Modernizing the Lending Industry with Automated Document Processing

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Modernizing the Lending Industry with Automated Document Processing

The lending industry has predominantly been a paper-intensive business. Automated document processing brings transformational change to archaic paper processing techniques and helps lenders streamline their operations. The implementation of the software enhances the overall customer experience by accelerating the loan approval process. From the company’s perspective, it increases accuracy in highly critical tasks and processes that are especially sensitive to human errors, such as data verification, aggregation, and further processing. 

While accuracy, optimization, and increased ROI are the focus points of using automated document processing, the technology’s impact is much more far-reaching for lending businesses.

In this article, we take an in-depth look at the various nuances of implementing automated document processing software in the lending sector. 

So, let's jump right into it:-

Importance of document processing in lending 

Lenders and underwriters are constantly chasing higher loan approval rates, a lower cost of acquisition, and a shorter average sales cycle. In the pursuit of achieving these metrics, making better decisions, and offering personalized customer service, they have adopted technologies such as AI, data analytics, and automated document processing. 

In this article, we specifically cover automated document processing for lending. This technology helps approval officers automate repetitive tasks such as: 

  • Gathering personal information documents 
  • Filling numerous applications
  • Constantly communicating with customers 
  • Reviewing documents for errors 
  • Further processing the documents after data extraction 
  • Scanning documents for errors 

More importantly, intelligent document processing (IDP) offers customized solutions for different financial institutions depending on their existing workflows. Therefore, lending institutions can easily adopt the functionalities of automated document processing software and impart training to increase the software adoption rate amongst employees. 

Benefits of automated document processing in lending 

Before getting into use-cases and benefits of automated document processing for the lending process, let’s go through the overarching benefits of implementing automated document processing:-

Intelligent document processing in Lending - Infographic

1. Improved efficiency by reducing document processing time to 30-60 seconds 

Processing documents faster allows the loan officer to get faster loan approvals. In other words, the customers do not have to wait for days before hearing back about their loan applications, thus enhancing the overall customer experience. 

Lending companies also avoid paperwork bottlenecks and improve the overall productivity of their employees. The employees get to invest their time to make better strategic lending decisions. 

2. Increase accuracy to more than 99%

Document verification is one of the more important steps in the lending process. In the past, dedicated employees would manually go through each personal document to double-check the customer’s application information. Needless to say, this process is incredibly inefficient. 

Automated data extraction is more than 99% accurate. This means the extracted data can be directly compared to the customer’s available personal information to verify its authenticity. It reduces manual labor and saves the company valuable resources. 

3. Fine-grade security  

Equipped with advanced automation technologies implemented by lenders, customers can view the status of their online application without worrying about data leakage. 

Ideally, look for an automated document processing system that is SOC-2 certified and GDPR compliant so as to ensure fine-grade security for users and their sensitive data. 

4. Reduce operational cost by 67-70%

The reduction in document processing time and lower error rates help the company decrease its operational costs by 67-70%. The company’s ROI increases, and the extra resources can be reinvested to improve other facilities. 

Use cases of automated document processing in lending

The most important feature of automated document processing in lending is its unmatched archiving function. After the data extraction and data classification processes, the document is permanently stored on the bank's servers. The loan officers and bank branch managers can easily retrieve and refer to these documents during the loan approval process. 

Let’s dive deeper into the various use cases:- 

1. Efficient document classification

Document Classification

Lenders use automated and cloud-based document processing systems to significantly improve the loan document management system. The platform uses machine learning algorithms to identify and classify documents into various categories, depending on the requirements of the financial institution. 

For example, most banks require customers’ personal documents, like salary slips, bank statements, existing insurance policies, and tax returns, before checking their eligibility for a loan. The document AI software automatically categorizes them into respective folders for easier tracking. 

Enhanced document classification reduces the effort required to find relevant documents. Apart from that, being cloud-based, the platform ensures that no important document is lost or misclassified. 

2. Intelligent document processing for data extraction

Intelligent document processing for data extraction

Intelligent document processing (IPD) helps with faster data extraction. IDP software uses intelligent character recognition (ICR) and optical character recognition (OCR) systems to scan and extract relevant information from documents. 

The software ingests documents and reads information from structured, semi-structured, and unstructured document types. To add to the ease of convenience, advanced IDP platforms allow the lender to accept almost all document types, like PDG, JPG, and even scanned documents, while collecting information from the customers. 

3. Automated verification of documents and customer information 

Document verificaton

Advanced AI helps with the verification process. The platform checks the document’s authenticity and validates customer information in real-time. 

The process includes confirming the customer's identities using government-issued IDs, verifying employment details using pay slips, and verifying loan repayment eligibility using bank statements. 

