1. Domain Knowledge: Novice analyst tend to put the data in a blender and see what comes out first instead of building some preliminary knowledge and intuition about the domain. This is quite evident in OP's analysis and finding about annual income. A person familiar with domain will ask the question "Why would a borrower with high annual income will borrow a small amount loan at high interest rate?" This right away will raise flags about risks of lending to such borrowers. OP will benefit by reading some of the publications (books, research) on credit scoring and modeling before deep diving into analyzing Lending Club data.
2. Data Exploration: Not spending enough time exploring the data can lead to erroneous conclusion like The second chance strategy. When did Lending Club start issuing loans to borrowers with delinquencies and public records has a big impact on returns as newer loans are not aged enough to have sufficient defaults.
> Watch for your average return (expected return), consistency of returns through time (risk), while making sure there is enough supply (liquidity) on the platform to deploy your strategy.
Time is not Risk. You need to find a proper measure for risk. Also consider negative kurtosis and frequent low positive returns but a few high negative returns nature of return distribution.
> I considered that investors deploy and re-invest their money continuously on the platform and therefore own a portfolio with different ‘vintages’ of loans. The ROI that are computed reflect this, as they are average returns across vintages.
Re-consider this argument of "average return across vintages" being representative of investor returns. Tip: look at loan volume across vintages as well as typical re-investment pattern of a typical investor.
> Please also note than due to the low issuance volume in the early days of the platform, the returns computed for the pre-2010 period are much less reliable than the post-2010 returns.
Please don't do this. The data between 2006 and 2010 is the most valuable due to the business cycle we were in at that time. The data since 2010 tells nothing about how loans might perform in the future when business cycle is not as good it has been in last few years.
OP will really benefit from re-evaluating his finings with critical eyes. I will suggest gaining some domain knowledge, spending lot of time on just exploring the data before start drawing definite conclusions, focusing on distributions, correlations and statistical significance.