Harmoney

[myles]

Time Lapse of the unique.csv loans. I may be able to back calculate the last payment date from the interest earned on those ~400 'Debt Sold' loans, which might let me generate a hazard curve. Will have a look later, but I'm hopeful...

[myles]

One thing I've not noticed before is that the early loans ~ pre mid 2017 were being paid off earlier - around week 20, while ~post mid 2017 loans are being paid off at around 30-35 week mark. Could be something to do with scorecard changes or borrower selection or even a shift in grade selection by lenders. Just interesting...

[Saffer]

The IRD had a discussion with Harmoney to determine if charged off principal is in fact a bad debt or a provisional bad debt. The IRD has now responded that it is a bad debt and can be written off against income if you are in the business of dealing in financial arrangements. Hope this is of help to any one.

[myles]

Fixed the time lapse for those 'Debt Sold' loans with overwritten last payment date. Much better appreciation for where the defaults occur now.

Turns out it's a very easy calculation to update the last payment date by adding [payments to date / (invested / loan total * monthly loan payment)] months to the start date - this is for loans with a status of 'Debt Sold' and a last payment date = '2018-02-08' (just short of 400 loans).

[beacon]

Attachment 10079

This loan tells us that when the borrower moved into the new home (presumably with a new mortgage) s/he had a large Harmoney loan in place already committing near to 20% of after tax income. I have difficulty accepting that the bank knew about it as the total expense to income ratio would have been unacceptable. Why didn't s/he use the bank to refinance Harmoney. The loan will fill reasonably quickly even though it doesn't make sense to rate this B1.

While I don't deny there is value in understanding more about the greater harmony portfolio, keeping loans like this out of one's own is the first step to reducing defaults.

Goes to show that the programmed data mining is still a poor substitute for experience, but in the absence of the latter, the former is indispensable. Thanks BJ1. Brilliant insight

[beacon]

I was looking at this one too but what caught my eye was actually the level of income on a benefit , By my calculations to get that level of after tax income would require a yearly before tax income of around $78,000. Are we really paying benefits that high? no wonder i pay so much tax (or is harmoney income data wrong again?)

That is equivalent of 1 person working full time for $37.50/hour or 2 people working full time at $18.75/hour or 91 hours of work/ week at minimum wage

Apparently benefit rises with the number of kids a young family has. And with other add-ons, like Accomodation Supplement for the city they live in etc. Sadly, for some, making babies can be more lucrative than getting a job

[beacon]

How useful/useless is this mapping of 2nd level loan criteria?

This cross tabulation is brilliant, Myles. A bivariate analysis is much more useful than segregated filtration in a multivariate environment. At the very least, it proves again that risk falls with age, until you hit 60.

I found it interesting that Boarders remained risky in most situations, but risk for those living with parents seems to be mitigated in certain situations like if they were 50-59 or divorced. Thank you for producing and sharing this.

[beacon]

Further to Myles efforts, couldn't resist doing a multivariate model. comparing two loan sets:
1. Debt to income < 20%, enquiries 3 or less, time in job of 3 or more years, exclude new vehicle - new boat - tax - wedding expense - other loan purpose, exclude lendors aged over 60, exclude loans having 2 or more defaults, exclude partial PP, exclude B and C grade who aren't homeowners, exclude all A and all F grades.
2. loans that don't match the above criteria

...

The results show that the model selection produced an average default of 3.6%, while the control had average default of 7.5%. Grade results, showed defaults were approx half in BCD, while E was only slightly improved compared to the control.

Brilliant work leesal. Thanks for proving again, that loan picking ISN'T simply happening for love, and so, ISN'T a sheer waste of time.

Am now applying two default sets of criteria for loan selection - A default minimiser and the another that takes stable loans less likely to early repay. Both generate a return 3% higher then the data.

I'm assuming 1. is your default minimiser. That is an awful lot of filters, overridden by top level elimination/modification of filtered loans. Be interesting to know, what criteria you chose for your second default set.

I wonder if the 25,000 loans the data set is missing is causing some selection bias.

There is bound to be selection bias, since only 17 or so investors contributed to the data pool, versus the 8,800 odd investors Harmoney has on its books today. Hence the disclaimers Myles has put in the report. Still, we got input from loan pickers and index buyers to some extent, and I'm not holding my breath that Harmoney will (ever) publish default info by individual variables for its whole dataset. So, we've got the next best thing.

What I find interesting also, is that Myles' efforts at cleaning and reporting data put Harmoney's output-to-date to shame. Four years, and they still have the type of data errors humvee recently reported. They also lack in investor education and communication, especially in the area of protect loans. But overwriting/hiding rewritten status/info of defaulting loans, I find absolutely appalling and unforgivably misleading, bordering on fraud. I hope they desist and rectify the wrong they have done - as it impacts on investment decision making.

[beacon]

The IRD had a discussion with Harmoney to determine if charged off principal is in fact a bad debt or a provisional bad debt. The IRD has now responded that it is a bad debt and can be written off against income if you are in the business of dealing in financial arrangements. Hope this is of help to any one.

Thanks Saffer. Be useful if you can provide an external link/reference, if possible, to this IRD confirmation.

[Saffer]

This was a telephone confirmation and I will ask for this to be put in writing.