The frustration of trying to invest in my hometown

The frustration of trying to invest in my hometown
bbc.com

If private lending doesn't want to back this project, even if there isn't 'strong competition' (at least 5 lenders willing to accept the land within a city as collateral), then the government (whichever layer values the land the highest) should be willing to be a buyer at that value and that should be the collateral for a loan at median market rate.

Automating that process and making it easier for consumers to check that data is a natural fit for tech.

What does this lead to? A value of zero in case of tenants is highly unlikely unless there are some large cost are modelled. If there are a lot of vacant properties with zero current value, that might lead to all values being depressed. If in the set are buildings with high future maintenance cost modelled, the value of the set could become zero.

Perhaps the bank didn't want the risk of all eight properties at the same time and he should have moved step by step: first buy and redevelop the buildings with tenants, only then to expand and get leverage while building on an existing portfolio. That is the way real estate fortunes are made where I live. Get a building, make condos, fill them, show a positive cashflow and add leverage. Rinse and repeat. With rental income in 5%+ and interest moving to 1% it has been a few lucky decades for those involved.

The statistics mentioned between loaning in white and black communities are quite stark. However, to give some more perspective from the lender. A low interest rate signals even smaller risk appetite for the lender. If there ever was room for defaults in portfolios, there is none at interest rates < 1%. It just kills your business to have any one customer fail on payments or worse needing auctioning off. I guess he could easily get crowdsourcing or private investment at 25% of needed capital with his story if he did 75% downpayment at 4%. But that would kill his part of the business case. I would agree that this risk management view could blow up inherent biases in the way valuation work.

Banks lend on statistics, just as insurance companies have rates based upon the same. And insurance companies, for the most part, can assign rates based upon average accident rates, for identifiable traits.

Like one's sex. Or where they live (a common way to get statistics without 'race/colour').

So what do I mean by the chicken and the egg, here?

Well, imagine that black landowners go bankrupt more often. And sadly, this could be because black landowners go bankrupt more often!

If a specific statistical classification indicates more bankruptcy, then it becomes true. For example, bank $a is bold enough to lend to someone whom they view as, statistically, more likely to fail. Then.. a few years later?

That person needs a fiscal injection. Were that person not black, it would be easier to get funding at a time of need. However, since that person is?

Well, then they get more denials, go bankrupt, and add to the proof that "statistically, more black people go bankrupt". Or as the banks are likely doing it, "the area where people live in".

In other words, unless you can make EVERYONE, 100% not deny based upon an statistical models? Race/gender/sexual orientation/sex/where they live, etc, etc? Anyone, like bank $a lending outside of those models, will be lending to people less able to find additional assistance when/if the time comes.

Chicken and egg. It's not right, but I view this a little bit like certain regulations, where corporations can't compete against other corporations which 'cut corners', so we have to mandate all corps behave in a certain manner to level the playing field.