Cloudera

JUNE 29, 2023

To ensure the stability of the US financial system, the implementation of advanced liquidity risk models and stress testing using (MI/AI) could potentially serve as a protective measure. To improve the way they model and manage risk, institutions must modernize their data management and data governance practices.

Data Architecture 84

Data Architecture Risk Management Risk Management 84

Alation

JANUARY 9, 2023

Alation joined with Ortecha , a data management consultancy, to publish a white paper providing insights and guidance to stakeholders and decision-makers charged with implementing or modernising data risk management functions. The Increasing Focus On Data Risk Management.

Risk Management 52

Risk Management Risk Management Metadata 52

Cloudera

MAY 30, 2024

In this context, Cloudera and TAI Solutions have partnered to help financial services customers accelerate their data-driven transformation, improve customer centricity, ensure compliance with regulations, enhance risk management, and drive innovation.

Data Analytics 71

Data Analytics Risk Management Digital Transformation Analytics 71

Cloudera

FEBRUARY 15, 2024

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 86

Insurance Data Architecture Risk Management Risk 86

erwin

JULY 12, 2019

It also helps enterprises put these strategic capabilities into action by: Understanding their business, technology and data architectures and their inter-relationships, aligning them with their goals and defining the people, processes and technologies required to achieve compliance. How erwin Can Help.

Data Governance 110

Data Governance Management Metadata Risk Management 110

erwin

OCTOBER 24, 2019

. • Structuring and deploying data sources – Connect physical metadata to specific data models, business terms, definitions and reusable design standards. Analyzing metadata – Understand how data relates to the business and what attributes it has. Standardize data management processes through a metadata-driven approach.

Metadata 104

Metadata Management Data-driven Data Architecture 104

IBM Big Data Hub

AUGUST 15, 2022

Sometimes as data scientists, we are often so determined to build a perfect model that we can unintentionally include human bias into our models. Often the bias creeps in through training data and then is amplified and embedded in the model. Model risk management.

Data mining 60

Data mining Risk Modeling Risk Management 60