We can say people who earn less than this amount to who or who live in this town have a higher probability than other people interestingly enough because people tend to to categorize people when they define and credit risk this categorizing has had some unfortunate social consequences one thing with categorizing is that it has led to discrimination one particular form of discrimination happen in America where what they did is they said because like I said it’s impossible to calculate the probability of an individual they created groups and they said groups have certain credit risk and one of the groups was they said that African Americans had a higher credit risk and therefore need to be charged a higher interest

You could go and you could have the exact same salary the same degree the same everything but because of the color of your skin or your ethnicity the financial banks would say sorry you have to charge we’re going to charge you much higher interest or we’re not going to learn lend you any money because of your ethnicity and this had massive social concert consequences because it means this group of people couldn’t buy houses couldn’t start growing economically and if they put them at quite a big disadvantage

That’s why this probability thing here it I mean some sort of discrimination is good people with low salaries might not be able to repay as people with high salaries you know maybe that’s a much better measure I know today’s rules in a lot of countries say you are not allowed to discriminate based on skin color or ethnicity despite whatever your data says because your data might have been flawed specifically say in the USA there might have been a ghost factor or a hidden variable that the models weren’t picking up so that is a little bit of a dark side of credit risks that has happened look I don’t think it happens too much today but it was happening a lot in in the past I’m not 100% certain when exactly but I know it was sometime in like the nineteen

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