Banker Bot, the ultimate judge of Bean Counters

We joke that bankers are bean counters, but it is literally true, they count beans. They talk to grocers, farmers, food processors. They visit their factories and farms, kick the tires on their vehicles, and makes notes, they count beans.

Banker bot can tell you the precision by which its member banks count beans. Banker bot measures their precision by matching their deposits and loans against the minimally redundant flow constraints.  It knows what the minimal flow of beans should look like, under the assumption that bean counters are pretty close. Pretty close is the assumption, at least some of the bankers have to make good faith bean counts. This is the Black-Scholes assumption.

The banker bean counters are making loans and deposits based upon whether their bean count shows more beans tomorrow or less beans tomorrow. All the member banks view the savings and loan balances that banker bot publishes, and these balances represent the collective judgement of all bean counters.  Further, all member banks know that banker bot is no arbitrage, when the collective estimates our out of balance, rates are paid and reset.

So, you see, in terms of rates paid and received, the precision of the bean count is maximally measured, and the value of banker bot is the value of measuring precision.  The actual operation of banker bot is cheap, a spreadsheet and electron exchange, at a minimum.  What makes the unit of exchange? The units of rates paid and received are automatically exchanged for beans because the numerator is optimally accurate; consumers can use that numerator to trade beans today for beans tomorrow.  Its about counting, ensuring that all actions in the bean industry can be sequentially ordered, and knowing when that ordering is violated. When the ordering is maintained, then the unit of account is an index that tells us how far back in line we are, at the bean check out stand..