Harmoney prides itself on being open and transparent about our marketplace performance. All information on this page is accurate up to 22nd August, 2016.
You can view your personal statistics in your Lender Dashboard.
Harmoney prides itself on being open and transparent about our marketplace performance. Automated graphs are updated regularly, all information on this page is accurate up to 20th Feb, 2017.
You can view your personal statistics in your Lender Dashboard.
Overall performance to date
Volume over time
Since launching in September 2014, Harmoney has continued to show steady and consistent growth in terms of the number of loans, and the amount of money lent through the Harmoney Marketplace. You can observe the seasonality of loan demand represented by sharp inclines during the months leading up to Christmas.
This graph shows both Loan Volume ($) on the left axis, and Loan Count (N) on the right axis, over time.
Realised Annual Return
Realised Annual Return (RAR) is a measure of the actual rate of return on funds invested on the Harmoney Platform. As RAR is based on historic performance that may not be a good indicator of future returns.In simple terms, RAR takes the income from lending (interest) and deducts the costs you have incurred (credit losses and fees) to provide the net return. The net return is then annualised and divided by the daily principal outstanding to provide your Realised Annual Return.
This graph shows the average RAR split out for Retail Lenders and Wholesale Lender, as well as total platform average.
Realised Annual Return by Unique Loans
The return of each individual Lender also depends on their diversification within their personal portfolio. This graph shows that 100% of Lenders who have invested in 100 or more personal loans have all returned a positive RAR. You can also see that once you have invested in 200 or more personal loans, the volatility of the RAR reduces significantly. Click here to learn more about Diversification.
Interest paid to Lenders
This graph shows the cumulative total of interest paid to Harmoney Lenders over time.
As more loans are funded through the Harmoney Marketplace, interest returned will continue to grow.
This graph shows the daily amount of volume that was funded via Auto-Lend.
Loans go through the Auto-Lend engine before they hit the Marketplaceup to the Auto-Lend allocation limit. This limit is currently set at maximum of 20% of the notes in a loan. This leaves 80% for manual orders. This ratio does change as Harmoney actively manages the marketplace.
Loan and Marketplace Performance by Grade
Loan Performance by Grade
This chart exemplifies the effectiveness of the Harmoney credit grade in ranking borrower risk. It is expected that higher grades will go into arrears less than lower grades. That expectation is realised in performance here.
Arrears by Credit Grade
Looking at the loan performance by grade in more detail (demonstrating further that the Harmoney credit grade ranks risk effectively) we see not only that the lower the grade the greater the proportion of arrears but also the greater the severity of the arrears, i.e. Grade F has more loans at >120 days than Grade E and Grade E more than Grade D, and so on. This gives us greater confidence in grading as it operates in our current processes.
Distribution of loans by Grade
This graph has been updated to show only the distribution of grades for the current month. If you would like to see the distribution of previous months you can still view that graph here.
What we see in this graph is that A & B grades make up almost 55% of the total volume (dollars) while only 40% of the total loans. By comparison, in the higher risk grades (E & F) we see a higher percentage of loans but a lower percentage of the volume. This is expected as the higher risk grades (E & F) can not borrow as much as the lower risk grades, which means proportionally there will be more loans as compared to the total volume. The converse is true of the lower risk grades, who can borrow more, so we typically see a higher proportion of volume from a lower proportion of individual loans.
Defaults (static loss)
This chart illustrates the actual loss rates experienced. Each year is broken into quarterly groups - or cohorts - with the exception of 2014 where we have combined Q3 and Q4. The combination of 2014 Q3 & Q4 is due to the low level of volume in the first months of operation.
One of the factors affecting the loss in each cohort is the risk grade mix. In the first month of operation, for example, Harmoney originated no A grade loans. By looking at the two graphs together you can get a better understanding of the population stability in each cohort. You can see each risk grade's estimated default rate here.
As these cohorts mature, we will see a flattening out of the losses as represented in our forecast Hazard Curve. We expect that around 80% of the defaults will occur by around 18 months, which means 36-months and 60-month loans will have a similar default hazard rate.
Repeat Borrowers (Rewrites)
Proportion of repeat Borrowers (Rewrites) by Grade
How to read this graph: Of all the volume (dollars) rewritten to date, 37.21% of it went to Grade A Borrowers, 25.66% went to Grade B Borrowers etc.
Repeat Borrowing is made possible by customers having sufficient limit available to them from which to draw a higher amount. It makes sense that higher grades with higher limits have greater opportunity to repeat borrow. A good Harmoney repayment history is a critical factor in being eligible to repeat borrow. Both of these factors contribute to the distribution of grades that have re-written their loans. This reinforces the value of repeat customers in reducing the overall credit risk in the portfolio.
Proportion of rewritten volume (dollars) by month
This graph illustrates the proportion of volume originated each month that was re-written, vs the proportion of volume that was new lending.
This graph shows a breakdown of the Harmoney loan portfolio by purpose for borrowing.
Debt consolidation is a large proportion of loan outcomes, however in a number of cases these loans will also include a portion of the loan funds going to the borrower for an additional purpose; debt consolidation was a means by which this could be achieved (by lowering the current repayment amount of credit to free up income for that additional purpose).
The spread of other purposes is varied and a positive thing for spreading portfolio risk.
Borrower by Region
This graph shows the proportion of the loan book broken down by borrower residence.
The Harmoney loan book has a strong representation from the Auckland, Wellington and Canterbury regions, which might be reasonably expected. There is no significant risk to portfolio from any acute concentration of risk in any one geographical region.
This graph shows the proportion of the loan book broken down by Borrowers' employment status.
It shows that the vast majority of Borrowers are skilled workers, reinforcing that we have a prime book of Borrowers.
This graph shows the proportion of the loan book broken down by Borrowers' residential status.
Almost 50% of Borrowers are homeowners (by loan count) which translates into over $165m by loan volume. The bulk of homeowners fall in the lower risk grades (A - C) with the higher risk grades often being renters and boarders.
This graph shows the proportion of the loan book broken down by Borrowers' marital status.
75% of the money lent has gone to Borrowers who are either married, or in a de facto relationship. Again it tends to be lower risk grades (A - C) that tend to have a higher proportion of married Borrowers.
This graph shows the proportion of the loan book broken down by Borrowers' age.
The average age of a Borrower is around 43 years old - slightly higher than the average age of a Lender.
Borrowers by Gender
This graph shows the proportion of the loan book broken down by grade and Borrowers' gender.
Overall the portfolio split is 45% women and 55% men - however as the chart shows the divergence from 50:50 becomes more pronounced in the higher risk grades.
Retail VS Institutional Funding
On average, 25% of loans have been funded by Retail (mum and dad) Lenders and 75% are funded by institutions.
The mix of retail and institutional Lenders has enabled us to scale, and continue our growth.