Octopai

JULY 9, 2020

It required banks to develop a data architecture that could support risk-management tools. Not only did the banks need to implement these risk-measurement systems (which depend on metrics arriving from distinct data dictionary tools), they also needed to produce reports documenting their use.

Insurance 86

Insurance Risk Management Machine Learning Metadata 86

Cloudera

MARCH 18, 2021

The Fundamental Review of the Trading Book (FRTB), introduced by the Basel Committee on Banking Supervision (BCBS), will transform how banks measure risk. In order to help make banks more resilient to drastic market changes, it will impose capital requirements that are more closely aligned with the market’s actual risk factors.

Risk 55

Risk Machine Learning Risk Management Measurement 55

CIO Business Intelligence

APRIL 15, 2024

The senior vice president and chief information and strategy officer at National Life Group, has spent years executing a technology roadmap to modernize the insurance company. A smaller number (16% of IT leaders and 11% of LOB) sought out CIO consultation to help evaluate and advise on choices using a risk management or governance lens.

Digital Transformation 127

Digital Transformation Strategy Technology Enterprise 127

AWS Big Data

AUGUST 14, 2023

At the same time, unstructured approaches to data mesh management that don’t have a vision for what types of products should exist and how to ensure they are developed are at high risk of creating the same effect through simple neglect. How do we define “risk” and “value” in the context of data products, and how can we measure this?

Management 81

Management Risk Measurement Optimization 81

Jet Global

APRIL 5, 2021

Financial modeling involves combining key accounting, finance, and business metrics to build an abstract representation, or model, of a company’s financial situation. Risk management. For example, the capital budgeting model that we talk about later in this post will make use of the DCF model for some of its metrics. .

Modeling 98

Modeling Forecasting Metrics Finance 98

CIO Business Intelligence

FEBRUARY 3, 2023

The Queen’s death brings e-commerce innovation Hobbs joined The Royal Mint in January 2020, bringing 20 years of experience from financial services, where he worked for Barclays Bank, Barclaycard, Lloyds Banking Group and Admiral Insurance. An unfortunate by-product was a variety of cyberattacks.

IT 52

IT Experimentation Scorecard Digital Transformation 52

CIO Business Intelligence

MARCH 13, 2024

At Gallagher, a global insurance brokerage, risk management, and consulting services firm, executive search practice managing director Tom Wilson says his team uses gen AI for research and written communications. Artificial Intelligence, CIO, Generative AI, IT Leadership, ROI and Metrics, Software Development

IT 127

IT Consulting Testing Cost-Benefit 127

Jet Global

MARCH 2, 2022

For one, companies that place an emphasis on their environmental and social impacts and responsibilities, have been shown to be more resilient and that they’re able to manage their risks better during a crisis. The SFDR aims to give more transparency about sustainability and provide a common set of rules on sustainability risks.

Reporting 59

Reporting Recreation/Entertainment Risk Insurance 59

IBM Big Data Hub

FEBRUARY 8, 2024

” European Parliament News The EU AI Act in brief The primary focus of the EU AI Act is to strengthen regulatory compliance in the areas of risk management, data protection, quality management systems, transparency, human oversight, accuracy, robustness and cyber security.

Risk Management 76

Risk Management Risk Metrics Machine Learning 76

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). Legal concerns, risk, compliance. So there are three unusual books suggested for your reading list.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

DataRobot Blog

JULY 21, 2022

Data scientists need to understand the business problem and the project scope to assess feasibility, set expectations, define metrics, and design project blueprints. Outline clear metrics to measure success. Document assumptions and risks to develop a risk management strategy. Define project scope.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

Andrew White

JANUARY 11, 2021

As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. Some data is more a risk than valuable. Value Management or monetization. Risk Management (most likely within context of governance). Product Management. Governance.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52