Automate mortgage processing, underwriting, reconciliation & more with Nanonets.
schedule a demo Get Started
PDF → Excel
Convert PDF bank statements to Excel 

Loan origination is the process of applying for and obtaining a loan, including all the steps and activities that are involved in evaluating, approving, and disbursing the loan.

This process includes activities such as evaluating a borrower's creditworthiness, income, and other financial information; determining the loan amount, interest rate, and other loan terms; and preparing and submitting the loan application. It also includes various other steps such as underwriting, documentation, and funding.  The lender typically charges a loan origination fee, which is around 1% of the loan amount, to cover the cost of the work involved in the origination process.


Automate your mortgage processing, underwriting, fraud detection, bank reconciliations or accounting processes with a ready-to-use custom workflow.


The loan origination process

Loan origination is a 7 step process that every individual must go through to obtain a mortgage or home loan. The term also applies to other types of amortized personal loans.

Origination in finance is often a lengthy process and it's overseen by the Federal Deposit Insurance Corporation (FDIC) for compliance with Title XIV of the Dodd-Frank Wall Street Reform and Consumer Protection Act. The process of loan origination typically involves the following 7 stages:

Loan Origination
Loan Origination

Stage 1: Pre-qualification

The borrower provides the lender with information about their income, assets, and credit history. The borrower typically provides the lender with the following information during pre-qualification:

  • Income: The borrower's salary, wages, bonuses, and other forms of income.
  • Assets: Bank account balances, investments, and other assets.
  • Liabilities: Credit card balances, car loans, and other debts.
  • Credit history: Credit score and credit report

Based on this information, the lender will use their internal underwriting guidelines and loan program requirements to determine if the borrower is likely to qualify for a loan and what loan terms, including interest rate, they can offer the borrower. It's important to note that pre-qualification does not guarantee loan approval and the lender will have to verify all the information provided by the borrower before approving the loan. The lender uses this information to determine if the borrower is likely to qualify for a loan and to estimate the loan amount and interest rate.

Stage 2: Application

The borrower submits a loan application to the lender. The application process typically involves the following steps:

  • Application Form: The borrower completes a loan application form, which typically includes information such as the borrower's name, address, income, employment history, assets, liabilities, and credit history.
  • Supporting Documents: The borrower provides the lender with supporting documents such as pay stubs, W-2 forms, tax returns, bank statements, and proof of insurance. The lender may also require additional documentation depending on the type of loan and the borrower's credit history.
  • Credit Report: The lender orders a credit report to verify the borrower's credit score and credit history.

Stage 3: Processing

Processing refers to the administrative tasks involved in preparing a loan application for review by an underwriter. This includes collecting and verifying information about the borrower, such as their credit history, income, assets, and liabilities. It also includes preparing any necessary documentation, such as pay stubs, tax returns, and proof of insurance. The processor is responsible for ensuring that all of the required information and documentation is complete and accurate before the application is sent to the underwriter for review.

Stage 4: Underwriting

This step includes a review of the borrower's creditworthiness, income, assets, and liabilities, as well as an assessment of the collateral that will be used to secure the loan. The underwriter will also verify the information provided in the loan application and may request additional documentation or information as needed. The goal of underwriting is to determine the likelihood that the borrower will be able to repay the loan and to set terms and conditions for the loan that will mitigate the risk of default.

Stage 5: Approval

Approval refers to the decision made by the lender or financial institution to grant the loan to the borrower. If the loan is approved, the lender will provide the borrower with a loan estimate, which will outline the terms and conditions of the loan, including the interest rate, the monthly payments, and any fees or charges that will be associated with the loan.

Stage 6: Closing

This is the final step in the loan origination process. It is the point at which the borrower formally agrees to the terms of the loan and the lender disburses the funds. During the closing process, the borrower will review and sign all of the loan documents, including the promissory note, the mortgage or deed of trust, and any other required disclosures. The closing agent will also collect any closing costs or fees due at the closing time. Once all of the documents have been signed and the funds have been disbursed, the loan is considered closed, and the borrower can begin making the loan payments.

Stage 7: Servicing

The lender will service the loan, which includes collecting payments, managing escrow accounts, and enforcing the terms of the loan.


Automate your mortgage processing, underwriting, fraud detection, bank reconciliations or accounting processes with a ready-to-use custom workflow.


Loan Origination Automation

Manual and paper-based underwriting processes are often characterized by a lack of consistency, accountability and accuracy. They are also known for being time-consuming.

Loan Origination Automation
Loan Origination Automation

Automation can help to address these issues by streamlining disparate systems, providing reliable and consistent data throughout the loan origination process and speeding up the overall process. Automation in the loan origination process may be used at various stages such as collection and verification of borrower information, underwriting, approval and closing of the loan. It can be implemented in various forms, such as software programs, platforms or APIs that can be integrated with existing systems.

One of the most common forms of loan origination automation is the use of online applications and portals, where borrowers can apply for loans and submit documentation digitally. Another example is the use of automated underwriting systems, which can analyze borrower information and make loan decisions based on pre-set criteria. Some lenders are also using artificial intelligence and machine learning to improve the accuracy and efficiency of underwriting. One of the case studies of loan origination system is the use of a digital mortgage platform by Quicken Loans; they implemented an end-to-end digital mortgage process, which allows borrowers to apply, upload documentation and receive loan approval online. This has resulted in improved customer experience and reduced the time it takes to close a loan.

