board of directors, regulators, investors, etc.

Credit risk management principles

Credit risk management should guide some important principles that ensure its effectiveness and alignment with the bank's objectives and strategies. Some of these principles are 3:

• Risk Hunger:

The bank should explain its risk appetite ، Which is the amount and type of credit risk that it agrees to accept in achieving its business goals. Risk hunger should be in line with the bank's capital adequacy, profit, liquidity and credibility.

•Risk Culture:

The bank should promote a risk culture that promotes awareness, accountability, transparency and moral behavior between all staff involved in credit risk activities. Risk culture should be supported with the help of appropriate incentives, training, and governance structures.

•Risk Framework

The bank should establish a comprehensive and consistent risk framework in which all aspects of credit risk management, such as policies, procedures ، Include roles and responsibilities, tools and systems, data quality and availability, etc.

•Risk Assessment

The bank should regularly and fully assess its creditors and departments, which use both quality and quantitative methods. Risk assessment should consider both current and future situations, as well as stress scenarios.

•Risk mitigation

The bank should implement effective risk mitigation strategies that balance the costs and benefits of credit risk exposure and loss reduction. Risk mitigation strategies should be tailored to the specific characteristics and requirements of each borrower and portfolio.

•Risk Review

The bank should conduct periodic and independent reviews of its credit risk management methods and performance using both internal and external auditors. The reviews should identify any gaps or weaknesses in the credit risk framework and provide recommendations for improvement.

Examples of credit risk management

To clarify how credit risk management works in practice ، Let's look at some examples of how banks implement credit risk management measures and principles on a variety of lenders.

Personal borrowers

Personal borrowers are those who apply for loans for different purposes, such as buying a house or a car, paying education or medical expenses ، Or stabilizing loans.

To handle credit risk associated with personal lenders, banks generally use the following methods:

•Credit scoring:

This is a numerical method that assigns scores to each borrower based on their personal information, such as income, assets, liabilities, credit history, etc. The score reflects the default possibility and helps banks decide whether to approve or reject the loan application ، Also, interest rates and other loan terms have to be determined.

•Self-attack:

 It is a solid asset that the borrower promises to protect the debt, such as a house or car. If the borrower fails to repay the loan, the bank may seize and sell a suicide attack to recover some or all the outstanding amounts.

•Letters:

These are contract clauses that impose certain responsibilities or restrictions on the borrower, such as maintaining the minimum income level ، Do not take additional loans, or provide regular financial statements. If the borrower violates any covenant, the bank may declare the loan by default and demand immediate payment.

Corporate borrowers

Corporate borrowers are businesses that apply for loans for a variety of purposes, such as expanding operations, investing in new projects ، Or re-financing existing loans.

To handle credit risk associated with corporate borrowers, banks generally use the following methods:

•Credit Rating:

This is a liter grade that reflects the reputation of business based on its financial performance, industry perspective, market position, etc. The rating is usually assigned by an independent agency, such as standard and poor or moody ، And it helps banks assess the risk and return of lending to a business, as well as compare it to other businesses in the same sector or region.

•Surveillance:

This is a process where a group of banks jointly provide a large loan to a single borrower, such as a multinational corporation or government agency. By sharing the amount and risk of debt in multiple banks, each bank reduces its individual exposure and diversifies its portfolio.

•Securitization:

This is a process where the bank transfers some or all its loans to a particular purpose vehicle ( SPV ), The capital then issues securities to investors in the market in support of cash flow from loans. By selling loans to SPV, the bank removes them from its balance sheet and frees the capital for new loans.

Benefits and challenges of credit risk management

Credit risk management offers banks a number of benefits, such as:

•Increasing Profits:

 Effective handling of credit risk, banks can improve their lending decisions, pricing strategies, and portfolio formation ، And so they can increase their interest income and fee revenue, while reducing their supply costs and written tasks.

•Capital Reducing capital expenditures:

By effectively handling credit risk, banks can improve the proportion of their capital ، Which measure their ability to absorb losses caused by unexpected events. This can reduce their financing costs and regulatory capital requirements, as well as increase their credit ratings and market credibility.

•Competitive Benefit:

By effectively handling credit risk, banks offer their customers better products and services, such as customized solutions ، Flexible conditions, can vary from your competitors, fast approval, etc. This can increase the loyalty and retention of their customers, as well as attract new customers and markets.

However, credit risk management banks also face some challenges, such as:

•Data availability and quality:

banks to handle credit risk effectively, banks have their creditors and departments, such as financial statements, credit reports ، Reliable and timely data on market indicators, etc. need access. However, acquiring and maintaining such data can be costly and complex, especially emerging markets, new products ، Or for large-scale transactions.

•Model accuracy and validation:

banks to effectively measure credit risk ، Banks need to use sophisticated models that achieve complex interactions and dynamics of credit risk factors, such as default possibilities; loss default ، Default exposure, etc. However, the development and validation of such models may be difficult and time consuming, especially low frequency or high intensity events ، Such as for financial crisis or natural disasters.

•Regulatory Compliance and Alignment:

Complying with regulatory requirements for credit risk management, such as Basel III or IFRS 9, Banks need to align their domestic policies and procedures with external standards and guidelines. However, such alignment can be difficult and costly, especially for cross-border or multilateral operations.

How data and analytics can increase credit risk management

Data and analytics are essential tools for credit risk management, as they enable banks:

•data Improve the availability and quality of data:

Data and analytics banks collect data from various sources and formats such as internal databases, external vendors, web scraping ، Can help integrate, cleanse and enrich, text mining, etc. This can improve the complete, consistency, accuracy and timeliness of data for credit risk analysis.

•Improve model accuracy and validation:

Creating, testing, testing, testing, testing, testing, credit risk measurements using modern techniques such as machine learning to data and analytics banks ، Can help calibrate and verify; artificial intelligence ( AI ), simulation, scenario analysis, etc. This can improve the strength, sensitivity and predictive power of models for credit risk assessment.

•Improve Regulatory compliance and alignment:

Data and analytics can help banks Monitor, report, and disclose their credit risk exposure and performance using standard formats and metrics, such as expected credit loss ( ECL ) ، Risk Weight Assets ( RWA ), Credit Value Adjustment ( CVA ), etc. This can improve the transparency, consistency and comparison of data for credit risk management.