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Customer experience is everything. Get it right for your lending process using AI

Author | Raabiya Singh

One thing every industry will agree on today is - customer experience is everything. With companies like Netflix and Amazon driving customer expectations higher using Artificial intelligence (AI) and machine learning, it is time for the credit and banking industry to integrate AI into their processes for a smarter and seamless lending experience.

Wesley Hawk, VP Finance & Credit Operations, The Fundworks LLC, believes that gone are the days of banking employees working from 10 to 4 with the three-martini lunches in between. Instead, today, customers expect to get their fund requests approved in just a click, and that too on the same day – all this while they are enjoying a quiet dinner with their families at home, outside business hours.

This transition in expectations has been shaped by their everyday experience of brands and companies anticipating their needs and wants at the drop of a hat. You've logged on to Amazon and are looking for products to help spruce up your garden. Along with the lawnmower you searched for, recommendations also pop up for other garden tools you may need. You add a couple of them to your cart along with the lawnmower and pay for the purchase; You are now equipped to tend to your garden when the only contribution from your end has been typing in the two words – "lawnmower."

Customers like the convenience of companies anticipating their needs before they even voice it themselves. They are used to things coming to them when they need them instead of thinking about when they might need this later. There is also no denying that the COVID-19 pandemic has fast-tracked this need to be digital, personalized, and instant.

"They expect things to be intuitive. You can't have long, multi-page applications… If people provide their tax ID, they expect you to know who they are and their business to pre-fill," added Wesley.

Bradford Primavera, Chief Product Officer, Rocket Financial, seconds this thought.

"They want it where they need it, and they want it fast," says Bradford. His company, Rocket Financials, uses aggregated data and actual transactional information over the months to better understand somebody's financial situation and reality to make quicker informed decisions regarding the same. They also spend a reasonable amount of money on UX and UI, ensuring that it caters to their users and their business clients.

While leading institutions in the lending space have been spearheading the use of AI, the smaller organizations, too, need to take their game up a notch to stay relevant. Brian Caird, Senior Underwriter, Northern Credit Union, believes that having the technology available to streamline and make their jobs more efficient is critical for their success in this industry. "If it takes us two or three days to get that approval out the door and money in that borrower's hand, that does us no good," added Brian.

To remain competitive, financial institutions, big or small, today need to leverage the power of AI to create a great customer and member experience. After all, while your customers might use your technology only once a couple of years, your employees are the ones dealing with it daily. For those wondering if there is a bigger priority between the two, our experts believe that both the employees and customers deserve equal importance when discussing AI integrations.

According to Seth Pfendler, Consumer Underwriter, Northern Credit Union, incorporating AI in your underwriting process frees up time for the employees to focus on more complicated lending decisions that require additional information and manual oversight. When you have cases where you are on the fence, AI provides you with more data points that give lenders the confidence they need to say yes or no. Automation of credit decisions gives the traditional underwriting operations a much-needed leg up. It also helps mitigate risk from lending to young first-time borrowers. By evaluating linear and interactive patterns, AI offers optimized and informed results.

For decades, credit scores were the prime source of approving various products, such as mortgages and auto loans. Unfortunately, this approach was based on a limited set of historical data, limiting the number of consumers eligible for credit, and reducing a credit union's lending opportunities. Seth believes that credit scores are not black and white, and his company prides itself on exploring the grey areas. They like to look at the human element, and AI helps them get to know their customer better, so they can tailor a solution for them that will work not only for their borrowers but also for the company in the long term.

With AI-powered models, credit unions can craft a seamless and intelligent customer experience that exceeds expectations in today's competitive market. From providing customers and members with the right credit products to building stronger relationships with their borrowers for capturing a greater share of their wallets, AI can be a game-changer for the credit industry.

By adopting an AI-first approach, lenders today can design highly personalized journeys and create value for their customers through a holistic and data-driven approach. According to Eric Steinhoff, Client Impact, Scienaptic AI, the beauty of AI and machine learning models is that things can be fine-tuned almost instantly with the help of the latest data and feedback. This unlocks better efficiency and boosts customer engagement.

At, we know that the prevailing credit administration is handicapped by old credit underwriting technology. As a result, banks experience high credit loss rates while customers get poor experiences, and we are on a mission to change that! With over 70 clients, Scienaptic's AI is powering 7 million annual credit decisions. Credit unions using Scienaptic's AI see 40% more approvals and massive lifts in instant decisioning rates. While Scienaptic AI's system can help boost the number of loan approvals without increasing risk, it can also catch riskier loans that may have otherwise been approved.

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