We collaborate with a leading Chinese FinTech lending company, to conduct a randomized controlled trial (RCT) to test for information asymmetry in the FinTech consumer credit market. In the experiment, we plan to manipulate three contract terms: interest rate, loan amount, and time to maturity, and offer randomized contracts to loan applicants. We then observe the impact of various treatments (contracts) on: (1) contract acceptance rate by borrowers, (2) loan default rate among the executed loans, (3) gross and net IRR of the loan. We hypothesize that among the pool of borrowers that share the same level of credit score, those who accept less favorable contract terms (e.g. higher interest rate, lower loan amount, and shorter time to maturity) tend to have higher unobservable credit risk, and have higher default rate that cannot be fully explained by credit score. Further, we hypothesize that there may exist a group of borrowers for whom none of the offered contracts can result in profitable lending (on average) because of the adverse selection problem.