Three Myths Investors Have About P2P Lending

The following article was published on LendAcademy on February 27, 2014, but is considered to be some of the best and most useful advice on LendAcademy. Look no further for your guide to P2P.

by Peter Renton, Founder of Lend Academy, via LendIQ:

It is amazing how many investors make their investment decisions based on so-called common sense. They “know” that small loans are a better investment or that you want a borrower with a low revolving balance on their credit cards. Because obviously this will lead to better returns. Really?

I prefer to look at the data history and use that as my guide. We can all have a hunch about something but hunches are often wrong. Today I am going to dispel several myths that I see repeated by bloggers and new investors on a regular basis. Here are three investment criteria that common sense suggests would lead to higher returns but that the history of both Lending Club and Prosper prove to be different.

To test my theories here I looked at all loan data on Lendstats from loans originating in 2009 and 2010 at both companies. These loans are all past their peak default period and have an average age of around 21 months.

1. Small Loan Sizes Are Best

This is one of the most common myths I see. Investors filter loans based on the loan size with the thinking that a smaller loan means a more manageable payment and therefore a lower likelihood of default. Now, what makes a small loan is subjective so I just chose the approximate median loan size to analyze roughly equal segments of loans.

Lending Club Loan Size: Less than $10,000 –> ROI: 5.13% Lending Club Loan Size: $10,000+ –> ROI 5.79% Prosper Loan Size: Less than $5,000 –> ROI: 4.22% Prosper Loan Size: $5,000+ –> ROI: 6.09%

At Lending Club the median loan during the period analyzed is right around $10,000. So, taking all loans of $1,000 — $9,999 generates an estimated ROI across all loan grades of 5.13% and loans of $10,000 or more have an ROI of 5.79%. This is before Lending Club increased the maximum loan size from $25,000 to $35,000 so all these loans are for $25,000 or less.

At Prosper this analysis is a little more complex simply because Prosper limits the loan amount borrowers can apply for based on loan grade. In order to try and compare apples to apples I just looked at loan grades AA and A because these borrowers can borrow any amount up to $25,000 the same as at Lending Club. Here the median loan size was around $5,000 but the same trend is seen. Loans below $5,000 returned an estimated ROI of 4.22% and loans of $5,000 or more returned 6.09% — a marked difference.

2. Choose borrowers with low revolving credit

One would expect that borrowers that have very little revolving credit would be the best kind of borrower to have. But one would be mistaken. First we should define revolving credit — basically we are talking about credit card balances here, specifically the total balance owing on all credit cards. The credit card companies report this data monthly to the credit bureaus and your credit report is updated.

Lending Club Revolving Credit: Less than $8,500 –> ROI: 4.89% Lending Club Revolving Credit: $8,500+ –> ROI 6.17% Prosper Revolving Credit: Less than $7,000 –> ROI 8.61% Prosper Revolving Credit: $7,000+ –> ROI 9.75%

At Lending Club the median revolving credit amount is around $8,500. So we take half the loans that have revolving credit of less than $8,500 and we get an estimated ROI of 4.89%. For $8,500 and above the ROI is 6.17% — a significantly higher number.

At Prosper the median amount for revolving credit is around $7,000. For loans below $7,000 the estimated ROI is 8.61% and for $7,000 and above it is 9.75% a similar large difference.

Again we see data that goes against common sense. Borrowers with more debt perform better than borrowers with little debt. Michael from Nickel Steamroller has just published an excellent analysis of revolving credit at Lending Club and provides much more information about this one filter.

3. Low Debt-to-income ratio is better

Debt-to-income is a ratio that expresses the percentage of a person’s income that goes towards paying debts. For p2p lending purposes both Lending Club and Prosper do not include any mortgage debt in the debt to income ratio. Lending Club has rules around debt to income — if your credit score is below 720 the maximum debt to income ratio you can have is 25%, for scores of 720 or more that increases to 30%. Prosper has no publicly available rules like that but we know they do take it into consideration when doing their underwriting.

One important point I should note about debt to income. Not all borrowers are verified for income so this ratio may not reflect a borrowers real income in all cases. Having said that, the numbers are still useful, particularly reflective of what they don’t show.

Lending Club Debt to Income: Less than 13% –> ROI: 5.59% Lending Club Debt to Income: 13%+ –> ROI: 5.75% Prosper Debt to Income: Less than 18% –> ROI: 9.08% Prosper Debt to Income: 18%+ –> ROI: 9.42%

At Lending Club the median DTI ratio is around 13% and at Prosper it is 18%. This is expected because Prosper allows a higher risk borrower on to their platform than Lending Club (with corresponding higher interest rates). Still you would have expected that a higher debt to income ratio would lead to a lower ROI for investors. But we see in the table above that is not the case. Now, these numbers are close so I am not going to categorically state that a higher DTI ratio is better but we can say that lower DTI doesn’t necessarily lead to higher returns.

There are other examples where common sense is not rewarded. Do some analysis on credit score or even length of employment (only available at Lending Club) and you will be surprised that what you expected to be true is not reflected in the data.

The Key Takeaway

The important lesson here is this. Don’t rely on what you think should be correct when investing. There is enough loan history for investors to see what has and hasn’t worked in the past. I think investors should base their investment decisions on data and not on a hunch that may or may not be true.

What do you think? Do you still use criteria that you think should lead to higher returns or do you look closely at the data? As always I am interested to hear your comments.

Originally published at on January 30, 2015.

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