RapidRatings: Vendor Analysis (Part 1) — Background & Solution Overview

Ask any procurement organization what area of risk is most pertinent to them and supplier financial risk will usually rise to the top. In particular, suppliers that are classified as strategic or critical based on business impact (not just annual spend) need to be monitored more closely and regularly to maintain operational resilience, ensure business continuity and minimize business risk — and this monitoring obviously must include evaluating financial viability. This is a core aspect of broader supply risk..

Predictive analytics are key to getting early insight (especially relative to your competitors) on suppliers whose financial health is starting to waver. Getting such intelligence via predictive analytics requires basically two things: strong analytic models and good data.

For publicly traded suppliers, you can get financial statements, but you still have to extrapolate from the historical financials to gain actionable insight or develop some sort of predictive statistic. Some companies have used the Altman Z empirical scoring model, but not only is Altman Z an outdated algorithm that has been shown to be inferior to more updated ones (to be discussed later), but you also have to spend the time compiling and interpreting the data, which tends to fall outside the usual purview of the procurement professional.

The bigger problem, though, is the lack of financial data readily available for private firms — especially in the U.S. For most corporations, up to 80% of their strategic/critical suppliers are private and don’t typically share their financial statements with customers for various reasons. One of those reasons may be that they’re highly profitable and don’t want procurement to see this information, although this is certainly not always the case. In other circumstances, a supplier might feel that being private exempts them from disclosure. Or in the worst of cases (from a supply risk perspective), a vendor might not be doing well financially and is worried about losing additional business. Yet, a customer still wants to be sure that a supplier is not in financial distress — or moving in that direction. So, what the buyer would really like is a scalable managed service with a service provider that can help predict supplier financial health, including bankruptcies.

But this won’t happen unless such a provider can address the supplier concerns of protecting the confidentiality of their raw financials.

This is where RapidRatings comes in. RapidRatings is a provider of empirically driven financial health scoring of businesses — including private suppliers. The firm’s Financial Health System uses financial data as inputs and then utilizes them within 25 industry-specific, integrated analytic models that calculate a normalized financial rating (0-100 scale) designed to help predict future corporate defaults and identify companies’ inherent strengths. Think of it as a “FICO score for corporations.”

RapidRatings claims to have predicted 94% of bankruptcies at least six months in advance, and that the FHR provides predictive capabilities out to 12–18 months. The firm also specializes in working with private suppliers to obtain the necessary financial data to produce their FHR. In fact, nearly two-thirds of the more than 40,000 rating events performed by RapidRatings are of private companies. Most impressively, the firm claims a greater than 85% success in getting private suppliers to submit their data.

This Spend Matters PRO Vendor Snapshot provides facts and expert analysis to help procurement organizations make informed decisions about RapidRatings' solution offering. Part 1 of our analysis provides a company background and detailed solution overview, as well as a summary recommended fit suggestion for when organizations should consider RapidRatings in the procurement technology area. The rest of this Spend Matters PRO Vendor Snapshot research brief covers product strengths and weaknesses, competitor and SWOT analysis, and insider evaluation and selection considerations.