The Challenge Our client, an investment bank, often constructs cancellation and claims frequency and severity curves for their clients’ financial products. These curves are critical for predicting future cancellations, claim timing, and severity. However, the process is labor-intensive, requiring significant time and manual effort to build each curve from raw data. Updates are even more […]

Colonnade Advisors, an M&A investment bank, faced a significant data challenge when a client provided customer data in an Excel file and CSV format. The data was disorganized, with customer information spread across multiple rows—sometimes as many as ten per customer. With hundreds of thousands of rows, the fragmented data made it nearly impossible to efficiently manipulate or analyze the dataset.