Lessons from Silicon Valley Bank: Using Analytics to Extract Public XBRL Data and Evaluate Financial Firms

ABSTRACT This case study is built on the collapse of Silicon Valley Bank and requires that students examine and compare financial institutions and assess financial stability. Students are expected to extract public XBRL data, transform that data into informative accounting measures, and load their findings to prepare for evaluation. The case aims to develop students’ data analytic skills and accounting intelligence using open-source software and data. In addition to an examination of accounting measures, students will apply textual analysis to evaluate corporate disclosures. This project provides detailed instructions for the use of Python code to extract the XBRL data from the SEC Edgar database and for the use of Excel and/or Python to develop visualizations that communicate their findings. Data Availability: Data are available from the public sources cited in the text. JEL Classifications: G21; G33; M41.