Data-Driven Investment Strategies for Peer-to-Peer Lending: A Case Study for Teaching Data Science

Abstract

We develop a number of data-driven investment strategies that demonstrate how machine learning and data analytics can be used to guide investments in peer-to-peer loans. We detail the process starting with the acquisition of (real) data from a peer-to-peer lending platform all the way to the development and evaluation of investment strategies based on a variety of approaches. We focus heavily on how to apply and evaluate the data science methods, and resulting strategies, in a real-world business setting. The material presented in this article can be used by instructors who teach data science courses, at the undergraduate or graduate levels. Importantly, we go beyond just evaluating predictive performance of models, to assess how well the strategies would actually perform, using real, publicly available data. Our treatment is comprehensive and ranges from qualitative to technical, but is also modular—which gives instructors the flexibility to focus on specific parts of the case, depending on the topics they want to cover. The learning concepts include the following: data cleaning and ingestion, classification/probability estimation modeling, regression modeling, analytical engineering, calibration curves, data leakage, evaluation of model performance, basic portfolio optimization, evaluation of investment strategies, and using Python for data science.

[Retracted] Construction of Smart Higher Education Teaching Resources Using Data Analysis Technology in Unbalanced Data Environment

“…Big data, in the opinion of Bachelor, will fundamentally alter modern education in various ways [ 14 ]. Big databased learning analysis, according to Cohen et al, can be used to both evaluate courses and teachers and identify and understand the workings of the learning process [ 15 ]. Big data technology, according to Dai, has the potential to digitize the entire educational process for kids.…”

Industry 4.0-based enterprise information system for P2P lending

“…Thus, the underlying design of the digital platform plays a critical role in various ways (Wang et al , 2015). There are many stakeholders in P2P lending and each of these stakeholder need wide variety of information and resources (Cohen et al , 2018). For instance, borrowers will need a web-based digital application that they can use to specify the amount needed and submit personal and financial credentials.…”

“…To be able to sustain, financial institutions again depend on information on what type of loans may lead to defaulting and related circumstances. However, these activities are only a few of several other processes and above all the processes are data-driven and operations are data-intense (Henriquez et al , 2018; Cohen et al , 2018).…”