I'd tend towards 2. Seems there are some issues danced around. They mentioned that there are other indicators of risk: the equity in your home, savings, job stability. All things that also reduce your actual need for credit. Lenders can take that stuff in to account, a mortgage broker might not but if they work closely with the underwriters then they will. You can also leverage your savings and put more down payment in. What's harder is to take folks with little or no savings, little or no credit history, potentially sketchy credit history, and a real need for credit and then determine their future loan repaying habits. Some times they've seen the light and repay on time, every time. Other times they don't. We're not talking about people with lots of money and we're not talking about folks with no money, it's the middle folks that have probably been late with some payments and maybe got themselves in to "trouble" a few times.
What would the other factors be that you'd measure them on to do better? Race? Religion? Education? I bet there are some algorithms that work better but they might be more messy. I bet if you looked at the credit history of a client's circle of 6 closest friends, the credit history of their parents, whether or not they were married, whether or not their circle of friends and families thought they were happily married and their attendance records at work and school and the last education level they had you could make some good predictions. I wouldn't be surprised if there were some religions that had better loan payers than others and some that had worse. I also wouldn't be completely surprised if there were races that tended to have better loan repayment habits and some that had worse, I'm fairly certain that it's true if you limit your samples to certain regions. I wouldn't be surprised if you could correlate a borrower's child being a good or poor student with the borrowers credit risk. I woulnd't be surprised if you could correlate the number of children had out of wedlock with credit risk. I don't know that'd we'd want large institutions using these kinds of factors to make lending decisions, we want it to be clinical, sterile, and somewhat blind which leads us back to something like the FICO score.
Now if they showed mortgage brokers gaming it, that might be a different matter, they're simply complaining about missing the cut-off. Trying buying groceries with just a couple dollars less than what the bill comes to..
What would the other factors be that you'd measure them on to do better? Race? Religion? Education? I bet there are some algorithms that work better but they might be more messy. I bet if you looked at the credit history of a client's circle of 6 closest friends, the credit history of their parents, whether or not they were married, whether or not their circle of friends and families thought they were happily married and their attendance records at work and school and the last education level they had you could make some good predictions. I wouldn't be surprised if there were some religions that had better loan payers than others and some that had worse. I also wouldn't be completely surprised if there were races that tended to have better loan repayment habits and some that had worse, I'm fairly certain that it's true if you limit your samples to certain regions. I wouldn't be surprised if you could correlate a borrower's child being a good or poor student with the borrowers credit risk. I woulnd't be surprised if you could correlate the number of children had out of wedlock with credit risk. I don't know that'd we'd want large institutions using these kinds of factors to make lending decisions, we want it to be clinical, sterile, and somewhat blind which leads us back to something like the FICO score.
Now if they showed mortgage brokers gaming it, that might be a different matter, they're simply complaining about missing the cut-off. Trying buying groceries with just a couple dollars less than what the bill comes to..