There’s a reason why bank loan officers and potential homeowners trust Zillow and its Zestimate® home valuation model. A Zestimate incorporates public, MLS and user-submitted data into Zillow’s proprietary formula, also taking into account home facts, location and market trends. 

Just as Zillow has shown that an algorithm based on fundamental home price data can be quite accurate in valuing a homogeneous product such as a home, Valulytics has shown that the same holds true for banks. After all, banks are highly regulated, which makes them highly homogeneous due to the similarity of their products, their regulator imposed financial constraints and the “follow the leader” nature of their style of management.

This isn’t just our opinion. We tested this hypothesis by developing an algorithm for valuing banks based on industry market sentiment and certain bank financial fundamentals. We even wrote a whitepaper about it that demonstrates that our algorithm has been found to be over 93% accurate in predicting bank fair market values over the period from 2010 to the present (based on 12,000+ bank individual monthly and quarterly observations). 

Here’s how our algorithm works. Each month we obtain stock price information for approximately 400 publicly traded commercial banks and we use statistical techniques to obtain an up-to-date valuation algorithm that we then apply to the entire universe of approximately 5,000 US banks.

Since this value is based on publicly traded bank stocks, it results in a “marketable minority” value based on “market comparables”. Accordingly, it qualifies as a “market-based valuation method” under IRS and business valuation industry definitions.