The Privileged Population of Technology & the Downturn of Manufacturing: What it Means for P2P Lending

Many new investable asset classes have emerged in the FinTech revolution, the most prominent of which might be peer-to-peer (P2P) lending, which allows retail investors to lend money directly to other individuals.  The yields are very attractive, ranging from 6% – 30%+ depending on credit quality and loan term (3-5 years), effectively allowing the average Joe to become a bank, democratizing the yield spreads that were once solely the domain of large financial institutions (think credit card interest rates that you can now charge someone else).  

So what’s the catch?  The loans are unsecured and can be used for any purpose.  If the debtor defaults, there is no collateral to buffer losses (you get back whatever a collection agency can recover).  The debtor can simply not pay and allow the default event to damage his/her credit rating.  So, while banks have large departments dedicated to credit analysis, allowing for robust credit modeling before loans are made, the retail investor relies on the FinTech platforms that have emerged to facilitate these loans, e.g., Lending Club, Prosper, etc.  If they model credit risk effectively, investors will benefit and vice versa.  However, they are new to this game and are being tested by recent socioeconomic developments.

As this article, Tech & Subprime Crunch, outlines, the services sector, especially technology, is driving job growth (over 3% in 2015, highest in a decade), while goods-producing manufacturing has contracted in recent years and is projected to remain stagnant through 2024, in spite of recent political momentum that suggests otherwise.  That’s led to an 8% increase in tech wages in ’15, thanks to increased demand, while manufacturing wages are at risk of stagnation or even decline.  It’s a diverse problem that becomes quite evident when one reviews the most common jobs by state, revealing that Truck Driver is the most common, with driving of all sorts employing 4.1 million people at the end of 2016.  Not only is truck driving a direct outgrowth of manufacturing, it’s at risk of being radically changed or eliminated via driverless technology (just as robotics endangers the assembly line worker)… Technology wins again!


What effect has the change in employment trends had on retail credit?  Default rates at the low end of the credit spectrum have increased, presumably as the less-skilled workers find jobs hard to secure and wages stagnant, coupled with moderate inflation, effectively decreasing their standard of living and putting additional strain on their debt burden.  P2P lending platforms have responded by increasing interest rates, primarily in the three lowest credit tiers per platform, from 2% – 6.3% in 2016.  One might argue that a higher interest burden on the shakiest credits isn’t a recipe for better debtor performance or increased net interest margin; perhaps more astute credit vetting is the better path.  But, again, these new P2P platforms are new to the racket of credit analysis, and there will be a learning curve as they improve their credit models and learn from their mistakes.  

What’s the take-away for investors?  P2P investing is an attractive, relatively new asset class that expands the available universe of return drivers for retail investors (just 10 years ago, corporate and government bonds were the only choices for debt invesments), which may improve an investor’s risk/return profile.  But it’s not without its risks, macro-economically and operationally.  As the socioeconomic profile of America changes and the credit capacity and expertise of the P2P platforms evolves and matures, it’s best to take a conservative approach in one’s allocation.  Stick to the highest credit grades available on P2P, where the most credit-worthy borrowers reside (theoretically primarily in the expanding service sector), requiring less-robust credit modeling by these nascent platforms.  

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