Data Extraction in Lending: Enhancing Efficiency and Accuracy in Loan Processing

Lending is a data-intensive industry. Yet, extracting crucial information from the deluge of loan applications, income verification documents, and credit reports remains a major operational challenge. Manual processes in data extraction in lending introduce delays and errors, create significant compliance risks, and hinder the borrower experience.

A new wave of innovation is transforming the lending industry. Increasing adoption of automated data extraction, powered by artificial intelligence (AI) is removing the manual bottlenecks. Lending institutions are experiencing accelerated loan approvals, and improved accuracy, and are gaining a competitive edge.

In this blog, we’ll know the hidden costs of traditional data extraction methods and the transformative power of automation. We will also learn about how KlearStack’s solution can make your lending operations smooth, with a step-by-step data extraction guide.

Main Documents in the Lending Industry

There are various documents involved in lending to process a loan application. Loan application forms ask for various personal and financial information to verify the identity and credit worthiness of the loan applicant. These documents serve as the foundation for assessing risk, making informed decisions, and ensuring compliance. Specific data points from loan documents must be extracted for proper evaluation.

• Loan Applications: The starting point of any lending process, capturing essential borrower information such as personal details, employment history and financial information. Key fields to extract include the loan amount, credit history, personal details, loan repayment terms, employment status, income details, assets and debts.
  
  
• Income Verification Documents: Income verification documents verify whether the loan applicant can pay the monthly EMI or monthly payment obligations. Documents such as pay stubs, income proof, tax statements, bank statements, and other financial records provide evidence of a borrower’s income and ability to repay the loan.
  
  
• Credit Reports: Credit reports offer insight into the financial behavior of the loan applicant. A good credit score indicates that borrower is likely to repay the loan dues on time. Credit rating agencies such as CIBIL, CRISIL, Experian, etc generate credit score reports that help lending institutions to understand borrower’s credit history, including payment patterns, outstanding debts, and credit utilization.
  
  
• Property Appraisals: Property appraisal determines an unbiased estimate of a market value of a propertyfor purposes such as securing financing, insurance claims, tax assessments, and price negotiations. It is a crucial component when property serves as collateral.
  
  
• Business Financial Statements: For commercial lending, balance sheets, income statements, and cash flow statements provide a snapshot of a business’s financial health, aiding in lending decisions.

Key Data Fields extracted for Lending Institutions:

Automated data extraction of lending documents is powered by technologies like Optical Character Recognition (OCR), AI, ML, etc to accurately identify and capture relevant information from these documents. Key data fields typically extracted include:

• Borrower Information: Name, address, contact details, social security number, employment history, and income details.
  
• Loan Details: Loan amount, interest rate, term, repayment schedule, purpose of the loan, collateral information.
  
• Financial Data: Assets, liabilities, debt-to-income ratio, credit score, credit history, bank statements.
  
• Property Details: Property address, square footage, number of bedrooms and bathrooms, estimated value, property taxes.
  
• Business Information: Company name, address, industry, annual revenue, expenses, profit margins, tax returns.

Challenges and Solutions in Data Extraction in the Lending Industry

Data extraction in the lending industry presents a unique set of challenges that can significantly impact operational efficiency, risk management, and the borrower experience. These challenges, if left unaddressed, have a ripple effect on the entire lending process.

Challenges Faced while Extracting Data from Lending Documents

• Document Variety and Complexity: Lending documents come in various formats, from structured forms to unstructured documents like handwritten notes and scanned images. This variety makes it difficult to apply a one-size-fits-all approach to data extraction.
  
• Data Accuracy and Consistency: Manual data entry is prone to human error, leading to inconsistencies and inaccuracies in the extracted data. This impacts lending decisions, leads to compliance issues, and damages customer relationships.
  
• Time-Consuming Processes: Manually reviewing and extracting data from large volumes of documents is a time-consuming and labor-intensive process, creating bottlenecks and delaying loan approvals.
  
• Scalability Issues: As loan volumes increase, manual data extraction processes become unsustainable, leading to backlogs and delays.
  
