“The past is a different country, they do things differently there”
Regular readers of this blog will have realised that I care about how we interact with banks and insurance companies (and supermarkets and other big corporations for that matter). Way back when, before decisions were taken using computer models, if someone wanted a loan they went to see their local bank manager. The bank manager made a decision based largely on his view (it usually was a man) of whether the loan would get paid back. If the bank manager said “no”, then it was possible to ask him, face to face, why he had said “no”.
It wasn’t a perfect system. Bank managers made mistakes, and there must have been many situations when prejudices came into play, both positive and negative.
In insurance, people grouped together to share their risks. “Mutual insurance”. Someone came round each week to collect premiums from people’s houses. There was face to face contact and the opportunity to ask questions. How much you paid in premiums was more a factor of how much you wanted to insure, than how risky you were.
Again, not perfect. Low risk, careful people subsidised the careless people.
Computer says “no”
Now, in most banks and insurers, decisions about lending to consumers and insuring them are made by computer model. There is less decision-making by individuals. That is not necessarily a bad thing. Computer models don’t have prejudices. But neither can they make use of their real world experience from a long career. And neither can they explain to a customer why their loan application has been rejected. Banks understand this, and have advisers to explain why an application has been turned down. But the computer models are very large and very complicated, and the adviser won’t know exactly how they work, or all the inputs that are used to make the loan decision. So the adviser will only be able to try to interpret the decision, not explain it.
Does this matter? Yes, because the person who wants a loan may not understand what they need to change to get one. It is easy to say “get a bigger deposit” and that probably is one answer for most mortgage applications. But there may be other options too.
Too many chocolate eggs in one go…
When it is the computer that says no, not a person, then it is easier for people to think it is OK to give the computer wrong information. Perhaps it feels like a victimless crime. So there are stories of mortgage brokers who will change the details in applications forms (perhaps entering a year of birth as 1984 not 1948) because they know that will get a positive result from the computer model.
But that is fraud. Not only that, it may well be a bad result for the person seeking a loan. Maybe there is a good reason that they were refused a loan. Maybe they won’t be able to pay it back. Lending to people who won’t be able to repay, and who will end up in financial difficulties, is a bad thing.
And application fraud is totally unacceptable. It is illegal, it makes assessment more difficult for banks and insurers, and it costs us all money because financial products become more expensive.
What do I want to change?
Insurers use computer models to assess how risky their customers are, in similar ways to banks. I am not advocating that they should turn the clock back and abandon that method. Being able to provide insurance very quickly to many thousands of customers helps everyone in this country, insured or uninsured, and is incredibly positive for society.
But I would like insurers to explain clearly to us, as individuals, how they make their decisions when they give us individual prices for our insurance policies. In language that we can all understand.
PolicyCastle helps our members understand
At PolicyCastle, we help our members understand how insurers assess them, so our members can change their risk level. This helps members get a lower cost insurance policy, but more importantly it helps them reduce the risk of accidents or damage to them and their property. We are totally against application form fraud, and support the insurance industry’s efforts to prevent it.
We want to rebuild trust between the insurers and our members, for everyone’s benefit.