The conceptual basis of classical hypothesis testing is useful in a wide variety of areas.* Pity most students get too caught up in following the recipes for constructing test statistics to realize this.
A Type I error is foreclosing against a good borrower. A Type II error is letting a bad borrower avoid foreclosure. I will readily grant that a Type I error is worse than a Type II error, so we should tolerate some of the latter in order to avoid the former. However, I contend that we have let this bias get completely out of hand, resulting in a huge pileup of Type II errors with catastrophic effects on the housing market.
This is in regard to a Maryland family that has gamed the system and not made a payment on the house they continue to live in for over 5 years.
* A Type I error is when you make the mistake of rejecting something that is true. A Type II error is when you make the mistake of not rejecting something that is false. For example, a Type I error is convicting someone who is innocent, while a Type II error is letting someone go who is guilty.