Caserta partnered with a multinational investment bank and financial services company headquartered in Switzerland. As the largest Swiss banking institution, it maintains a presence in all major financial centers around the world. The company provides private banking, wealth management, asset management, and investment banking services for its clients.
At a time when alternative data was in its infancy, it took the investment bank’s analysts three months to ingest the data they wanted to test for a new investment idea. Every time they thought of a new investment idea, they would start screenscraping the data of all their competitors to see how they stood from a pricing perspective. They would then build mechanisms to get that data, adjust that data, put it into a data lake, and do analytics on it. Their manual system would allow analysts to test about 600 ideas a year.
The investment bank wanted a system that would allow them to test at least 1000 ideas a year and called on Caserta to design and build a laboratory that would allow them to take full advantage of alternative data in investment banking.
Caserta designed, architected, and built a data science laboratory that would allow the investment bank to collect, analyze, and assess their new investment ideas. The data science laboratory features a domain-specific language that allows subject matter experts (as opposed to ETL engineers) to design workflows in addition to a lookup system that supports mastering master and reference data as a part of a holistic approach to ETL workflows vs. bolt-on MDM tools.
The data science laboratory architected by Caserta resulted in a 10x increase in data onboarding times, more accurate data, and a rapidly growing collection of governed reference data. Every day, it enables analysts to use large alternative datasets to refine investor questions and support company research.
Today, this industry-leading data science laboratory is the world’s largest sell-side primary research organization and is available for subscription.
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