A Day in the Life of a Loan Underwriter

Last month, I was on a short trip to my native place. I had to meet quite a few people, but I had time restrictions. So, I decided to meet one of my closest friends, Ben, at his workplace. Ben is a loan underwriter. I reached his office before his work timings, but I could see a long queue of customers waiting for him to verify their applications.

I noticed the way he works. As he came in, we just exchanged smiles and he started his day—thanks to the long queue. He was manually going through each application and the supporting documents. He was simultaneously verifying applicants’ identity, address, employment proof, salary proof, and other related documents. It was as tiring as it sounds. That’s a whole lot of documents to be checked manually and repeatedly.

I wanted to take him out for lunch, his schedule didn’t allow him to take a break. He stressfully said, too much work! When I asked him about work, he laughed and said, it’s not over yet. Now, the bank’s personnel will go to each address to verify the identity and residence proof.

No wonder the loan approval takes approx. 20-30 days and sometimes even more than that.

Just imagine if an application with a huge loan amount turns into a bad loan. Simple – nightmares for Ben!

On my way back, I kept thinking about Ben and the way he operated. In today’s digital world, everyone looks for comfort and wants everything at the tap of a finger. Quickly I understood something that Ben’s bank didn’t realize. I immediately rang Ben and warned him of losing his customers. Reason – his customers will switch to intelligent lending. Appalled at my warning, he was quiet for the next five minutes.

I told him in today’s competitive world, you need not work hard; instead, work smart. Today technologies like artificial intelligence and machine learning (AI/ML) can help you simplify the complex lending process. These technologies will not only help you increase operational efficiencies and mitigate risks but enable you to deliver a personalized and frictionless customer experience.

The immediate takeaway for Ben – It was his time to act before it is too late. He must leverage intelligent lending solutions.

Hello readers,

Does this sound familiar to you? Are you Ben? Do you want to know more about intelligent lending? How do these technologies work? Let’s dig in deeper…

Derive Actionable Insights

AI/ML can derive relevant and actionable insights and patterns from raw data analysis. It can track customers’ behavior based on their search history and digital footprints. These data points and credit scores are fed into an analytic platform from which the lender, like you, can determine an applicant’s creditworthiness.

Mimic Human Intelligence

AI/ML works together to mimic human intelligence and simulate a conversation in natural language through messaging applications, websites, or mobile apps. AI-powered software applications like voice AI and chatbots can provide a contextual response to customers based on information from customer accounts, demographics, social media interactions, and past customer interactions.

Quick and Accurate Decision making

AI/ML can quickly analyze large data sets and provide critical insights about the applicant/existing customer, helping you make unbiased and accurate credit decisions in less time.

First, let’s look at Your Stumbling Blocks

Fewer Opportunities

Despite the digital push and exponential growth in financial inclusion in recent years, much of the population remains underbanked or unbanked. Their applications get rejected due to a lack of credit history, bank records, and security.

Bias Credit Decisioning

Human beings are biased to a certain extent, irrespective of their best efforts. These biases are inherent to us because of the ecosystem we grew up in and often lead to biased credit decisions.

Lack of Scalability

Legacy architectures and systems often struggle to manage the increasing flow of loan applications.

Scaling operations are expensive for traditional and new players in the lending industry without using state-of-the-art technologies.

The Potential Benefits Of Artificial Intelligence are Huge

High Scalability

“Low-ticket, high-volume” lending is typically a “lower risk, higher-income” business that every financial firm wants to enter.

But assessing risk at the individual level becomes a challenge when done manually. Eligibility or risk exposure is calculated based on parameters such as the customer’s monthly disposable income, collateral valuation, transaction history, income tax history, customer behavior, and future inflation.

Besides, the process becomes complicated for first-time applicants with no credit score. AI/ML can simplify this complex process by integrating with third-party applications and systems, tracking prospects’ online activities, and using it to determine their creditworthiness. It makes the decision making process faster, more accurate, and at scale.

Minimized Operation Costs

AI/ML can significantly reduce operational costs by automating several manuals and redundant processes using intelligence, reducing human errors, and implementing AI-powered chatbots. This frees your white-collar employees from standard and routine activities and reallocates them to complex applications requiring human experience and expertise.

Predictive analysis can monitor suspicious transactions and trigger response protocols. It can detect AML, BSA, KYC frauds, duplicate applications, or blocked customers, thereby saving lenders from losses.    Modern customers expect banks to provide 24×7 customer service, which can consume a big chunk of the bank’s budget. AI-powered self-help, voice AI, and chatbots can provide quick and ideal solutions to frequent problems, thereby helping banks to save millions of dollars.

Unbiased Credit-decisioning

Credit decisions are very critical, as many dreams are built on this!

The decision can often be suboptimal, as the underwriter cannot imagine all possible scenarios. Knowingly-unknowingly, the decision can also be biased and can vary from person to person. AI/ML-powered lending solution helps underwriters generate prompt credit decisions for corporate clients, mini, small, and medium-sized enterprises, retailers, or customers looking for personal loans. It helps make unbiased decisions and offers optimal loan amounts with risk-based pricing to the right customers.

More Benefits With Predictions and Collections

Once the loan is approved, AI/ML helps you predict the customers likely to pre-pay the loan and identify the defaulters. Accordingly, you can align your marketing executives with upselling/cross-selling other personalized products. AI can review customers’ financial health based on credit rating and past payment history, allowing banks to engage, communicate, and work toward loan restructuring to reduce defaults.

Besides, scores can help you predict yearly collection and losses accurately. You can also plan your budget and make strategies to maximize recoveries and reduce costs.

Time to Embrace AI/ML

 According to RESEARCH AND MARKETS, The global digital lending platform market size is expected to reach USD 26.08 billion by 2028, registering a CAGR of 24.0% from 2021 to 2028.

The time is now for lenders to embrace AI and ML to cost-effectively extend their financial lending services to the masses. The faster these technologies are adopted, the better the chances of grabbing a larger pie of the market and increasing customer longevity.

Newgen’s intelligent lending solution, built on a low-code digital transformation platform, enables your financial institutions to provide a digital experience utilizing intelligent underwriting, intelligent decisioning, and straight-through loan disbursement for all products, including credit cards and personal loans. Click on the link to learn more about Newgen AI Cloud.