We've updated our loan performance statistics
Lender guides

We've updated our loan performance statistics

This past week, Lending Works has updated its statistic pages, although unlike our usual monthly updates which are characterised by subtle tweaks and shifts, our latest update includes some new statistics being introduced.

In consultation with the Peer-to-Peer Finance Association (P2PFA), the industry body who set out a robust set of rules and operating principles to which its members must adhere, all P2PFA members have been mandated to make certain changes to comply with what we hope will be a new industry standard, thus allowing consumers to make like-for-like comparisons on loan performance data between peer-to-peer lending platforms.

However, as you have probably come to expect from Lending Works, we’ve gone the extra mile in this respect, and, aside from displaying a greater array of statistics than we are required to, we’ve also delivered a set of graphs which, rather than simply giving you a static number, provide a representation of data over time, thus producing more powerful and easy-to-understand information.

Actual, expected and forecast defaults

The most significant among the changes to our statistics pages is that of the graphs charting actual and expected defaults; with the new orange line representing forecast defaults – essentially our most up-to-date projection of lifetime bad debts based on actual loan performance to date plus expected losses remaining on the loans in the portfolio.

The addition of forecast defaults into the graph is intended as a helpful predictive tool for a customer like you to assess the projected levels of losses anticipated on loans written in a specific year. Unlike the expected defaults, which charts our expectation at the time of loan origination, the forecast takes into consideration the actual level of performance so far and is therefore a much more accurate prediction with which to make an assessment of credit performance. As such, the data behind this orange line is constantly updated – right the way throughout the lifecycle of the loans.

You may also have noted that we no longer include a graph for the current year cohort: this is due to our projected performance being based on 12 months of actual loan performance for each cohort i.e. the loans we’ve written during 2016 haven’t yet matured sufficiently for us to make accurate projections. However, at the start of 2017 (and indeed the corresponding following year for each calendar year thereafter), you will see this data presented graphically in the same way.

Calculating these figures

We follow industry-standard data analysis techniques for updating our projections. Each loan is allocated into one of a number of risk bands, which broadly reflects the borrower’s propensity to pay i.e. how likely we believe it is that they will fully repay their loan. Our data for the performance of loans in each risk band continues to build, and we thus get an increasingly accurate idea of both the rate of default within each and the relative timing of such defaults, therefore allowing us to more accurately predict the lifetime losses to be expected. The calculations are based on 12 months’ performance of loans within each cohort (from loans which were written more than 18 months ago).

You may also note that the fundamental units for the X-axis on these graphs has changed from the previous versions. Previously, we represented the timeline according to the extent to which loans in each cohort had matured i.e. had been repaid. However, the base units for the X-axis are now reflected in months. In doing so, the graph instead contextualises the timing of bad debt throughout the loan lifecycle, rather than being relative to the proportion of loans repaid, which is arguably a more relevant representation given that early repayments could potentially skew things.

Other changes to our statistical reporting

We have also added another new statistic titled ‘Shield utilisation’ (both actual to date and projected), which represents the proportion of the loan contributions into the Shield which have been used to cover any arrears and defaults which arise for loans within this cohort. Remember, we allocate a proportion of our fees on each loan to the Shield’s reserve fund for this purpose. In simple terms, if the figure is below 100 per cent in respect of any given year, it means we have ‘over-reserved’ i.e. payments into the reserve fund for that particular loan cohort are higher than the amounts it has been required to pay out. This allows you to identify whether any particular cohort performed above or below expectations and the extent to which the level of Shield contributions have been adjusted going forward as a result.

The other change we have incorporated into this page is that each row of the two tables now has a ‘Total’ column, which represents a weighted average for each statistic for all loan cohorts since we launched in 2014. This is also a handy means by which you are able to glean a collective, overall picture, factoring in varying loan performance over the different years - rather than only being able to make assessments of each individual year in isolation.

In conclusion

We have embraced the attempts by the P2PFA and its members to ensure a consistent standard of data reporting, which further underlines our commitment to complete transparency and empowering investors like you to make fully-informed decisions about where to invest your hard-earned money. Being able to compare investments on a like-for-like basis is fundamental, and we hope the rest of the industry sees the benefit of adhering to these standards.

We hope that the above gives you a clearer picture, and puts your mind at ease with respect to the changes made to our data reporting. But, as ever, if you have any queries with respect to these revised statistics – or anything else for that matter – our dedicated team is on hand to help.

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Michael Todt

Mike joined Lending Works in early 2015 with a background in marketing and journalism. Having long held a passion for economics, he is now the chief contributor to the Lending Works blog, and regularly writes about all things peer-to-peer lending, fintech and personal finance.