Cloud servers, Egalitarianism, and the French Army of 1805

We’re often asked how we decide which clients are first in line to buy the best loans, since there is a limited loan volume with each issuance. Our fiduciary duties also oblige us to act in a way that is ‘fair’ to all our clients. The answer is that every client is first in line.

It’s true. In a way, we’re like Napoleon.

Napoleon was the greatest general of the 18th century. Napoleon won each battle with a combination of superior tactics and overwhelming force. He also was a champion of egalitarianism – all citizens should be treated as equals (which also meant everyone was front in line and equally at risk, unfortunately for them).

We pride ourselves at LendingRobot of our intelligent machine-learned technology. Our loan-picking strategy has been successful so far – but even the best strategy will fall apart if it isn’t executed properly and quickly.

After all, there are many other “armies” out there battling for the same loans we are. Hedge funds and intuitional investors would love to take all the best loans for themselves.

Instead of soldiers, we issue our commands through computers. There’s a problem, though: just as just as a Napoleonic soldier can only fire one bullet at a time, one server can send only so many loan requests at once.

So like Napoleon, we combine our superior loan-picking strategy with overwhelming force. Minutes before each loan release, a command goes out to count the number of clients who have orders to place. Utilizing cloud technology, we’re able to call on additional servers – effectively spawning soldiers onto the battlefield.

Like a line of infantry firing a volley, our army of servers is able to pick out their loan targets and fire off order requests at exactly the same time, usually 850 milliseconds after the round begins. Egalitarianism (our fiduciary duty) is upheld, and the battle for the best loans is won. Vive la patrie!

 

napoleon

(Battle of Chippewa, 1814, by H. Charles McBarron, Jr.)

Full-Metal Algorithm

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