
In the insurance industry - where profit margins vary widely based on catastrophes on the property casualty side and are usually razor thin on t…
Subject to reasonable use.
In the insurance industry - where profit margins vary widely based on catastrophes on the property casualty side and are usually razor thin on t…
Banking is one of the most data-intensive industries, with data woven into every facet of client experience, banking operations, and servicing.…
I recently joined the Celent Corporate Banking Practice, having spent most of my career working at the intersection of business and technology w…
Over the past week, I had the great opportunity to present at two events – Celent’s inaugural Asia webinar series and the Toronto Machine Learni…
In this discussion, Aneesh Chopra,President, CareJourney, who served in the Obama Administration as the first US Chief Technology Officer, chatt…
ESG criteria promotes doing business for good and holds organization accountable for actions that are damaging to the people and planet it aims…
Taiwan Life saw an opportunity to be the first to leverage new digital data from the government’s e-health initiative, using machine learning (M…
The FWD Group Data team developed a smart insurance framework, an AI-everywhere approach that aims to transform the insurance journey by leverag…
What is data management and data lineage and why is it important to have a process for understanding data sources in your organization? How do w…
Breakthrough innovations are occurring in cash management thanks to advances in artificial intelligence and machine learning (AI/ML), connectivi…
The specialized technology that supports risk management functions has traditionally been supplied by internal development teams as well as by e…
Alternate data sources can be a possible way to enhance insurance models and provide greater insights for insurers, leading to the inclusion of…
MLOps is a multi-phase process that leverages the power of large volumes and variety of data, abundant compute on GPU, and open-source machine l…
Historically small business banking has been fraught with trade-offs between lowering cost-to-serve and improving customer experience. As a resu…
Alternative data sources would provide insurers with additional data that complement internal organizational or policyholders’ information. It w…
In the insurance industry - where profit margins vary widely based on catastrophes on the property casualty side and are usually razor thin on t…
Banking is one of the most data-intensive industries, with data woven into every facet of client experience, banking operations, and servicing.…
I recently joined the Celent Corporate Banking Practice, having spent most of my career working at the intersection of business and technology w…
Over the past week, I had the great opportunity to present at two events – Celent’s inaugural Asia webinar series and the Toronto Machine Learni…
In this discussion, Aneesh Chopra,President, CareJourney, who served in the Obama Administration as the first US Chief Technology Officer, chatt…
ESG criteria promotes doing business for good and holds organization accountable for actions that are damaging to the people and planet it aims…
Taiwan Life saw an opportunity to be the first to leverage new digital data from the government’s e-health initiative, using machine learning (M…
The FWD Group Data team developed a smart insurance framework, an AI-everywhere approach that aims to transform the insurance journey by leverag…
What is data management and data lineage and why is it important to have a process for understanding data sources in your organization? How do w…
Breakthrough innovations are occurring in cash management thanks to advances in artificial intelligence and machine learning (AI/ML), connectivi…
The specialized technology that supports risk management functions has traditionally been supplied by internal development teams as well as by e…
Alternate data sources can be a possible way to enhance insurance models and provide greater insights for insurers, leading to the inclusion of…
MLOps is a multi-phase process that leverages the power of large volumes and variety of data, abundant compute on GPU, and open-source machine l…
Historically small business banking has been fraught with trade-offs between lowering cost-to-serve and improving customer experience. As a resu…
Alternative data sources would provide insurers with additional data that complement internal organizational or policyholders’ information. It w…
In the insurance industry - where profit margins vary widely based on catastrophes on the property casualty side and are usually razor thin on t…
Banking is one of the most data-intensive industries, with data woven into every facet of client experience, banking operations, and servicing.…
I recently joined the Celent Corporate Banking Practice, having spent most of my career working at the intersection of business and technology w…
Over the past week, I had the great opportunity to present at two events – Celent’s inaugural Asia webinar series and the Toronto Machine Learni…
In this discussion, Aneesh Chopra,President, CareJourney, who served in the Obama Administration as the first US Chief Technology Officer, chatt…
ESG criteria promotes doing business for good and holds organization accountable for actions that are damaging to the people and planet it aims…
Taiwan Life saw an opportunity to be the first to leverage new digital data from the government’s e-health initiative, using machine learning (M…
The FWD Group Data team developed a smart insurance framework, an AI-everywhere approach that aims to transform the insurance journey by leverag…
What is data management and data lineage and why is it important to have a process for understanding data sources in your organization? How do w…
Breakthrough innovations are occurring in cash management thanks to advances in artificial intelligence and machine learning (AI/ML), connectivi…
The specialized technology that supports risk management functions has traditionally been supplied by internal development teams as well as by e…
Alternate data sources can be a possible way to enhance insurance models and provide greater insights for insurers, leading to the inclusion of…
MLOps is a multi-phase process that leverages the power of large volumes and variety of data, abundant compute on GPU, and open-source machine l…
Historically small business banking has been fraught with trade-offs between lowering cost-to-serve and improving customer experience. As a resu…
Alternative data sources would provide insurers with additional data that complement internal organizational or policyholders’ information. It w…