Elon Musk, founder and CEO at Tesla, just announced his company will add an electric semi-truck to their fleet of products. The immediate public assumption was that this innovation will do more than just improve the environment—it may follow Tesla’s consumer approach to make all driverless vehicles. If semi-trucks can eventually deliver goods without a driver, the innovation would threaten up to 3.5 million truck drivers in the United States alone. This shift is happening on assembly lines, in transportation, and many other industries. Reports widely suggest massive job cuts in the finance industry in the coming years, especially at the banking level. The “man versus machine” argument has made its way to private lending.

Traditionalists tend to see fintech as a foe to the industry where others depend on innovation to some extent in their day-to-day businesses. Marketplace platforms and fresh regulations contribute to this evolution, making it possible to invest in real estate from your couch. This evolution has caused reflections on how things have been done to date. The impact of innovation is yet to be seen because adoption and adaptation occurs at such a rapid pace. Demand for systems and solutions in the industry varies. Meaning, there are fewer lenders seeking “AI” (Artificial Intelligence) for the purposes of replacing human underwriters with robots than there are fund managers looking for better data, and ways to visualize that data, in an effort to make better decisions.

Fintech is seeing this demand and developing a supply solutions. Many lenders are even taking it upon themselves to develop for their own needs, in-house. So how has this demand shaped the horizon of fintech and who’s driving that demand? While technology is spreading far and wide, categorizing private lenders by technology adoption is rather simple.

Domo Arigato, Lender Roboto

The same Elon Musk previously mentioned just acquired a company called Neuralink, whose pursuits make most science fiction look antiquated. Musk says it will attempt to develop technology to integrate artificial intelligence with the human brain so users can do things like improve their vocabulary with the simple firmware update. The most forward-thinking fintech innovators aren’t quite reaching to that extent, but they are introducing machine learning into tasks like underwriting and loan approval. In theory, this allows lenders to have an idea about loan quality based on real-time analytics and past performance. It “stereotypes” borrowers and projects based on historical indicators. The machine approves or denies loans before a human ever sees it. The benefit to this level of innovation is the depth of understanding and obvious time lenders would get back. Although AI introduces supposed human-level interaction with data, it still isn’t quite human. Lenders who rely wholly upon machines or data for algorithmic decision-making are disregarding the importance of experience, intuition and creativity to some extent. It is advisable for progressive lenders to calculate ways to embrace fintech without removing the human from such an important fiduciary process.

 

Loan approved

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Big Data in Beta

The next tier of fintech integration is made of lenders who understand the power of data and seek or develop tools to improve the quality of loans and the time it takes to close them. More and more lenders are using credit profiles as a trace of breadcrumbs to how borrowers might perform rather than as a qualification benchmark. As borrower, property, and demographic data is analyzed and visualized, lenders make better decisions. Some data is used as the prime witness in the loan approval process where other sets are merely used to confirm or raise new questions on decisions already made. The extent of data utilized can come down to cost. The best data, pre-packed to minimize human entry, comes at premium. Other data is available to the general public, but typically requires human entry. One pitfall of fintech integration is the lack of good options or the inability to find the right fit. This often leads groups to develop their own solutions, which is far more expensive than most anticipate. Rather than jumping from option to option or responding favorably to every LinkedIn developer who pitches their services to build an exclusive platform, lenders should research all available options, compare them carefully, and determine the best way to implement technology without compromising the human element.

Motorized Horse and Buggy

There are those who view any replacement of word processors and Excel spreadsheets as an amazing advancement. They are doing whatever they can to speed up processes, even if it doesn’t necessarily lead to improvement. Some of these groups will integrate several third-party services like Dropbox for cloud storage, or a popular LOS—but they lack a full-service solution. These types usually settle for software that allows them to create borrower and investor statements, but unknowingly lacks all the important aspects of lending that occur prior to funding. This contingent of lenders may not be using technology to its fullest extent, but perhaps careful integration of technology, before turning components of the loan process over to a computer, is a good thing. It’s actually commendable if the pace of adoption is second to a commitment to policies and procedures. As these types of lenders consider and adopt new technology, there should be heightened awareness to avoid wasting time and money trying to fit with trends.

Sticking with the Legal Pad

There are still many, many lenders who fear or reject technology. This type of lender typically delays the adoption of fintech because they’re either ignorant to what is available, or they’re ingrained in their ways. The due diligence list is scribbled on a white board. They have their favorite deals written on dated pages in a notebook. This type usually has no issue with high legal bills, because they rely almost entirely on counsel to produce documents sent to borrowers—from the first LOI, through loan documents, and even statements and communication during a loan term. There is no major harm in this model, but it does stifle growth and scale. It also frustrates borrowers when lenders move slowly because there is no certain process in place. These lenders should also explore options and carefully select ways to improve through adoption of some extent of fintech.

Every lender has similar options:

  • Develop its own solutions. This can become expensive and typically doesn’t lead to a successful outcome.
  • Utilize several third-party services. This can fulfill needs of the moment, but wastes money as an organization jumps from solution to solution, and deflects control, in part, to the third party.
  • Purchase an LOS or software solution. This can range from a few hundred dollars to over a hundred thousand dollars per year depending on the organization size. An LOS alone falls short of all that is needed. But too much non-correlated software can be counter-intuitive.
  • Do nothing different. Lenders can sit on the sidelines and keep things on white boards and spreadsheets until the right fit comes along.

The demand for quality fintech is absolute, but the human core that has formed the private lending industry should be unwilling to compromise what made it great. Lenders must effectively balance the “fin” with the “tech” as new innovation arises. So while considering new and proven solutions for loan and investor management, it’s important lenders note the unmatched value of people.