Lenders use AI’s verification prowess to detect potential fraud and reduce the risk of omitting crucial information during the verification process. Altogether, AI and automation ensure that lenders have reliable and trustworthy information before approving loans to customers. 

4. Setting role-based access for faster authorization 

Authorization of loan documents

Getting a loan approved is no easy task. After the loan officers do their due diligence, the case is passed onto bank managers and credit analysts for approval. Normally, the process is time-consuming and relies on timely responses from people in the upper hierarchy. The approved papers are again sent to the loan officer to perform the final checks. 

Automated document AI system eradicates the manual re-routing process in loan origination systems by introducing a role-based hierarchy. 

The software automatically routes the loan application to the relevant personnel, depending on their role and authorization level. And, since all the details are already verified, it only takes a few minutes for the managers to review and approve the loan application. 

Implementation of automated document processing in lending 

The implementation of an automated document processing system will vary depending on the company’s requirements. However, the challenges faced by them and the best practices to follow for faster implementation remain the same. 

Best practices to follow for faster implementation

Here are the implementation best practices worth considering: 

  • Outline the goals to achieve with automated document processing software
  • Identify the most common document types processed by the organization
  • Establish data extraction rules or, use pre-trained APIs for data extraction. 
  • Check the IDP software’s compatibility with your existing ERP and other business sources. 
  • Set up a role-based hierarchy.
  • Regularly test and optimize the software to ensure its longevity.

Challenges faced during the installation process

Third-party integrations

If the software is not compatible with existing business workflows, it becomes a challenge for lending organizations as they have interconnected and dependent business systems and workflows.


Ensure that the software has no server downtimes with a sustainable data center, as network connectivity issues not only delay the loan approval process but also make the organization vulnerable to cyberattacks. 

Low user adoption

Educate employees about the benefits of automation and train them to use the platform to gain the maximum ROI. Inadequate training or complex user interface lead to low user adoption. 

Optimize the IDP software implementation process with data analytics 

The implementation process can be further optimized by using insight obtained from the organization’s data analytics team. By analyzing the data available in the system, the lending financial institution can identify hurdles in the workflow and areas for improvement. 

Impact of automated document processing on lending 

In the traditional loan origination process, the borrowers have to jump through multiple regulatory hoops and furnish various documents, like credit scores, address proofs, bank statements, and salary slips. 

On the other end, the loan officials go through a similar ordeal while extracting the relevant information from these documents and securely storing them. Automation, on the other hand, streamlines this process. Here’s how. 

1. Replacing traditional document processing models 

Adding AI-based automation to document processing leads to improved efficiency and faster turnaround times for loan approvals. In addition, AI can keep processing documents and information 24/7 without fatigue, unlike its human counterpart. 

2. New opportunities for innovation and growth 

Automating the most critical aspects of document processing frees up employees, especially loan officers, to focus on more important tasks. These officers can now focus on more high-value tasks, such as customer service, and risk management. 

Increased attention to innovation paves the way for the development of new lending financial instruments and the introduction of an improved risk assessment model. 

3. Potential for greater financial inclusion for customers 

Faster loan approval times help lenders expand their customer base. In doing so, they start offering loans to a previously underserved population. Improved data extraction accuracy helps the data analytics team make consistent credit decisions, eventually leading to the establishment of fairer lending practices. 

It empowers lenders to introduce more flexible plans, like micro-loans and pay-as-you-go plans, that are more suitable for low-income households. Access to affordable credit increases financial inclusion and the customer base. 


One of the most widely adopted use cases of the automated document processing platform Docsumo is in the lending industry. 

A case in point is National Debt Relief, an American debt relief company. 

Like any other legacy financial institution, National Debt Relief also faced challenges that come naturally in paperwork-intensive industries. 

  • They had to manually scan debt settlement letters.
  • Lacked any kind of data validation and verification during the capture process.
  • Double manual entry wasted valuable resources. 
  • The team had to go through 350,000 letters every year, drastically increasing the chances of error due to fatigue. 
  • Varying vendor formats added to the challenges of the accounts payable team.

Here’s how Docsumo simplified document processing for the lending company: 

  • Docsumo’s pre-trained algorithms auto-classify letters. 
  • The extracted data was instantly validated using custom rules in real-time.
  • Implementation of IDP software meant employees only had to review the exceptions. 
  • All letters were digitized and stored in the cloud with enterprise-grade encryption. 

National Debt Relief, now powered by Docsumo, has served over 450,000 customers and settled over $10 billion in debt.

If you want similar automated document processing solutions for your paperwork-ridden organization, try Docsumo’s 14-day free trial. 

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Pankaj Tripathi
Written by
Pankaj Tripathi

Helping enterprises capture data for analytics and decisioning

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