Predicting Peer-to-Peer Loan Rates Using Bayesian Non-Linear Regression
DOI:
https://doi.org/10.1609/aaai.v29i1.9515Abstract
Peer-to-peer lending is a new highly liquid market for debt, which is rapidly growing in popularity. Here we consider modelling market rates, developing a non-linear Gaussian Process regression method which incorporates both structured data and unstructured text from the loan application. We show that the peer-to-peer market is predictable, and identify a small set of key factors with high predictive power. Our approach outperforms baseline methods for predicting market rates, and generates substantial profit in a trading simulation.
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Published
2015-02-19
How to Cite
Bitvai, Z., & Cohn, T. (2015). Predicting Peer-to-Peer Loan Rates Using Bayesian Non-Linear Regression. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9515
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Section
Main Track: NLP and Machine Learning