How Lenders are speeding Up Loan Approvals using Smarter Data Extraction

Getting a loan approval is always a tedious task, requiring multiple forms, approvals, verification, and huge paperwork. However, data extraction has made the process simple and seamless. It is now easier to capture information and process it faster & accurately. With the advent of technology, every sector is reaping the benefits, and so is banking.

Nowadays lenders are adopting smarter data extraction tools to cut delays, reduce human error, and increase customer satisfaction & retention.  Let’s understand the tools used for Data Extraction!

1. OCR (Optical Character Recognition)
2. Text from photos or scanned documents can be converted into machine-readable text using OCR technology. It helps in automating the digitization process of data extraction, thereby reducing the time taken by any lending institution to process a loan application. Hence, OCR data extraction from documents like bank statements, loan applications, credit reports, & photo identity saving on resources.

Did you know? A fintech company in the USA used OCR to reduce document review time from 3 days to a few hours.

• DMS (Document Management System)
• A tool used to store and manage documents digitally. It has a plethora of features, including document scanning, indexing, workflow automation, etc, that help in streamlining the process of document processing and extracting data. Lending institutions can also retrieve and locate loan-related documents easily.

Did you know? Many Banks in India digitized the customer KYC form and reduced storage costs by 40%

• AI (Artificial Intelligence)
• AI serves as a powerful tool to reorganize and restructure the unorganized data, especially in the data extraction process.  With the help of AI, only the most relevant data can be extracted from the documents, thereby allowing a seamless loan application process.  AI also plays a crucial role in fraud detection, finding the authenticity of documents submitted, and analyzing past transactions.

Did you know? National Debt Relief achieved 99% accuracy in Document Processing using AI-powered Data Extraction

• APIs for the Classification of Documents
• Processes such as risk assessment, compliance, loan approval, or customer onboarding can be automated and streamlined with the help of the Document classification API. The process is simple; they identify documents, auto-categorize as per type, mark missing pages with errors, and much more. Thus, it helps not only to streamline the process but also to save time and energy with automation.

Did you know? API helps in fetching real-time bank documents and credit scores, eliminating manual uploads by customers.

• Machine Learning
• The most crucial part of the lending process is predicting and analyzing credit creditworthiness of the loan applicants. Relevant data from the history and customer profiles can help Institutions to create a predictive analysis solution that helps in managing risk associated with the loan. Thus, ML facilitates predictions based on past data.

Did you know? With ML, you can approve a loan in minutes, reduce delay, and increase loan volumes.

• RPA (Robotic Process Automation)
•  RPA uses bots to take care of routine, rule-based tasks that work across various software applications.  It can help institutions to extract data from both internal and external sources. Let’s take an example: if an applicant fails to submit a credit report, the system can log in to a credit rating website and fetch a report to add to the application. Hence, RPA reduces manual efforts and speeds up the loan application process.

Did you know? A USA Bank uses RPA to auto-find missing credit reports, cutting approval time by 74%

Frequently Asked Questions

1. Name some technologies used in Smarter Data Extraction?
2. OCR, AI, API, RPA & Machine Learning are widely used for data extraction and streamlining the loan approval process.

• Is data extraction secure?
• Yes, data extraction tools are secure and comply with all the security standards required to protect the sensitive financial information of the customers.

• Do loan Applicants benefit from Automation?
• Yes, Automation speeds up approvals, reduces errors, and provides a transparent, hassle-free process.

Conclusion

Automated Data extraction helps institutions improve their operational efficiency and provides a competitive edge in the market. It helps to capture data from documents, manage risk via customer profiling, and analyze past data. Faster loan approvals benefit both lenders and loan applicants. Institutions can save on resources, and customers can enjoy a hassle-free experience. Smarter data extraction has ensured higher accuracy by reducing human errors and maintaining transparency and consistency in the process.