Non-performing loans - solving challenges with AI

Non-performing loans (NPLs) are a key problem in the financial sector. They can significantly affect the financial equilibrium of banks and other financial institutions and trigger a chain reaction of economic instability. The management and control of loans is therefore of central importance. We show how AI can help to overcome these challenges.

What are non-performing loans?

Non-performing loans (NPLs) are loans where the borrower has been in arrears with the agreed payments for more than 90 days or where repayment is considered unlikely without the creditor having to take measures such as realizing collateral. These loans can arise for various reasons, such as economic difficulties of the borrower, high indebtedness or unexpected financial burdens.

Non-performing loans can be divided into different categories:

• Loan in arrears - Loans for which the agreed payments are late.
• Reorganization loan - Loans where the conditions have been changed in favor of the borrower to enable repayment.
• Uncollectible loans - Loans for which no repayment is expected and which must be written off.

What challenges arise when dealing with non-performing loans?

According to the current Report of the European Central Bank 2.6% of loans in Europe are classified as non-performing. These have a volume of around €347 billion. Although the ratio of non-performing loans (NPL ratio) has been falling for years, current inflation and rising interest rates for expiring fixed interest rates could change this in the short and medium term.

Keeping the NPL ratio as low as possible is equally relevant for banks and financial institutions. Achieving this goal and establishing a sustainable approach to non-performing loans entails several challenges that financial institutions must overcome:

a) Balance sheet charges

Non-performing loans are a considerable burden on banks' balance sheets. High NPL portfolios can impair a bank's equity and liquidity and worsen its risk profile.

b) Regulatory requirements

Banks are subject to strict regulatory requirements designed to ensure that they hold sufficient capital to cover potential losses from non-performing loans. Compliance with these requirements can be complex and costly.

c) Operational challenges

The process of identifying, monitoring and managing non-performing loans requires considerable resources and can be operationally demanding. This includes assessing the creditworthiness of borrowers, carrying out restructurings and tracking repayments.

d) Economic impact

Non-performing loans can also have a broader economic impact. High NPL ratios in a banking system can undermine confidence in the financial system and restrict lending to businesses and consumers, which in turn can affect economic growth.

How do financial institutions deal with non-performing loans?

Financial institutions use various methods to manage non-performing loans and minimize their impact:

a) Provisions and amortization

One of the first things banks do is to set aside provisions for potential losses. These provisions affect the bank's income statement and serve to cover expected losses. If a loan is classified as uncollectible, it is often written off.

b) Restructuring and refinancing

Another approach is to restructure or refinance the loan. This may involve extending the term, reducing the interest rate or making other adjustments to help the borrower repay their debt. The aim is to bring the loan back to a performing status.

c) Sale of non-performing loans

Financial institutions can also sell non-performing loans to specialized companies that focus on collecting such debts. This can help banks to clean up their balance sheets and gain liquidity.

d) Enforcement and realization of collateral

If all else fails, banks often resort to foreclosure and realization of collateral to recover some of the lost capital. This may include the sale of real estate or other assets that served as collateral for the loan.

How can AI simplify the handling of non-performing loans?

Artificial intelligence (AI) offers innovative solutions to overcome the challenges of dealing with non-performing loans and increase the efficiency of banks.

a) Early identification of risk loans

AI can help to identify potential risk loans at an early stage before they become non-performing. By analyzing large amounts of data and using machine learning algorithms, patterns and anomalies can be identified that indicate an increased risk of default.

b) Automation of processes

AI can solve many of the Automate manual processesassociated with the management of non-performing loans. This includes checking creditworthiness, monitoring payments and carrying out restructurings. Automated systems can work faster and more accurately than human employees, thereby increasing the efficiency of banks.

c) Optimization of credit valuation

AI models can optimize credit scoring by taking into account a variety of factors and performing comprehensive risk analyses. This enables banks to make more informed decisions about granting loans and managing existing loans.

d) Improving customer communication

Through the use of AI-supported chatbots and virtual assistants banks can improve communication with borrowers who are having difficulties repaying their loans. These technologies can provide round-the-clock support and suggest personalized solutions.

e) Predictive analytics

Predictive analytics, a form of predictive analysis, can be used to forecast future trends and risks associated with non-performing loans. This enables banks to take proactive measures and address potential problems at an early stage.

Konfuzio and non-performing loans

Konfuzio is software that uses the latest technologies for data extraction and processing. It specializes in the needs of banks and financial institutions and helps to make processes more efficient through automation and optimization. Konfuzio offers several advantages in the context of non-performing loans:

a) Automated document analysis

Konfuzio uses artificial intelligence and machine learning to process documents automatically analyze and extract relevant information. This can be particularly helpful when it comes to assessing the creditworthiness of borrowers and sifting through relevant documents quickly and accurately.

b) Efficient data processing

The platform can process large amounts of data in a short time, which significantly improves the speed and accuracy of the assessment and management of non-performing loans. By automating data processing, errors can be minimized and resources saved.

c) Integration into existing systems

Konfuzio allows himself Seamlessly integrate into banks' existing systems and processes. This means that banks do not have to fundamentally change their existing workflows, but can benefit from the additional functions and increased efficiency.

d) Improved decision-making

By providing accurate and up-to-date data, Konfuzio helps banks to make more informed decisions. This is particularly important when evaluating restructuring or refinancing options for non-performing loans.

e) Reduction of manual tasks

Many of the time-consuming manual tasks associated with managing non-performing loans can be automated with Konfuzio. This includes extracting information from contracts, monitoring incoming payments and generating reports.

f) Scalability and flexibility

The platform is scalable and can be adapted to the specific needs and requirements of a bank. This makes it a flexible tool that is suitable for both large banks and smaller financial service providers.

Conclusion

Non-performing loans represent a significant challenge for banks. However, with the right strategies and technologies, these challenges can be overcome and financial risks in the lending business minimized.

The use of artificial intelligence offers promising opportunities to improve efficiency and accuracy in dealing with non-performing loans. By identifying risks at an early stage, automating processes and optimizing credit assessment, banks can not only minimize their financial losses, but also make an important contribution to the stability of the entire financial system.

Tools such as Konfuzio can play a crucial role in this by automating data processing and thus making the entire process of managing non-performing loans efficient and future-proof.