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

Corinium

APRIL 25, 2019

Ahead of the Chief Data Analytics Officers & Influencers, Insurance event we caught up with Dominic Sartorio, Senior Vice President for Products & Development, Protegrity to discuss how the industry is evolving. I am head of Products here, which comprises of R&D, Product Management and Global Customer support.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

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

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 119

Digital Transformation Strategy Technology Enterprise 119

Cloudera

MARCH 18, 2021

From a data management point of view, FRTB’s requirements will require greatly increased quantities of historical data, along with an increased need for analysis and intensive computation against this data. .

Risk 55

Risk Machine Learning Risk Management Measurement 55

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

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 120

IT Consulting Testing Cost-Benefit 120

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. We used a security scorecard benchmark and said we could become the most secure global mint.”

IT 52

IT Experimentation Scorecard Digital Transformation 52

Jet Global

MARCH 2, 2022

The SFDR aims to give more transparency about sustainability and provide a common set of rules on sustainability risks. In terms of the regulation, asset management, pension funds, and insurers must disclose how they take ESG issues into account in their investment decisions.

Reporting 59

Reporting Recreation/Entertainment Risk Insurance 59

AWS Big Data

AUGUST 14, 2023

Earlier in their lifecycle, data products may be measured by alternative metrics, including adoption (number of consumers) and level of activity (releases, interaction with consumers, and so on). Monitoring and Event Management X X. The following diagram illustrates how value and risk of a data product are driven by its consumers.

Management 81

Management Risk Measurement Optimization 81

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). So there are three unusual books suggested for your reading list. Secondly, because stakeholders.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

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. Value Management or monetization. Risk Management (most likely within context of governance). Product Management. Governance. Architecture.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52