Top Lending Risks for Banks & How To Prevent Them
Every year, major events impact financial markets, the economy, and banks, whether geopolitical, financial, or something completely unanticipated like a global pandemic. The years 2024 and 2025 will be challenging for banks, even without significant surprises. Inevitably, banks will face lending risks that can impact their profitability and stability. The table below lists the top 10 lending risks for banks, risk assessments by the Office of the Comptroller of the Currency (OCC), and strategies to mitigate those risks.
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Top 10 Lending Risks for Banks & How To Prevent Them |
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Risk |
Description |
OCC Assessment |
Prevention Strategies |
|
1) Credit Risk |
Risk that borrowers will fail to repay their loans. |
Increasing due to inflation, declining corporate profitability, and potentially slow economic growth |
– Creditworthiness assessment – Risk-based pricing – Loan diversification – Collateral requirements |
|
2) Interest Rate Risk |
Risk that changes in interest rates will negatively affect a bank’s financial condition. |
Increasing due to continuing high interest rates |
– Interest rate swaps – Gap analysis – Duration matching |
|
3) Liquidity Risk |
Risk that a bank will not be able to meet its short-term financial obligations. |
Increasing due to broader market liquidity contraction |
– Liquidity buffers – Stress testing – Diversified funding sources |
|
4) Operational Risk |
Risk of loss due to inadequate or failed internal processes, people, systems, or external events. |
Elevated due to continuing cyberthreats and heightening risks of fraud and error from digitalization efforts |
– Strong internal controls – Employee training – Technology investments – Incident management plans – Robust cybersecurity |
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5) Market Risk |
Risk of losses due to changes in market prices, such as interest and exchange rates. |
Increasing due to the speed and magnitude of rising rates and reduced market liquidity. |
– Value-at-risk analysis – Limit setting – Hedging strategies |
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6) Compliance Risk |
Risk of legal or regulatory sanctions due to non-compliance with laws and regulations. |
Elevated due to heightened focus on equal access to credit, fair consumer treatment, and partnerships with third parties. |
– Regulatory monitoring – Compliance programs – Internal audits |
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7) Climate-Related Financial Risk |
Risks of damage or loss related to the physical effects of climate change and the shift to a lower-carbon energy supply. |
Elevated due to early stages of understanding climate-related financial risk analysis and ways to mitigate risk |
– Integration of climate-related financial risk into strategic planning – Transparent climate-related financial disclosures – Green project financing |
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8) Reputational Risk |
Risk of damage to a bank’s reputation due to negative public perception. |
N/A |
– Transparency – Corporate governance – Crisis management |
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9) Concentration Risk |
Risk of loss associated with exposures that could produce losses large enough to threaten the bank’s core operations. |
N/A |
– Exposure limits – Portfolio diversification – Regular reviews |
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10) Artificial Intelligence-Related Financial Risk |
Risk of loss or damage as a result of lack of visibility, potential bias, privacy concerns, third-party and cybersecurity risks, and inaccurate responses that appear credible. |
Emerging due to the early stages of AI use by financial institutions and rapid changes in this area of financial risk |
– Incorporation of AI into existing risk management frameworks – Implementation of AI in a safe, sound, and fair manner |
Technologies to Mitigate Top Lending Risks for Banks
Banks can use various technologies to reduce lending risks, each leveraging different aspects of modern tech to improve risk management and decision-making processes:
Data Analytics
How It Works: Data analytics involves processing and analyzing large and diverse datasets to uncover hidden trends, patterns, and correlations.
Application: Banks can use big data to enhance their understanding of borrower behavior, assess risk more comprehensively, and make data-driven lending decisions. Analyzing social media activity, utility payments, and other non-traditional data sources can provide additional insights into a borrower’s creditworthiness.
Robotic Process Automation
How It Works: Robotic process automation (RPA) uses software robots to automate repetitive and rule-based tasks previously done manually.
Application: In the lending process, RPA can automate data entry, document processing, and compliance checks, reducing human error, speeding up loan approvals, and freeing human resources for more complex tasks.
Credit Scoring Technologies
How It Works: These technologies use statistical models to evaluate the creditworthiness of potential borrowers based on various financial indicators and behaviors.
Application: Enhanced credit scoring tools can integrate traditional credit data with alternative data sources to provide a more comprehensive and accurate risk assessment, helping banks make better lending decisions.
Risk Management Software
How It Works: These platforms provide tools for identifying, assessing, and managing risks across various aspects of banking operations.
Application: Risk management software can help banks monitor and mitigate credit risk, market risk, operational risk, and compliance risk through advanced analytics, reporting, and real-time monitoring capabilities.
Cybersecurity Solutions
How It Works: Advanced cybersecurity tools and practices protect digital assets and sensitive information from cyber threats.
Application: By implementing robust cybersecurity measures, banks can protect borrower data, maintain regulatory compliance, and reduce the risk of data breaches, which can have significant financial and reputational impacts.
Artificial Intelligence and Machine Learning
How It Works: Artificial intelligence (AI) and machine learning (ML) algorithms analyze vast amounts of data to identify patterns and predict outcomes. In lending, these technologies can enhance credit scoring models, predict loan defaults, and assess borrower creditworthiness more accurately.
Application: ML models can continuously learn and improve using historical data, providing more precise risk assessments and personalized loan offers.
defi’s Platforms Can Help Reduce Lending Risks
defi’s loan origination platforms offer industry-leading features to reduce lending risks and streamline loan origination processes. These include:
- Access to alternative credit data sources and data analytics tools
- Automated decisioning, conditioning, deal structuring, and funding to maximize return on investment while controlling risk
- Customer-facing portals and other technology to improve customer service
- Flexibility to identify and target specific market segments and change business models
- Integration with a broad ecosystem of third-party services and partnerships, such as compliance and risk management services
- Support for complex pricing matrices and models
The benefits of an industry-leading loan origination platform are clear. Improved customer satisfaction leads to revenue growth for lenders. So let’s talk about what you need.
Getting Started
defi SOLUTIONS is redefining loan origination with software solutions and services that enable lenders to automate, streamline, and deliver on their complete end-to-end lending lifecycle. Borrowers want a quick turnaround on their loan applications, and lenders want quick decisions that satisfy borrowers and hold up under scrutiny. With defi’s originations solutions, lenders can increase revenue and productivity through automation, configuration, and integrations and incorporate data and services that meet unique needs. For more information on lending risks for banks, contact our team today and learn how our cloud-based loan origination products can transform your business.
