Limits and Opportunities of Big Data For Macro-Prudential Modeling of Financial Systemic Risk

We explore the use of "big data", i.e. large unstructured data sets, within financial risk analysis. We conclude it has value, but structured data remain critical. We show that forward-looking financial analysis on the systemic level needs a data structure that represents financial contracts as algorithms that produce state contingent cash flows. Currently the industry lacks such a standard, which precludes meaningful systemic forward-looking analysis. We introduce ACTUS as an emerging standard that will enable consistent analysis on all levels. This standard will also create an infrastructure for macro financial analysis.