Artificial intelligence (AI) is rapidly becoming more prevalent in today's society, reaching into industries that many investors never would have thought. Deere & Company, for example, is bringing artificial intelligence and machine learning to tractors with a fully autonomous tractor that can plow, harvest, and plant crops without a driver. With Deere, among other companies, it is clear that artificial intelligence is making its way into nearly every part of our world, and there are three companies you can invest in today that I think could be the best companies to capitalize on it. Upstart Holdings (NASDAQ:UPST) is bringing AI to a very old market: loan determinations. For decades, Fair Isaac has ruled the loan determination space with its FICO score, but it is a flawed system.
Humans invented artificial intelligence, so it is an unfortunate reality that human biases can be baked into AI. Businesses that use AI, however, do not need to replicate these historical mistakes. Today, we can deploy and scale carefully designed AI across organizations to root out bias rather than reinforce it. This shift is happening now in consumer lending, an industry with a history of using biased systems and processes to write loans. For years, creditors have used models that misrepresent the creditworthiness of women and minorities with discriminatory credit-scoring systems and other practices. Until recently, for example, consistently paying rent did not help on mortgage applications, an exclusion that especially disadvantaged people of color.
Today, Daily AI, the provider of intelligent solutions for the future of mortgage lending, announced that it has acquired Whiteboard CRM. Whiteboard provides a mortgage CRM built to accelerate lead management, partner relationships, team production, and revenue growth. This acquisition will enable Daily AI to continue its significant expansion of market share since its founding in 2019 and continue fulfilling its mission of empowering mortgage professionals to increase their performance with its suite of automation tools. "All of us at Daily AI are looking forward to partnering with Whiteboard," said Spencer Dusebout, co-founder and CEO of Daily AI. "With the combined power of our sales, development, product, marketing, and customer success teams, we believe we will be an unstoppable force in the mortgage lending industry to create automation and AI-driven products and services of significant value to our customers."
Shay Sabhikhi (pictured top) and Matt Sanchez (pictured top right), co-founder and COO and founder and CTO respectively, of CognitiveScale, spoke with Mortgage Professional America to describe the efficiencies of scale achieved since launching TrustStar, a SaaS-based product designed to provide mortgage companies with AI-powered market intelligence. Sanchez used an example of AI's use in lending: "If you were to get a bad decision, let's say you were denied credit for something, you'd want to know what that decision was based on, of course, as a consumer. And perhaps you might even want to know what you can change to get a better decision. That level of explanation is something we find very important. It becomes more important when you introduce artificial intelligence."
AI is an integral part of that second benefit in particular, and it's helping the insurance giant tap data to solve core business problems. In this interview, Huntsman offers insight into Prudential's broad initiative to transform underwriting, including how it translates digital strategy into business outcomes enabled by data science. How has the data science team participated in Prudential's digital transformation journey? Huntsman: Because underwriting is such a big part of our business, it was the first place the company looked at digitizing processes. Historically, between the life insurance application, medical exams, and statements from the customer's doctor, the underwriting process could be lengthy and painful.
The current issues of the lending industry can be solved through technology and digitalizing the operations as much as possible. A thorough research and analyses on this matter has led Rishabh Goel to the idea of launching Credgenics, a technological solution to digitize a largely manual collections workflow. Rishabh was soon joined by Anand and Mayank, who are currently the CTO and COO of Credgenics respectively. Analytics Insight has engaged in an exclusive interview with Rishabh to discuss about his vision of creating a technology-based solution for the lending industry. After graduating from IIT Delhi, I worked first with Deutsche Bank and then with Blackrock, where I understood the nuances of the lending industry and observed the problems with the current collections practices.
If mortgage lenders could figure out when their existing customers were thinking about moving, they could offer to help them find their next home -- and prequalify them for a loan. That's the thinking behind two complementary services offered to mortgage lenders by Senso, a Toronto-based fintech analytics startup. Senso Insights employs artificial intelligence to evaluate a lender's existing pool of borrowers to identify those who are actively looking to buy their next home. After calculating each homebuyer's purchasing power, Senso Engage provides them with personalized listings prioritized by neighborhood and affordability, along with access to loan pre-approval. This automated lead-nurturing campaign can help keep borrowers from defecting to another lender.
"Alexa, buy a stock that has the best chance of going up between 1% and 3% today." Could the complexity of financial research ever become this simple? New developments in artificial intelligence (AI) and machine learning (ML) are disrupting the underwriting process, portfolio composition, robo-advising, research and virtually every corner of fintech. Someday, you'll have reliable AI that can analyze your specific investing style, alert you as to where opportunities lay hidden and offer you hard-hitting analyses to stay informed. This is vital because sound financial systems underpin economic growth and development, and they're the engine behind the civilized world in advancing shared prosperity and reducing class inequality.
When we started our IDP business, our assumption was that cost savings would be the main driver for purchasing decisions -- in other words, how we can help our customers save 30–50 percent on data processing costs. But the last six years have taught us those cost savings are the number two priority for most companies looking for IDP solutions. Our customers have taught us that the number one thing is being able to effectively scale their operations. Today, data processing is heavily dependent on manual labor. We've worked with customers who were worried about their business picking up more volume because they just did not have the capacity to handle that increase.