Where you spend can have an impact on a decision… e.g. you may have the income and savings but if you’re regularly spending on gambling that can be a red flag.
If the loan assessment criteria are objective, they can be quantified.
The basic concept here is: ZKP lets you prove arbitrary statements.
Instead of:
Here is entire bank history, you decide.
You can say:
Had a fixed income above $X for 12 months.
Had a surplus of $X after fixed expenses in the last 3 months.
Did not buy anything irregular above $1000 in the last 3 months.
"Did not gamble" is a moral judgement. Who knows, maybe I'm buying gum at the local casino, is that gambling? Maybe I'm tossing a coin every night after work as to whether I should drive in the opposite lane, is that not gambling? You can only objectively measure financially risky behavior in statistical terms.
Think of a ZK proof as a program that can take both public and private knowledge as input, and produce public and private knowledge as output.
This is what seems magical to me: A program with secret input. You can't run the program to verify that my execution of the program is correct, but you can verify a proof that I ran the program with input you didn't have.
The way private knowledge works is through cryptographic commitments.
For example, the bank may start by giving you a signed, structured document with your transactions.
You can then feed their signature and the document to your program, and produce any derivation.
You can use the MCCs of each tx, then generating a zk-proof that shows none of the MCCs in your account match restricted categories.
This requires cooperation from the "bank", ideally providing Merkle trees to make sure no tx is missing in the proof like it would be for a blockchain-based solution.
