With the help of Artificial Intelligence, Machine Learning Algorithms, and other related technologies, an automated underwriting software helps lenders in making underwriting decisions with quicker turn-around time, improved accuracy, and minimal human intervention. Compared to manual underwriting, it is faster, more accurate, and reliable. The automated underwriting system streamlines the entire loan approval workflow from automating data extraction from different underwriting documents to matching the extracted data against third-party data from banks, creditors, lenders, and other financial institutions to give an analysis report.
What is automated underwriting software? How does it work? How should you go about choosing one for your business? - All your questions answered in this article.
Let’s jump right into it:-
Loan Underwriting refers to the process of analyzing the quality of a loan application, and deciding whether to extend a loan or not. It's more complicated than simply looking at the credit score/credit history of a borrower, and requires evaluation of dozens of different variables in a credit report and deciding the likelihood of repaying a loan.
There are several approaches to automated underwriting, but it boils down to one common denominator: borrower information analysis. The same information is used in each course; it's just analyzed differently.
The automated underwriting software helps loan officers come up with a score based on the data available in the applicant's credit report, income, and assets. The software consists of two modules:-
i) A loan pre-qualification engine that provides an early estimation of the borrower's creditworthiness
ii) A secondary assessment tool used to verify information submitted by the borrower in their initial mortgage application.
The secondary assessment tool produces risk scores used to determine whether or not a potential borrower would be approved for a given loan amount based on their creditworthiness and debt-to-income ratios. The results are then sent back to the lender from a secure database, after which an underwriter can manually review any questionable aspects of the borrower's initial documentation.
Here is a brief look at the main types of automated underwriting and how they work:-
This type of software is used to determine rates for insurance plans. It uses various data points to rank customers based on their likelihood of claims. Propensity score statistics include age, gender, driving record, occupation and marital status. The model then calculates the probability of a loss over a certain period. The more likely the event, the higher the premium charged.
This type is used to determine the amount of money an insurance company makes in profit after paying out its client's bills. It determines what premiums are needed to pay expenses while also keeping costs down by using cheaper methods to bill customers or not paying out claims as often.
This type is used to assign a risk level to customers based on factors such as age, gender and driving history. The risk level helps determine which products a customer would be offered, how much they would pay for coverage, and what kind of discounts they might qualify for.
The process begins with the data entry, where all the information is entered into an automated data entry system. This includes data like credit scores, debt ratios, and income, although some lenders may use manual methods instead of an automated system for this step.
After this comes validation and tracking, where the auto-underwriter determines whether the data is valid, and matches up with other already existing information about the borrower.
The final phase determines any errors or inconsistencies in the entered information; this also does a last check to ensure that all required documents have been submitted. If these three phases pass, then the loan gets sent to an underwriter.
The software looks at the information on a loan application and makes a decision, usually within minutes. Then it sends the results directly to the lending officer for review.
In general, there are two different types of underwriting software:
Pre-application credit underwriting happens before the applicant submits any formal application for a loan or credit. Pre-application software is designed to help lenders screen out people who are likely to be high-risk borrowers so that they can focus their efforts on those people who are most likely to repay their loans.
Post application credit underwriting takes place after a borrower has already applied for a loan or line of credit and has either been approved or denied.
Steps taken include:
1) Verifying information from the borrower's credit report
2) Determining soft credit data such as employment status, income and length at current job
3) Applying risk factors that may increase or decrease the interest rate based on the applicant's score
4) Calculating the overall debt-to-income ratio
5) Generating a preliminary approval or denial decision
6) Running the data through a fraud detection system (FDS) to check for inconsistencies and missing or inaccurate data
The whole process can be described to have two stages:-
Check the applicant's income information, employment history, and assets (such as the value of the home). Applicants are most likely to be asked about student loans or other debts. Most financial institutions ask the borrower to provide proof of income and date of birth, along with other documents.
Once the initial screening process is concluded, underwriters need to determine whether the borrower has a good enough chance at making their loan payments to make the loan worthwhile for lenders. At this stage, underwriters look at the terms of the loan or credit card debt in detail to understand if the applicant can afford the loan at all. If not, the bank may deny the loan altogether.
The following list includes the documents commonly required for a loan application:-
Manual underwriting is the process of evaluating a loan application based on the applicant’s financial history and credit score manually. It can be something as simple as asking whether the applicant has ever been charged with a crime or filed for bankruptcy.
There are plenty of things that can cause the application to fall through the cracks. For example, some companies have an employment background check requirement, which disqualifies people who've been fired for cause or resigned after being accused of stealing. And some banks are strict about verifying income levels. If the income doesn't line up with what's reported in the application, it's likely not going to make it through the manual underwriting process.
Conventional underwriting rules are designed to ensure the safety of the loan. However, they may not always be suitable for every borrower. Banks can adopt more flexible underwriting rules to avoid missing out on a potentially good borrower. On the other hand, manual processing of loan applications is not only time-consuming, but it comes with unwanted human errors.
Here are some of the benefits that automated underwriting offers:
Docsumo provides an intelligent document processing solution that offers automated data extraction loan origination documents in real-time. The software comes with pre-trained APIs for documents such as:-
The extracted data is validated against in-document data and database using Excel-like validation rules.
More reasons to choose Docsumo:-
In today’s dynamic business world, filing and archiving official documents in the digital form makes it handy, and works wonders in the future or in unforeseen circumstances.
An automated invoice processing solution helps businesses streamline their accounts payable operations by automating tasks ranging from data extraction from invoices to data validation, and entering data into a database for further analysis and processing. Processing invoices may be one of the most time consuming tasks, but it can’t be ignored as it is directly linked to the finances of the business. Automation solves this problem by improving turnaround times for invoice processing, and improving the quality of data.
Automated document processing involves capturing components present on a document with the help of softwares. It utilizes technologies like Machine Learning, Computer Vision, Natural Language Processing, and OCR. Automatic processing of documents in an organization helps reduce manual labor, compliance requirements, eliminate challenges, and offers speed to the workflow environment. In this article, we cover different techniques used for document processing along with their pros and cons. This comparison will help you choose the best automated document processing software for your organization.
Accounts Payable (AP) is a current liability representing money owed to customers. Analysing the AP turnover (how long does the organisation take to pay the creditors) regularly can help organisations meet deadlines and avoid delinquencies. Accounts Payable influences a company's financial performance, credit conditions, and capacity to recruit investors and provides essential information about its general financial health. When deciding whether to invest or lend money, investors and lenders use these measurements to evaluate a company's solvency and management consulting procedures. In this article, we discuss how to calculate accounts payable, what to interpret and conclude from it, and the limits it has.