Octopai

JULY 9, 2020

As a core principle of data management, all BI & Analytics teams engage with data lineage at some point to be able to visualize and understand how the data they process moves around throughout the various systems that make up their data environment. A key piece of legislation that emerged from that crisis was BCBS-239.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

Cloudera

FEBRUARY 15, 2024

It’s hard to believe it’s been 15 years since the global financial crisis of 2007/2008. From stringent data protection measures to complex risk management protocols, institutions must not only adapt to regulatory shifts but also proactively anticipate emerging requirements, as well as predict negative outcomes.

Insurance 82

Insurance Data Architecture Risk Management Risk 82

Octopai

JUNE 16, 2021

If you’re a bank, however, taking risks doesn’t just have implications for you, but for all your customers and (if you’re big enough) for the economy as a whole. . Up-to-date data management makes meeting the credit risk and market risk standards much more feasible, and is absolutely necessary for operational risk.

Management 52

Management Risk Management Risk Visualization 52

Octopai

APRIL 8, 2020

The worldwide economy was shaken in 2007 when the United States stock market had its largest drop since the Great Depression. While there are many factors that led to this event, one critical dynamic was the inadequacy of the data architectures supporting banks and their risk management systems.

Finance 52

Finance Cost-Benefit Metadata Data Architecture 52

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. The ability to measure results (risk-reducing evidence). I double-dare you not to visualize that cohort! Frédéric Kaplan, Pierre-Yves Oudeyer (2007).

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66