The traditional commercial lending process is labor intensive work that involves manual data entry and carrying out tasks related to underwriting, application approvals, and post-loan processing standards. Commercial lenders depend on the creditworthiness of borrowers when lending money and hope to make a profit from investments, which means that they deal with a degree of unpredictability when it comes to losses. Financial institutions and NBFCs are always looking to diversify their investment portfolio, enhance customer experiences, and scale up by generating enough profits. They can meet these milestones by using Robotic Process Automation (RPA) for loan processing.
Steps involved in loan processing
Processing thousands of loan mortgage documents can be time-consuming, and without intelligent automation workflows, banks can have a tough time processing applications and ensuring data compliance and accuracy. That's why companies are investing in document processing automation tools to connect disparate systems, improve efficiency, and ensure smooth data flows throughout different parts of the organization.
The commercial loan process entails the following steps:
1. Customer management
Customer management includes the collection of customer data, analyzing their creditworthiness and reviewing their track record for making repayments in time. Submitting the loan file is a part of the pre-qualification process and borrowers have to submit a list of required documents to the bank, namely:
- Bank Statements
- ID and Address Proofs
- Salary slips
- Credit Score
- Current Employment Details
2. Credit report analysis
The loan officer asks for the credit report if it already hasn’t been submitted with the loan file document. Most credit reports are uploaded and stored electronically which means they pull the details from them through online databases. The lending worthiness of the borrower is evaluated and the amount of loan that can be approved for filing is decided based on that.
3. Credit presentation and decisioning
After collecting information about customers, doing ratio analysis, mining data, and determining their risk rating, bankers get an idea of what their loan risk appetite will look like. Automation tools can immensely help this process by collecting multiple documents, extracting data, performing integrations, and mapping out information that tabulate financial statements, tax forms, cash flows, balance sheets, and income documents.
4. Income verification
Lenders request for income verification in the form of W2 forms, letter of employment, and paystubs. Depending on the loan department’s policy, they may even phone up the employer and ask for details. Income verification for loan processing terms and conditions vary from lender to lender.
5. Appraisals and inspection
If you are applying for a mortgage loan, the property you are taking a loan for will get inspected. After verification of income sources is done, lenders will work on getting appraisals, proof of insurance, and inspect the items you’re taking a loan out for. There may be other procedures included with this process and the formalities will depend on your state or local laws.
6. Review, certification, and approval
After all the details have been reviewed and inspected and you’re good to go with the relevant documentation, the loan department will proceed with sanctioning the loan. Loan processing time period will depend on the type of loan you are applying for and its purpose. Individuals with a high credit score usually get their loans processed quickly at attractive interest rates.
How to automate loan processing
Lenders try to process thousands of applications on a day-to-day basis and are working on improving speed, accuracy, and reliability when it comes to faster loan processing. Machine learning solutions and automated data extraction platforms like Docsumo makes it easier for organizations to manage the loan application processing much more efficiently.
Here is how to automate loan processing with Docsumo.
1. Sales and marketing
AI and intelligent OCR solutions in Docsumo can help organizations in automatically reading data from customer applications. Neural nets use data parsing rules to determine what areas of documents to read and extract information from. The information extracted gets validated by APIs and processed for further review. The advantage of using automated data extraction with Docsumo is that you can train an API to recognize a single document type and upload multiple documents for automated data extraction and entry once it’s sufficiently trained. This can save you countless hours of time and streamline credit report analysis, letting you better understand risk profiles and decide which customers have the lowest default rates.
2. Loan verifications and approvals
The best part about using Docsumo for automated loan processing is document verification and validation. Errors get flagged by APIs and individuals are automatically sent alerts. This reduces the number of false-positive cases by ensuring data completion and accuracy. AI models can help with cash flow analysis, compare statistics, and update information over time. You can process a wide variety of documents in different formats and Docsumo has no limits when it comes to document storage.
3. Improved customer experience
One of the added advantages of using Docsumo is improved customer experience. Your users can view their applications online and get assured complete data privacy. The platform is GDPR compliant and SOC-2 Certified which means that all the data processed through Docsumo is secure. You can upload unstructured documents and let Docsumo organize information for clients by training API models. The biggest benefit is that your customers won’t have to wait long for their loan application approval and processing since document reviews are done fast.
Benefits of loan processing automation
Commercial loans differ by size and many lenders use paper-based document processing to sanction and approve loans. Using traditional methods of loan processing lead to slower decision making times, more paperwork, and time invested into manual data entry. For example, underwriting tasks are done these days by using spreadsheets to insert credit information. Data entered into spreadsheets may be prone to errors, redundancy, and typists may make mistakes by entering wrong details sometimes.
Manual paper-based underwriting workflows are also not reliable, lack accuracy, and take countless hours for processing. If applications are rejected or there are any discrepancies, re-entering of data is needed. All this can be solved by using automation software for loan processing.
An automated loan origination system lets borrowers and lenders store and share information electronically. Lenders can interact with customers online, process applications, and review details on-screen. The biggest benefit of automated loan processing is that risk assessment and analysis done on user profiles turn out to be better due to data accuracy and integrity.
Using Robotic Process Automation (RPA) and Artificial Intelligence (AI) for commercial loan processing can:
- Help verify details about third-party vendors
- Streamline business operational, managerial, and administrative workflows
- Process financial transactions faster by using rule-based approaches for structuring data
- Perform audit trails and ensure that data meets legal regulations and compliance
- Process documents from multiple sources and save it in various electronic formats such as PDF, JSON, XML, etc. These documents can be shared over email to clients or lending agencies for reviews and faster approvals
Are you ready to start automating your loan processing today? Schedule a free demo with Docsumo and experience hands-on how loan processing automation works.