An open source credit rating agency now exists!
I was very excited that Marc Joffe joined the Alternative Banking meeting on Sunday to discuss his new open source credit rating model for municipal and governmental defaults, called Public Sector Credit Framework, or PCSF. He’s gotten some great press, including this article entitled, “Are We Witnessing the Start of a Ratings Revolution?”.
Specifically, he has a model which, if you add the relevant data, can give ratings to city, state, or government bonds. I’ve been interested in this idea for a while now, although more at the level of publicly traded companies to start; see this post or this post for example.
His webpage is here, and you will note that his code is available on github, which is very cool, because it means it’s truly open source. From the webpage:
The framework allows an analyst to set up and run a budget simulation model in an Excel workbook. The analyst also specifies a default point in terms of a fiscal ratio. The framework calculates annual default probabilities as the the proportion of simulation trials that surpass the default point in a given year.
On May 2, we released the initial version of the software and two sample models – one for the US and one for the State of California – which are available on this page. For PSCF project to have an impact, we need developers to improve the software and analysts to build models. If you care about the implicatiions of growing public debt or you believe that transparent, open source technology can improve the standard of rating agency practice, please join us.
If you are a developer interested in helping him out, definitely reach out to him, his email is also available on the website.
He explained a few things on Sunday I want to share with you. They are all based on the kind of conflict of interest ratings agencies now have because they are paid by the people who they rate. I’ve discussed this conflict of interest many times, most recently in this post.
First, a story about California and state bonds. In the 2000’s, California was rated A, which is much lower than AAA, which is where lots of people want their bond ratings to be. So in order to achieve “AAA status,” California paid a bond insurer which was itself rated AAA. That is, through buying the insurance, the ratings status is transferred. In all, California paid $102 million for this benefit, which is a huge amount of money. What did this really buy though?
At some point their insurer, which was 139 times leveraged, was downgraded to below A level, and that meant that the California bonds were now essentially unbacked, so down to A level, and California had to pay higher interest payments because of this lower rating.
Considering the fact that no state has actually defaulted on their bonds in decades, but insurers have, Marc makes the following points. First, states are consistently under-rated and are paying too much for debt, either through these insurance schemes, where they pay questionable rates for questionable backing, or directly to the investors when their ratings are too low. Second, there is actually an incentive for ratings agencies to under-rate states, namely it gives them more business in rating the insurers etc. In other words they have an eco system of ratings rather than a state-by-state set of jobs.
How are taxpayers in California not aware of and incensed by the waste of $102 million? I would put this in the category of “too difficult to understand” for the average taxpayer, but that just makes me more annoyed. That money could have gone towards all sorts of public resources but instead went to insurance company executives.
Marc then went on to discuss his new model, which avoids this revenue model, and therefore conflict of interest, and takes advantage of the new format, XBRL, that is making it possible to automate ratings. It’s my personal belief that it will ultimately be the standardization of financial statements in XBRL format that will cause the revolution, more than anything we can do or say about something like the Volcker rule. Mostly this is because politicians and lobbyists don’t understand what data and models can do with raw standardized data. They aren’t nerdy enough to see it for what it is.
What about a revenue model for PCSF? Right now Marc is hoping for volunteer coders and advertising, but he did mention that there are two German initiatives that are trying to start non-profit, transparent ratings agencies essentially with large endowments. One of them is called INCRA, and you can get info here. The trick is to get $400 million and then be independent of the donors. They have a complicated governance structure in mind to insulate the ratings from the donors. But let’s face it, $400 million is a lot of money, and I don’t see Goldman Sachs in line to donate money. Indeed, they have a vested interest in having all good information kept internal anyway.
We also talked about the idea of having a government agency be in charge of ratings. But I don’t trust that model any more than a for-profit version, because we’ve seen how happy governments are at being downgraded, even when they totally deserve it. Any governmental ratings agencies couldn’t be trusted to impartially rate themselves, or systemically important companies for that matter.
I’m really excited about Marc’s model and I hope it really does start a revolution. I’ll be keeping an eye on things and writing more about it as events unfold.