• Regulatory Compliance: The lending industry is heavily regulated, and lenders must ensure that data extraction processes adhere to strict compliance requirements. Manual processes increase the risk of non-compliance.

Challenges Solved by Automated Data Extraction in Lending

There is an increasing shift towards automated data extraction, powered by artificial intelligence and other advanced technologies. These technologies offer a solution to the challenges faced and make the processes much more efficient. Here’s how:

• Handles Document Variety: AI-powered data extraction tools intelligently process a wide range of document formats, including structured, semi-structured, and unstructured data.
  
• Improves Accuracy and Consistency: Machine learning algorithms continuously learn and improve, reducing errors and ensuring greater consistency in data extraction.
  
• Accelerates Processing Times: Automation eliminates manual bottlenecks, enabling lenders to process documents faster and make quicker lending decisions.
  
• Achieves Scalability:  Automated systems easily handle increasing volumes of documents without compromising speed or accuracy.
  
• Supports Compliance: By automating data validation and verification processes, lenders reduce the risk of non-compliance and ensure data integrity.

Trends in Data Extraction for Lending

Data extraction is undergoing a rapid evolution, with the lending industry leading the charge. We are witnessing a clear shift away from manual, paper-based processes towards automated, data-driven solutions.

Global Adoption: A 2023 report by Grand View Research projects the global intelligent document processing (IDP) market, which encompasses automated data extraction, to reach $5.2 billion by 2030, growing at a CAGR of 31.5% from 2023 to 2030. This highlights the rapid adoption of these technologies across various industries, including lending.

Lending Trends in the US: Within the US lending sector, the trend is even more pronounced. A recent survey by McKinsey found that 60% of US banks are actively investing in AI and machine learning technologies, with data extraction and analysis being key focus areas. This reflects a growing recognition of the need to streamline operations, improve efficiency, and enhance the customer experience.

The AI Advantage: Artificial Intelligence is set to dramatically change data extraction in lending. Its ability to process vast amounts of information quickly and accurately is key. AI-powered solutions can extract data from even the most complex and unstructured documents, such as handwritten notes and scanned images. This opens up new possibilities for lenders to gain deeper insights into their customers, identify potential risks, and make more informed lending decisions.

Future of Data Extraction in Lending

As AI and other technologies continue to advance, we can anticipate even greater levels of automation and efficiency in data extraction. Lenders who adopt these innovations will be well-positioned to succeed in an increasingly competitive market.

Some of the key trends to watch for include:

• Greater emphasis on data security and privacy: With increasing concerns about data breaches and cyberattacks, lending institutions will prioritize data security and ensure that their data extraction processes are robust and compliant with relevant regulations. Look for solutions that offer advanced encryption, secure data storage, and role-based access controls to safeguard sensitive borrower information.
  
  
• Integration with other lending technologies: Data extraction will become increasingly integrated with other lending technologies, such as loan origination systems. This seamless integration will enable lending institutions to automate their entire lending workflow, from application submission to final approval, creating a frictionless experience.
  
  
• Advanced machine learning capabilities: The future of data extraction lies in the ability to not just extract data, but to truly understand it. Expect to see solutions that leverage advanced machine learning algorithms to identify patterns and extract insights.
  
  
• Increased adoption of cloud-based solutions: Cloud-based data extraction platforms offer flexibility, scalability, and cost-effectiveness, making them an attractive option for lenders of all sizes. Imagine accessing and processing loan documents from anywhere, at any time, with the assurance of enterprise-grade security.
  

KlearStack: Advanced Data Extraction Solution for Lending Institutions

KlearStack is at the forefront of data extraction innovation, delivering a future-proof solution that not only meets but exceeds the demands of today’s lending industry. Our platform combines the power of AI with a suite of advanced features, designed to tackle the challenges lenders face head-on.

1. Template-less Solution: KlearStack’s OCR technology extracts data accurately from any document layout, eliminating the need for constant model retraining and saving valuable time and resources.
   
