Background & Objectives
Our core product is a robust API that enables our clients to aggregate their financial accounts from a variety of financial institutions. While we have numerous anecdotal evidence from clients that our API is of a higher quality than the leading alternatives, we do not have any quantitative metrics that we can use as evidence.
The primary objective of this analysis would be to establish independent research, which we can point to whenever a prospective client ask, "what makes your API better?"
Some examples of quantifiable statistics we'd love to pull are: average account sync time, update frequency, error rates/availability (for things like tickers, cost basis, expense categorization), length of account history pulled.
The ideal output would be a brief presentation explaining what was discovered as well as the database from which the results have been extrapolated. I.E. if one of the metrics being reported on is the error rates, we should be able to see the raw data from which the error rates were computed.
Because of the technical nature of this project, we will need someone who is familiar with APIs, has some understanding of financial services, and is comfortable handling large amounts of data.