The Credit Manager’s Secret Weapon: A Crowdsourced Risk Score

Crowdsourced Credit Risk Score: The Credit Manager’s Secret Weapon

Business bankruptcy hits the headlines every week. 

And while there are often advance warning signs of financial trouble, lots of credit managers still get blindsided. Just look at the list of unsecured creditors in any bankruptcy petition!

While a business failure can leave you in the lurch if you didn’t see it coming, we’ve got some good news to share.

Now, we've improved our bankruptcy prediction accuracy, right when you need it most. The FRISK® score, well known to thousands of credit managers who have come to rely on it — has got your back.

Find out more about how we improved the FRISK® score’s accuracy and reliability.
Download the crowdsourcing white paper here

Timing matters

As a credit manager, you walk a fine line. Knowing the right time to mitigate risk and tighten credit terms is a critical part of what you do.

You need to keep credit flowing so new and existing customers continue to buy from your company. But you also need to make sure your company will be paid on time. Adjust terms too early, and you miss out on revenue. Let things go too long, and you might get hit with a loss.

And when you’re talking about big public companies, there can be a lot of money on the line.

Why public companies are different

For private companies, payment history is a reliable distress signal that lets you know when your customers hit a financial rough patch. And if you’re like most CreditRiskMonitor subscribers, you routinely use a payment-based metric to assess creditworthiness, and adjust terms or take other steps to protect your company, accordingly.

But public companies behave differently. When they’re in financial trouble, payments usually won’t tell you. As a result, it can be easy to miss the warning signals. Compounding this problem, some commonly used risk scores, such as the Altman Z-score, may predict risk too early, so you react sooner than you need to. 

Alternatively, you can dig deep into the available public company data -- debt agency ratings, SEC filings, financial reports, and more. But gathering all the relevant data and spreading financials to support a home-grown credit analysis can be extremely time consuming, and interpreting the data correctly -- especially when there are contradictory signals -- complicates the task.

That’s why, 10 years ago, we created a predictive financial risk score for public companies, called the FRISK® score. And now, we've added activity signals from your fellow credit managers, to up our accuracy of predicting bankruptcy, right when you need it most.

Crowdsourced Click Data: The ‘Secret Weapon’

The FRISK® score gives credit managers a reliable and timely way to rein in credit on a public company. It predicts whether a public company will file for bankruptcy within the next 12 months, with 96% accuracy.

And last year, we discovered that when a select group of credit managers -- our subscribers -- use the CreditRiskMonitor website to research specific companies, it’s an excellent forward-looking indicator that can be used to improve our predictive bankruptcy risk score for certain companies. So we enhanced our model with this crowdsourced click data, which improved accuracy and timeliness of the FRISK® score even more.

We refer to this proprietary data from our website as your ‘secret weapon’. To understand how it helps you to predict bankruptcy, here are two recent examples:

Example #1: Catalyst Paper Corporation:

Take the Catalyst Paper Corporation, a company that’s been in the ‘Red Zone’ of risk for many months before their bankruptcy filing. When crowdsourced data is added to our model, the FRISK® score drops from 3 to 2, which means it has double the chance of a bankruptcy within 12 months. In fact, Catalyst did file five months after the crowdsourcing data showed the drop.

Example #2: Performance Sports Group

The same score improvement occurs for Performance Sports Group, which filed for bankruptcy in October 2016. Here too, crowdsourcing data highlighted greater risk, causing a several point drop in the FRISK® score, earlier than it otherwise would have occurred. As a result, we were able to alert our subscribers that bankruptcy risk doubled in the months leading up to their bankruptcy filing.

A Collective Gut Check

As the result of this enhanced, ‘crowdsourced’ financial risk score, you’re only seconds away from a collective ‘gut check’ from thousands of corporate credit professionals in Fortune 1000 companies around the world. It’s like having every credit peer group and credit analyst on speed dial, for every industry you can think of!

The proof?  Every week, credit managers tell us that the FRISK® score has given them the heads-up they needed to save their bacon. And there’s no better feeling than that!

Learn how ‘credit crowdsourcing’ helps to uncover hidden public company risks.
Download the crowdsourcing white paper

About CreditRiskMonitor

CreditRiskMonitor is a financial news and analysis service designed to help professionals stay ahead of public company risk quickly, accurately and cost-effectively. More than 35% of the Fortune 1000, plus thousands more worldwide, rely on our commercial credit reporting and predictive risk analytics for assessing the financial stability of more than 56,000 global public companies.

At the core of CreditRiskMonitor’s service is its 96%-accurate FRISK® score, which is formulated to predict public company bankruptcy risk. One of four key components calculated in the FRISK® score is crowdsourced subscriber activity. This unique system tracks subscribers' patterns of research activity, capturing and aggregating the real-time concerns of what are essentially the key gatekeepers of corporate credit. Other features of CreditRiskMonitor’s service include timely news alerts, the Altman Z”-Score, agency ratings, financial ratios and trends. CreditRiskMonitor’s network of trade contributors provides more than $150 billion in trade data on their counterparties every month, giving them visibility into their biggest dollar risks.