There are several benefits of loan origination automation, including:

  • Increased efficiency: Automated systems can quickly and accurately collect and verify borrower information, reducing the need for manual data entry and minimizing the risk of errors. They can also help to automate the underwriting process, allowing lenders to quickly evaluate loan applications and make decisions based on a variety of factors, such as creditworthiness, income, and collateral.
  • Improved accuracy: Loan origination systems in the banking sector can help reduce the risk of errors by providing more consistent and accurate data. Additionally, the use of artificial intelligence and machine learning can help to improve the accuracy of underwriting and other loan origination processes.
  • Reduced costs: Automation can help to reduce costs by eliminating the need for manual labor and reducing the need for paper-based documentation. This can help to increase the overall profitability of the lender.
  • Improved customer experience: Automation can help to improve the customer experience by making the loan origination process more efficient, streamlined, and convenient. For example, using a digital mortgage platform allows borrowers to apply, upload documentation and receive loan approval online.
  • Better compliance: Automated origination systems can help to ensure compliance with regulations by providing consistent and accurate data, and by automating the compliance checks.
  • Scalability: Automation allows lenders to handle a larger volume of loan applications, which can be useful for lenders with a high volume of loans or rapid growth.

Choosing a tool for loan origination automation

Choosing the appropriate technology for automating the loan origination process requires a very clear understanding of which areas of the process can be automated. While the entire process can and should be automated, implementing an end-to-end solution takes time. Technologies such as RPA, OCR, and AI can play a role in automating business processes, but determining which technology is best suited for a particular use case is crucial for a successful deployment

When choosing an automation tool for loan origination, there are several key factors to consider:

  • Functionality: The tool should have the capability to automate the specific tasks and processes that are part of your loan origination process. This includes things like application and document collection, underwriting, approval, and closing.
  • Integration: The tool should be able to integrate with your existing systems and workflows so that it can seamlessly fit into your current process.
  • Scalability: The tool should be able to handle the volume of loan applications your organization receives and be able to scale with your business.
  • Security: The tool should have robust security features to protect sensitive borrower information and comply with regulations and data privacy laws.
  • Reporting and analytics: The tool should provide detailed reporting and analytics capabilities to track performance, identify areas for improvement and measure results.
  • Cost: The tool should be cost-effective and provide a good return on investment.
  • Support: The tool should have a reliable and responsive support team that can assist with setup, implementation, and ongoing maintenance.
  • Compliance: The tool should be able to comply with regulations and industry standards.

Automate your mortgage processing, underwriting, fraud detection, bank reconciliations or accounting processes with a ready-to-use custom workflow.


Nanonets in the loan origination workflow

Nanonets can be a valuable tool in the loan underwriting process. The software uses OCR technology to automatically extract information from borrower documents, such as ID cards, income statements, and bank statements.  This can help to speed up the verification process and reduce the risk of errors. By automating the data entry process, the Nanonets software can also help to reduce the risk of human error and improve the consistency and accuracy of the data. With the ability to process large volumes of data quickly and accurately, Nanonets can help to make the loan underwriting process more efficient and effective.

Nanonets is an excellent choice for automatic data extraction from loan application packages because of its various features such as:

  • Range of data that can be extracted: Nanonets uses advanced OCR technology which enables it to automatically extract information from a variety of document types, including ID cards, income statements, and bank statements.
  • Customizable templates: Nanonets enables the creation of customizable templates that can be tailored to the specific data fields required for loan applications. This ensures that the software can extract the relevant information quickly and accurately.
  • Flexible data validation: Nanonets allows for flexible data validation, which can be configured to ensure that the extracted information meets specific criteria. This can include checks for compliance with regulations and industry standards.
  • Machine learning-based data extraction: Nanonets uses machine learning algorithms to extract data, this ensures that the software can learn and adapt to new document types and data fields over time, which improves its accuracy and performance.
  • Integration: Nanonets can be integrated with existing systems and workflows, which allows for seamless integration into the loan origination process.
  • Reporting and analytics: Nanonets provides detailed reporting and analytics capabilities which can be used to track performance, identify areas for improvement, and measure results.
  • Scalability: Nanonets can handle a large volume of loan applications and be able to scale with your business.
  • Security: Nanonets provides robust security features to protect sensitive borrower information and comply with regulations and data privacy laws.
  • Support: Nanonets has a reliable and responsive support team that can assist with implementation, customization, and ongoing maintenance, as well as troubleshooting and problem resolution. This ensures that lenders can rely on the software to perform consistently and effectively and that any issues can be quickly resolved.

Takeaway

The use of automation technology has greatly improved the efficiency of many industries worldwide. However, the process of originating small business and commercial loans has remained largely unchanged for decades. This is now beginning to change as more traditional lenders adopt automation methods in their loan origination processes. The reasons for this shift include competition from technology-enabled competitors, a desire for increased efficiency and productivity, a need to improve customer service, cost savings, and compliance with stricter regulatory standards. Many lenders are motivated to implement technological solutions to gain better control over their data and gain more accurate business insights.

The shift towards automation in the commercial lending landscape is not intended to replace human intelligence. The goal is to retain talent and enable bankers to focus on crucial tasks such as risk analysis and customer relationship management, as opposed to administrative tasks.