Reshaping the landscape of bank monitoring and risk disclosures

该项目将开发一种基于机器学习的创新方法，用于衡量、监测和评估银行贷款活动和风险披露，以利用现有的大数据。它将使用多维数据为评估银行风险和风险披露质量提供更相关的指标，并将其应用于监管政策评估。该项目的研究结果将大大提高人们对减轻银行不当行为的认识。它们还将为监管当局提供有效的监测工具和预警装置，以促进更好的贷款和风险披露做法，并建立一个更加透明和稳定的金融体系，以支持澳大利亚和全球的金融中介。

The project will develop an innovative machine-learning-based approach for measuring, monitoring and evaluating bank lending activities and risk disclosures to take advantage of the big data available. It will use multidimensional data to produce more relevant metrics for assessing bank risks and risk disclosure quality and apply them in regulatory policy evaluation. The project findings will significantly advance the knowledge on mitigating banking misconduct. They will also equip regulatory authorities with an efficient monitoring tool and an early-warning device to promote better lending and risk disclosure practices, and foster a more transparent and stable financial system to support financial intermediation in Australia and worldwide.