Harmoney

[myles]

A couple of charts that are an attempt to find loans that are more likely to default than others. These are based on my loan set so may differ from others and some of my criteria may limit some details showing up.

The number in the brackets after the description is the sample size for that group.

Attachment 9976

Nice data-set that highlights that some borrower cohorts appear to be more likely to default than others. I find it interesting that a De Facto relationship is lowest in that group. I haven't taken a loan from a 'boarder' for a long time, but some of my earlier loans were. Most other details are kind of what you would expect I think. The 'Home' income type stands out from the rest (still not 100% sure what it is defined as).

Attachment 9977

There was some discussion a long way back suggesting borrowers location might influence defaults - this chart certainly suggests that might be the case. Note I split out the smaller sample size regions just for clarity. Other regions, for me, have not had a default.

Hope there are some details here that are useful to others for 'picking' loans.

Just as an example, so it's clear what these are showing - I have had (or still have) 14 loans from borrowers residing in Timaru, just under 15% of those loans have defaulted (so that would be 2 out of the 14). [The 14 is in the brackets after 'Timaru'.]