AI Articles and Analysis about Text analysis

Content analysis is a wide and heterogeneous set of manual or computer-assisted techniques for contextualized interpretations of documents produced by communication processes in the strict sense of that phrase (any kind of text, written, iconic, multimedia, etc.) or signification processes (traces and artifacts), having as ultimate goal the production of valid and trustworthy inferences.

Driving AI Adoption
in Insurance-1-min

Driving AI Adoption in Insurance – with Ryann Foelker of American Family Insurance Group

As a rule, AI adoption tends to take more time for legacy industries compared to digitally-native sectors. As a profile from June 2021 in Harvard Business Review explains, insurance companies are data-rich but have long relied on actuarial approaches to data and analytics.  The insurance industry has several concerns regarding the integration of AI. Insurance companies obviously have regulatory compliance as a top priority, so any AI solution implemented needs to comply with existing regulations regarding consumer protection and data security, among others. 

Claims and Underwriting Trends in Personalized Insurance with AI – v.1-1

Claims and Underwriting Trends in Personalized Insurance with AI – with Kelly Cusick and Michael Cline of Deloitte

This interview analysis is sponsored by Deloitte and was written, edited, and published in alignment with our Emerj sponsored content guidelines. Learn more about our thought leadership and content creation services on our Emerj Media Services page.

Artificial Intelligence at IQVIA@1x-min

Artificial Intelligence at IQVIA

IQVIA is a Fortune 500 health information technology (HIT) and clinical research company that provides advanced analytics, technology solutions, and clinical research services for various healthcare stakeholders. 

AI Communications Surveillance-1x min

AI for Communications Surveillance and Compliance – Two Use Cases

Communications surveillance in financial services involves both monitoring and analyzing electronic communications within a financial institution to prevent fraud, ensure regulatory compliance, identify and manage risks resulting from inappropriate activity, and maintain integrity in financial markets. 

Future of Drug Targeting – Lilly @2x-1-min

The Future of Drug Targeting and Clinical Development with Generative AI Tools – with Ramesh Durvasula of Eli Lilly

Lily is a pharmaceutical giant with a legacy dating back to its founding in 1876 by Colonel Eli Lilly. The company engages more than 9600 employees in research and development, with clinical research conducted in more than 55 countries. As of 2022, the company clocked a revenue of $28,541.4 million and made a net income of $6,244.8 million. 

AI at Morgan Stanley@2x-min

Artificial Intelligence at Morgan Stanley – Three Use Cases

Morgan Stanley was founded in 1935 and is headquartered in New York City. They are an American multinational investment bank and financial services company recognized as a leader in wealth management. With over $1.19 billion in assets, Morgan Stanley is among the top 15 biggest banks in the world.

OECD-Approved AI Tools and Resources for Financial Services@2x

OECD-Approved AI Tools and Resources for Financial Services

The OECD.AI Policy Observatory is an inclusive platform that brings together resources and expertise from the OECD and its partners to facilitate dialogue and provide evidence-based policy analysis on the impact of AI. It is built upon the foundation of the OECD AI Principles, the first intergovernmental standard on AI adopted in 2019, endorsed by OECD countries and partner economies.

Managing Model Development@2x-1-min

The Value of Topic Search in Detecting Signals with ROI – with Ben Webster of NLP Logix

In the era of big data, companies need help navigating through an overwhelming volume of unstructured data to uncover meaningful insights. The topic search process presents unique challenges in deciphering data signals and identifying critical information before problems escalate.

Text analysis

Content analysis is a wide and heterogeneous set of manual or computer-assisted techniques for contextualized interpretations of documents produced by communication processes in the strict sense of that phrase (any kind of text, written, iconic, multimedia, etc.) or signification processes (traces and artifacts), having as ultimate goal the production of valid and trustworthy inferences.