How Does a Firm Adapt in a Changing World? The Case of Prosper Marketplace

63 Pages Posted: 26 Jun 2019 Last revised: 2 Jan 2021

See all articles by Xinlong Li

Xinlong Li

Nanyang Business School, Nanyang Technological University

Andrew T. Ching

Johns Hopkins University - Carey Business School

Date Written: December 31, 2020

Abstract

In a rapidly changing world, older data is not as informative as the most recent data. This is known as the concept drift problem in statistics and machine learning. How does a firm adapt in such an environment? To address this research question, we propose a generalized revealed preference approach. We argue that by observing a firm’s choices, we can uncover the way the firm uses the past data to make business decisions. We apply this approach to study how Prosper Marketplace, an online P2P lending platform, adapts in order to address the concept drift problem. More specifically, we develop a two-sided market model, where Prosper uses the past data and machine learning techniques to assess borrowers' and lenders' preferences, and then classify their loans by risk ratings and set their interest rates accordingly to maximize her expected profit. By observing Prosper's choices over time, we find evidence that Prosper likely assigns different weights to past data points depending on how close the economic environments that generate the data are to the current economic environment. In the counterfactual, we demonstrate that Prosper may not be using the past data optimally, and it could improve its revenue by 9.02% if it uses the Ensemble Hidden Markov model proposed in our study.

Keywords: Peer-to-peer Lending, Two-sided Market, Concept Drift, Machine Learning, Structural Model, Fintech

JEL Classification: C33, C35, C38, C53, C55, D12, D14, D22, G21

Suggested Citation

Li, Xinlong and Ching, Andrew T., How Does a Firm Adapt in a Changing World? The Case of Prosper Marketplace (December 31, 2020). Available at SSRN: https://ssrn.com/abstract=3403404 or http://dx.doi.org/10.2139/ssrn.3403404

Xinlong Li

Nanyang Business School, Nanyang Technological University ( email )

Singapore, 639798
Singapore

Andrew T. Ching (Contact Author)

Johns Hopkins University - Carey Business School ( email )

100 International Drive
Baltimore, MD 21202
United States

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