Framing it as machine learning undersells the problem.
It's a hybrid model trading in an adversarial, real-dollar environment. The leverage comes from having a small human team trade big volume, much more than they could possibly trade directly, by augmenting their human abilities with automation and a model. Or seen from the other side, it's a model with human oversight.
Any system like that is high risk, high reward. All the successful ones started out by losing a lot of money. Paypal lost an incredible amount to fraud before they started breaking even. OpenDoor lost an incredible amount to mispricing, and took on a ton of balance sheet risk, before their business really started working.
I think Opendoor still does poorly in new markets, but then it improves as they work out the quirks of the local market and start asking the right questions and collecting the right information.
A big part of Opendoor is creating the right apps and processes to collect this information to feed their models. The machine learning part is important, but can give the false impression it's just about data scientists crunching numbers at head office, when in reality there's a huge real-world operational machine that's driving it.
It's a hybrid model trading in an adversarial, real-dollar environment. The leverage comes from having a small human team trade big volume, much more than they could possibly trade directly, by augmenting their human abilities with automation and a model. Or seen from the other side, it's a model with human oversight.
Any system like that is high risk, high reward. All the successful ones started out by losing a lot of money. Paypal lost an incredible amount to fraud before they started breaking even. OpenDoor lost an incredible amount to mispricing, and took on a ton of balance sheet risk, before their business really started working.
"To live, you must be willing to die"
- poker legend Amir Vahedi