The most important role in any organization that invests financial capital for the purpose of creating economic value is risk estimation or for those in the industry – “underwriting”. In simple terms, the underwriting practice quantifies the risk and the return associated with an investment opportunity using a combination of historical performance, financial terms, and professional insight (I think our underwriter has something that resembles Harry Potter’s wand under his desk…but I digress).
Like many organizations in Financial Services, we use “alternative data” to inform and improve the way we think about risk and return, in supplement to (and as a complement to) all of the usual data suspects. Unlike data related to historical account performance, alternative data is the “data exhaust” that is created from unrelated activities – like using Yelp reviews to assess small business risk as developed by JP Morgan Chase just a few years ago. In consumer credit risk, no cost “alternative” sources of zip code level data include the IRS , the Census Bureau , Zillow . Organizations with deeper data science skills may be “scraping” social media sites for consumer behavior data to inform credit risk . These alternative sources can help those responsible for pricing risk associated with deployment of financial capital to decrease variance, increase accuracy, and generate higher returns for investors.
For more information about FLOCK Specialty Finance, contact Jennifer Lewis Priestley, CDO (jpriestley@flockfinance.com)
[1] https://www.bostonglobe.com/business/2016/09/04/could-yelp-indicate-whether-your-business-deserves-loan/Bal1Oo5c1yJTVkamdREgGL/story.html
[2] SOI Tax Stats – Individual Income Tax Statistics – ZIP Code Data (SOI) | Internal Revenue Service (irs.gov)
[3] Data (census.gov)
[4] Housing Data – Zillow Research
[5] https://news.uga.edu/how-social-media-posts-could-affect-credit-scores/
