AWS Big Data

FEBRUARY 1, 2024

The following are some of the key business use cases that highlight this need: Trade reporting – Since the global financial crisis of 2007–2008, regulators have increased their demands and scrutiny on regulatory reporting. You can run a direct query from QuickSight for BI reporting and dashboards.

Data Warehouse 131

Data Warehouse Dashboards Risk Management Risk 131

Octopai

JULY 9, 2020

Actually, effective data lineage delivers important enhancements to BI and enables informed decision-making , as it enables data teams to tackle numerous use cases such as regulatory compliance, system upgrades & migrations, M&A (system consolidation), reporting inaccuracies, business changes etc.

Insurance 98

Insurance Risk Management Machine Learning Metadata 98

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 88

Insurance Data Architecture Risk Management Risk 88

CIO Business Intelligence

APRIL 28, 2022

auxmoney began as a peer-to-peer lender in 2007, with the mission of improving access to credit and promoting financial inclusion. Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. The Solution for Scale and Speed Lies in the Cloud .

Analytics 98

Analytics Insurance Big Data Uncertainty 98

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. Download the Whitepaper.

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). Frédéric Kaplan, Pierre-Yves Oudeyer (2007). Large-Scale Study of Curiosity-Driven Learning”.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66