Economics, AI, And Digital Lending At Drive ‘19

Artificial intelligence and real economics drive the discussion on day two at CU Direct’s annual educational confab.

 
 

GraphsandLaughs economist Elliot Eisenberg gave a lively, balanced take on the nation’s economy during his keynote address on Wednesday at CU Direct’s Drive ’19 conference at The Cosmopolitan Hotel in Las Vegas, NV.

Rapid first quarter GDP expansion (3.2%) is largely the result of one-off events that hit the U.S. economy in harmony. Eisenberg —  known as the “Bowtie Economist” — predicts the economy will grow approximately 2.5% in 2019 and approximately 2.0% in 2020 compared to the 3.0% growth posted in 2018. 

Although growing at a slower pace increases the economy’s susceptibility to a recession, this is not a pressing issue at the moment, according to Eisenberg. The yield curve is nearing inversion,  which is historically the most accurate indicator of an coming recession. On average, a recession hits 600 days after the beginning of the inversion, so should the curve remain inverted, the expected recession would be on the far horizon.  

The remainder of the day was filled with breakout sessions and panels on topics ranging from mortgage lending to artificial intelligence. In a session on mortgages, panelists agreed that relationships, traditionally one of the biggest strengths for credit unions, are a problem. That’s because credit unions tend to have amazing relationships with members but lack the same connection with real estate agents. Realtors are integral to funneling consumers to credit unions, so many institutions are looking for ways to build that camaraderie. 

Per the overall theme of the conference, the panel proceeded to discuss technology that improves process efficiency and client connectivity. One key message: Credit unions are spending too much money trying to mimic the large online mortgage finance companies. Instead, cooperatives should use the scale of these larger institutions to their advantage. Most credit unions do not target the entire country, so they should use technology to reach the specific needs of their niche. Simply imitating a nationwide lender is neither effective nor sustainable. 

Proceeding with the overarching theme of technology, another breakout session focused on artificial intelligence in retail lending. Sure, artificial intelligence streamlines underwriting, but there are more applications. In underwriting, there are AI programs that take a holistic view of the loan candidate. For example, instead of looking solely at income and FICO score, AI programs can incorporate more abstract qualifications, such as whether a candidate’s profession, independent of salary, has a bearing on their ability to pay back a loan. These characteristics hopefully provide confidence in automated decisioning as a method to streamline underwriting. 

Auto lending and identifying the condition of repossessed cars on a mass scale provides another example of AI use. There are programs that identify specific traits of cars with 99% accuracy based on a single picture. The knowledge is based on previously associated characteristics and pictures that the program “learns” from and applies in mass across an upload. 

These are easy examples of how credit unions can use AI and machine learning to increase efficiency. The most successful products will not require a data scientists to operate, but they will allow loan officers to learn without too much difficulty. 

The last panel of the day was a conversation about participation lending and the digital platforms that make it easy to connect with a buyer or seller. Pricing is an issue, however, as there is no set market price on a participation. The price is negotiated between the buyer and the seller, which hinders overall transparency. 

Some of these digital platforms list the point at which all deals in the database are clearing, giving credit unions on both sides of the participation a rough idea of how participations are pricing. Technology in this space is aimed, in a large part, at reducing friction between the parties and reducing the time to negotiate the contract. 

For the most part, credit unions are looking for ways to make their lending programs more efficient through digitalization, artificial intelligence, and more. Drive ’19 has highlighted the ways all cooperatives, despite size and resource availability, are implementing technological changes now. 

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May 17, 2019


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