   
2. Multi-lingual Support: With support for 50+ languages, KlearStack ensures language barriers don’t hinder your global operations.
   
   
3. Bulk Document Processing: Process large volumes of documents simultaneously, boosting efficiency and reducing processing times.
   
   
4. Line-item Data Extraction: Capture every critical detail from invoices and other documents, ensuring accuracy for financial analysis and inventory management.
   
   
5. Multi-page Data Extraction: Extract data seamlessly across multiple pages, ensuring no crucial information is missed.
   
   
6. Self-Learning Algorithm: KlearStack’s AI continuously learns and improves, enhancing accuracy over time and reducing the need for manual intervention.
   
   
7. Seamless Integration: Effortlessly integrate KlearStack with your existing ERP and accounting systems, eliminating manual data entry and boosting productivity.
   
   
8. Document Classification: Automatically categorize documents based on their content, streamlining workflows and improving organization.
   
   
9. Automated Document Splitting: Separate documents from attachments like invoices or receipts, enabling efficient data analysis.
   
   
10. Rich Document Audit Engine: Set rules to validate extracted data, flagging exceptions for review and ensuring accuracy.
    
    
11. Rules-based Workflows: Automate document routing based on specific criteria, eliminating manual intervention and accelerating processes.

8 Steps Guide to Extract Data from Lending Documents

KlearStack helps you extract data quickly and easily from lending documents. It saves thousands of hours and delivers output with up to 99% accuracy. Here is a step-by-step guide to extracting data using KlearStack:

Step 1: Register/login to the software

• Once you successfully register with KlearStack as a user, you will get access to the login credentials. Upon entering these, read the terms and conditions carefully, and tick the check box. After this, you can log in to the dashboard, where all the wonders of data extraction start!

Step 2: View the dashboard to upload the documents

• Once logged in, you will see the dashboard from where different documents can be uploaded. From here, you can add and process various documents, including bank statements, invoices, bills, purchase orders, receipts, and over 12 other document types.
• KlearStack also has an excellent feature that allows bulk processing of the documents, which means you can upload multiple documents and it will process all of those simultaneously giving you speedy and meticulous results.

Here we will use Bank Statements as an example of lending documents.

Step 3: Upload the Bank Statement

• Click on the ‘Add new’ tab. KlearStack allows you to upload documents in different formats such as Electronic PDF, Word, Excel, JPG, BMP, TIFF, PNG or Image, scanned PDF, and ZIP.

Step 4: Select the document type

• Here you can browse your document and upload from sources available.You also have an option to select if the document is for a B2B or B2C transaction. This ensures better categorization and storage of your data and streamlines your further process of data collection when it comes to final reporting.
• Click on Done to proceed.

Step 5: View the added document

• Your most recently uploaded document will appear on top. Uploaded documents with their extracted data appear here, providing a quick snapshot of all necessary information at any given time

Step 6: Click to check the extracted data

• For detailed information you can click on the uploaded document, you will see all the fields on one part of the screen and the uploaded document on the other. Here you can scroll and check all the extracted data.
• If you wish to understand where the information has been picked from, simply click on that particular field and it will get highlighted on the uploaded document. If the information is incorrect, you can edit it here. This will retrain the model for future bank statements. Once done, click on ‘Save’.

Step 7: Click on approve

• Once you’ve verified the details are correct, click on “Approve.” The models are trained to capture data quickly and accurately.

Step 8: View the document on the dashboard

• Once approved, go back to the dashboard and you will see your document there with the approval sign. Here you will be able to see all the documents and data extraction done from each.

KlearStack: Your Partner for a Data-Driven Lending Future

Manual data extraction is no longer a sustainable solution for lenders seeking to thrive in today’s competitive market. Automated data extraction, driven by AI, offers a clear path to improved efficiency, accuracy, and compliance. KlearStack, with its advanced features and commitment to innovation, is your partner in this transformation.

Stay ahead with the latest trends and techniques in data extraction. Book a DEMO Call now to troubleshoot your problems and increase efficiency by 500%, while saving 80% on document data entry and auditing costs.