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7210网络借贷具有高频次、反复借贷的特点，用户往往具有再次借款的需求，利用网络平台累积的各种信息，特别是用户的“行为轨迹”和“社会交往”数据，对平台上具有“再次借款”可能的优质用户进行挖掘，不仅能提高平台的运营效率，也能促使网络借贷市场平稳长远的发展。文章采用XGBoost算法，利用网络借贷平台上2.6万个用户68万多条数据，首创性地建立了用户“是否再次借款”的预测模型，并对用户关键特征进行可视化分析。主要结论为：网络借贷中预测用户是否申请再借款，用户提供的“硬信息”（个人基本信息）已不具有信号揭示作用，用户在平台上的借贷和消费的“行为轨迹”信息以及“社会交往”信息，更具有信任信号的揭示作用。如果在平台上积极维护个人信息、保持良好的还款记录、维持良好网络社交的用户，再次申请借款的可能性就很高。
行为轨迹及社交信息能预测用户是否再借款吗？——基于网络借贷的实证分析
摘要
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引用本文
黄静, 缪世磊. 行为轨迹及社交信息能预测用户是否再借款吗？——基于网络借贷的实证分析[J]. 上海财经大学学报, 2019, 21(2): 93-105.
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