With automated underwriting software, data from various underwriting papers can be compared to third-party data from banks, Cbanks, suppliers, funders, and other investment firms to generate an analysis report.
We are still using manual underwriting methods. No wonder, many are not aware of the advantages of automated underwriting systems.
Advantages Of Automated Underwriting System
1. Takes Wiser Decisions
There can be millions of dollars worth of loans that do not pay back because algorithms don’t make mistakes. No matter how skilled an individual is, they will eventually have a bad day. Thanks to loan origination software, machine learning and more data on loans, automated systems are getting better at figuring out which loans will do better.
2. Exhibits Increased Productivity
The lender and borrower both save time when using an automated underwriting system since decisions are made faster and fewer steps are required than with manual underwriting. With automated underwriting, the borrower gets what they want—faster processing—without compromising the loan’s integrity or putting the lender’s balance sheet at risk.
3. Agile Fraud Detection
In today’s loan industry, it is easy to commit fraud. Only credit card fraud is worth billions each year. Automation in routine processes greatly reduces fraud risk. By employing robust predictive analytics, the automated system can accurately assess the risks associated with extending credit to a particular customer. It is possible to detect fraud using these techniques by issuing alerts at the first hint of suspicion.
4. Greater Consistency
Automating the review, approval, and documentation of credit allows the bank to meet its standards in a more personalized manner. It makes up for the fact that the bank agent doesn’t understand bank policies, which can be different for each employee. Automated underwriting also takes into account all loan risk factors associated with important lending regulations. This is something humans might miss when underwriting a loan.
5. Resource Management in Underwriting
Let’s say a lender uses its automated underwriting system for very straightforward problems. By eliminating the need for human underwriters on a large number of policies, the lender can use its underwriters more efficiently on higher-value, more complicated situations. By automating the process, the lender can use its resources more efficiently.
6. Reduced Paper Process
By switching to an automated data-driven method of getting information from paper applications, lenders can save time and reduce the cost of imaging, the number of manual handoffs, and the number of human failure points. In an e-application connected to an underwriting rules engine, questions cannot be left blank.
Getting rid of paper saves the underwriter money on filing, human rework, and storage.
7. Scalability
The traditional underwriting process is hard to scale because you have to understand a lot about the lending business in order to classify, analyze, stack, and extract different documents. A professional team of analysts may be necessary, but they are very expensive. Automated underwriting can solve this problem.
The analysts will be able to focus on improving the system rather than going through every event in the underwriting process.
Conclusion
Automation in credit underwriting has enabled more accurate and efficient decision-making when determining a person’s creditworthiness. Reliable algorithms now manage labor-intensive pattern recognition and repetitive tasks, which, in turn, has disrupted the traditional lending industry. Automated underwriting has brought innovation to both loan startups and traditional banks alike – enabling much needed access to money for businesses as well as individuals.
