In the contemporary world of business, expedited loan approvals and streamlined lending procedures stand as pivotal objectives for both lending institutions and loan applicants. Consequently, lenders are persistently in search of methods to enhance their operations and boost productivity. Automation, specifically within the loan underwriting phase, holds substantial potential to revolutionize this process. In this blog, we will discuss loan underwriting, challenges that financial institutions face and how automation can accelerate loan decision-making.
What is Underwriting and How it Works?
Underwriting is the procedure by which a person or a company accepts financial risk in exchange for a fee. Most of the time, this risk is associated with loans, insurance, or investments. The word “underwriter” comes from the practice of having each risk-taker sign their name under the entire amount of risk they were ready to assume for a given premium.
Even though this mechanism has evolved, Underwriting plays a critical role in the financial industry. The entire Underwriting process is based on the risk related to the borrower returning the loan on time or default.
Underwriters assess loans, particularly mortgages, to gauge the possibility of a borrower paying as agreed and the availability of sufficient collateral in the case of default.
In addition, underwriters look at a policyholder’s health and other criteria to distribute the risk as widely as feasible in insurance. Underwriting securities, which are most commonly done through initial public offerings (IPOs), aid in determining a company’s underlying value compared to the risk of funding its IPO.
Challenges with Manual Loan Underwriting
Underwriting is a critical process in the financial institution where companies assess and evaluate risks associated with loan applicants. While underwriting plays a crucial role in ensuring the financial stability of BFSI companies, there are several challenges and complexities associated with this process. Some of these challenges are-
- Data quality and availability
- Regulatory Compliance
- Data Privacy
- Risk Assessment
Although manual underwriting may seem appealing for clients with unconventional financial circumstances, like those who are new to establishing credit or have a history of financial difficulties, it can be a significant burden on providers in terms of time and resources.
How Automated Loan Underwriting Works?
Automated underwriting systems are computerized tools used by financial institutions, such as banks and insurance companies, to evaluate and make decisions on loan or insurance applications. These systems streamline the underwriting automation process by using algorithms and data analysis to assess the creditworthiness, risk, and eligibility of applicants. Here’s how they work:
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Data Collection
The underwriting process starts by collecting data from applicants. This data typically includes personal information, financial records, credit reports, employment history, and other relevant information. This data can be provided by applicants directly or obtained from various databases and credit bureaus.
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Data Verification
Using intelligent document processing solutions, financial institutions can verify the accuracy of the data provided by applicants. It can check for inconsistencies, errors, or missing information that could affect the underwriting decision.
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Risk Assessment
With automation and AI in underwriting, underwriters use sophisticated algorithms to assess the risk associated with each application. It considers factors such as credit scores, income, debt-to-income ratios, and employment stability to determine the applicant’s risk profile. These algorithms are often based on statistical models and historical data.
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Rules and Guidelines
Financial institutions can use AI to program their bot with specific rules, guidelines, and lending or insurance policies. These rules can be adjusted to reflect the institution’s risk tolerance and business objectives. For example, a bank may set a minimum credit score requirement for mortgage applicants.
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Decision Making
Based on the data, risk assessment, and predefined rules, the AUS generates an automated underwriting decision. This decision can fall into several categories, including approval, denial, or referral for manual underwriting.
- Approval: If the applicant meets all the criteria and the risk assessment falls within acceptable parameters, the system can automatically approve the application.
- Denial: If the applicant’s risk profile is too high or doesn’t meet the institution’s criteria, the system can automatically deny the application.
- Referral: In some cases, when the application is borderline or has certain complexities, the system may refer it for manual underwriting. This involves human underwriters who will review the application in more detail.
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Documentation
The automated underwriting system may also identify required documentation or additional information needed to finalize the underwriting process. For instance, it may request pay stubs or bank statements for income verification.
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Communication
The system communicates the underwriting decision to the applicant. If the decision is automated, it is usually provided instantly. If the application is referred for manual underwriting, the applicant will be informed about the additional steps required.
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Monitoring and Compliance
Automated underwriting systems can be often programmed to monitor loans or insurance policies for ongoing compliance with the institution’s policies and regulations. This may include periodic reviews of borrower creditworthiness or policyholder risk.
Overall, automated underwriting systems are designed to increase efficiency, reduce the time required for decision-making, minimize human errors, and ensure consistent application of lending or insurance policies. However, they are not completely devoid of human involvement, as some cases may still require manual review by underwriters, especially when dealing with complex or exceptional situations.
Automated Loan Underwriting’s Advantages
Using automation technologies like RPA and AI, financial institutions can leverage a lot of benefits while performing the underwriter process
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Increasing Productivity
It’s a win-win situation for both lenders and borrowers. The automated credit underwriting approach saves time for both parties, allowing for faster decision-making and fewer steps than traditional Underwriting.
The automated Underwriting process also ensures that the borrower’s desire for more rapid processing is addressed while maintaining accuracy that does not jeopardize the lender’s balance sheet. -
More Effective Decision-Making
Algorithms are incapable of making clerical errors. As a result, a human, no matter how efficient, might have a bad day, costing a lender millions of dollars in non-performing loans. However, automated algorithms are becoming better at forecasting which loans will do better because of machine learning capabilities and increased data on such loans.
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Fraud Detection that is More Intelligent
Loan fraud is on the rise. In and of itself, credit card fraud is a multibillion-dollar business. However, fraud risk is significantly and systematically reduced by automation. How? The robotic operations use powerful predictive analytics to quickly identify hazards associated with disbursing a loan to a customer. Wherever a mismatch is placed, these systems raise red lights, allowing for more accurate fraud detection.
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A customer-centric experience
Loan paperwork may be merely a back-office procedure. However, it’s vital to make sure that all of the rules are followed. With the Government imposing strict measures for banking institutions and charging hefty fines on erring institutions, there are zero scopes of error.
Hence, underwriting and loan disbursement documentation are automated, ensuring a seamless solution for the bank. -
Underwriting Consistency
The bank’s capacity to underwrite, approve, and document credit in a more personalized manner while remaining compliant with the bank’s standards is enhanced by automation. It compensates for the bank staff’s inability to interpret bank policies, which may differ from one employee to the next.
Furthermore, automation considers all loan-risk elements related to loan policies, which may overlook traditional Underwriting yet critical to a loan decision. -
Compliance with Regulatory Standards is Easier and More Effective
The best aspect about automation is that you may update a rule, and it will be applied across the board based on the filters you specify. As a result, regulatory requirements that may be neglected in a traditional system are always checked in automated methods, resulting in improved compliance.
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Improved Auditing
Automation of documenting processes simplifies the documenting and lending operations, allowing for quicker and less time-consuming audits. This is beneficial to traditional banks and credit unions since it improves accuracy and reduces fraud.
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Workflows That are More Consistent and Well-Defined
To put it another way, automation operates through a specified process that makes Underwriting well-defined, resulting in a more consistent and efficient operation. As a result, it overcomes and slashes out all weaknesses of legacy banking systems.
Conclusion
In summary, the automation of loan underwriting procedures offers substantial advantages to lending institutions. It enhances the efficiency and precision of loan approvals, reduces the likelihood of errors, and ultimately enhances overall business performance and customer satisfaction. Leveraging AI and machine learning algorithms, electronic document management systems, automated decision-making processes, digital signatures, and e-signatures, as well as automated validation, empowers lenders to streamline the loan underwriting process effectively.
AutomationEdge is one of the leading automation platforms in automating banking, insurance and financial services processes. To know more, request a demo.