Exploits
An exploit, laut Wikipedia, is “a sequence of commands that take advantage of a bug, glitch or vulnerability in order to cause unanticipated behavior.” One of the many things that makes designing distributed systems such a challenge is trying to avoid creating such vulnerabilities. It can be a complete nightmare trying to fix any that make it into a live system, especially if they’re the sleeper kind that only get uncovered after years of successful operation.
The Fractional Reserve Banking System, is a distributed system. It has a set of rather poorly documented rules that are implemented by banks worldwide, which have emerged for the most part from empirical experience. So is this the bug that caused the credit crisis?
Consider two banks:
| Bank | Deposits | Loans | Reserve |
|---|---|---|---|
| A | 1000 | 900 | 100 |
| B | 1000 | 0 | 0 |
Bank A has $1000 in deposits, has lent out $900 and has kept a reserve of $100 as it is required to. To be very specific , since it matters more than might be imagined: Bank A is an American bank, and the $1000 is being kept in daily checking accounts, so there is a reserve requirement. To make the example as simple as possible, Bank B just has deposits, and no loans. Bank A creates a Mortgage Backed Security of $900, and sells it to the deposit holder at Bank B.
| Bank | Deposits | Loans | Reserve |
|---|---|---|---|
| A | 1000 | ||
| B | 100 | 0 | 0 |
| MBS: $900 |
So far so good. Bank A lends out $900 again. It is allowed to do this, this in some sense is what being a bank is all about. The $100 it keeps as a reserve, is a contingency fund to cover any daily demand for funds. The $900 borrowed is then used to purchase something, and eventually is deposited at bank B. This gives the following:
| Bank | Deposits | Loans | Reserve |
|---|---|---|---|
| A | 1000 | 900 | 100 |
| B | 1000 | 0 | 0 |
| MBS: $900 |
Notice that the third table is identical to the first, with respect to the money, loans and reserves at each bank. The only difference is the $900 mortgage backed security, representing the $900 in loans that were sold by bank A. Bank A in other words, can go through this loop as many times as it wants, as long as it can find people to lend to, and people to buy the resulting securitised loans.
I haven’t yet found much in Economics about what limits there should be on commercial bank lending. The fractional reserve banking system itself, if it were working as described in textbooks, would impose an implicit limit on the amount, but even this doesn’t appear to be directly acknowledged. The other problem, is that loans are made for many years. So any failure in their systemic regulation, wouldn’t necessarily be noticeable for quite a long time. By the time it was noticed, it might even be thought to be the normal behaviour of the system.
Which does indeed appear to be what’s happening now.
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I was just looking for information about this when I came upon your blog post. I’m just dropping by to say that I really liked seeing this post, it’s really well written. Are you considering posting more on this? It appears like there is more material here for more posts.
Thanks for the feedback.
Yes, i’m intending to post quite a lot more. When i began i thought i would be explaining the fractional reserve system, but i’ve started to realise what i’m actually going to have to do is reverse engineer it. So i’m slowly working through that. It may take some time…
Nice article. I came across your post by searching on “statistical multiplexing” and lending. It’s surprising that there isn’t much classical economics that thinks of the world in these terms. Maybe this paradigm is only natural to computer scientists and professional economists find their existing paradigms more attractive.
The other thing I liked about your post was the approach of looking for a bug. One thing I’ve always found dissatisfying about economic theory is that there is so little way to test or really apply it. I think the finding a bug attitude is a partial solution to that.
Thanks again for the nice post.