If you do not live in a flood zone, it varies a lot. Florida requires new homes to be built to appropriate hurricane proof codes since Andrew, so newer homes insurance are about like anywhere else in the nation. Older homes are somewhat more expensive, but usually not insane.

The issue here was fraud. My credit score doesn’t help you assess risk if someone else is impersonating me.

Credit score likewise plays a role.

There are many many attributes taken into account when discussing fraud. Some models use methods which take in all attributes. There’s many kinds of fraud as well, some of which will be impacted by credit score (for instance if you have more credit, and use your credit card more often, you’re more likely to be a target for a “hacker”. This means fraud will be more likely to occur on your account).

For reference: I’ve built fraud detection models being used at banks.

As but one component to this a person who never takes on debt has, tautologically, managed to live a life without any need of debt. That implies he would have little difficulty continuing to live a life without access to credit. Because of this, he will generally have substantially less concern about his credit rating than a person who depends on credit for their basic livelihood.

If I avoid debt for a decade, suddenly seeking debt should be a bit of a red flag, and I should have a correspondingly low credit score.

Yeah no.

Credit scores, being a composite set of observations of recent financial behavior, are literally the opposite of an immutable genetic characteristic fixed from birth.

Credit scores are far, far, from perfect, but if you have a better way of judging the future actions of a human than compiling a list of their recent actions do speak up.

The use of data from credit reporting agencies is not to predict the outcome of lending to a specific person, but to predict the outcome of many, many loans to many, many people. For which I would say it succeeds, as the entities utilizing it seem to be economically successful due to making a smaller proportion of bad bets than entities who would not, for example in the linked article.

Second, the whole concept of “bad neighborhoods” where people aren’t trustworthy is partly a racist trope (there are good and bad people everywhere), and partly the result of generations of well-documented racist policies by the government and banks that prevented those areas from being developed.

Third, nobody said the cars were getting stolen from “bad neighborhoods”. What the article says is that the vehicles were being driven to an area just outside of the Car2Go coverage area and dumped there.

The concept of a "bad neighborhood" comes from crime statistics, not racist tropes. Either crime (theft, robbery, fraud, et all) is high, or it is not high, race be damned. Subscribers to a particular political ideology need to calm down with the whole "your facts/science are racist" bit, because it hurts everyone overall in the long run.

Ouch man, you're not even going to try to dog whistle?

From your link:

As of 2003 West Virginia Blacks accounted for just 3.2% of the total population and 34.9% of the total prison population.

Simply translated: White areas are safer areas. That is an irrefutable fact. The poverty argument, or excuse more accurately, can be torn to shreds time-after-time.

There are so many conclusions being jumped to there that you've probably worn the mat out already. All of that racist bullshit completely ignores the disparities in enforcement, prosecution, and sentencing. As an added bonus it completely misinterprets how the FBI categories race. But hey, maybe you can get a good deal on a dog whistle for Prime Day.

There are plenty of "bad neighbourhoods" with white people and every nationality. These same bad neighbourhoods exist in UK, Canada, across Asia and Latin America, etc. It's quite rare to find any large urban area without one. It's a human problem not a race one and it's hardly a trope. It's very much real.