AI Articles and Analysis about Recommendations

Recommender systems or recommendation systems (sometimes replacing \"system\" with a synonym such as platform or engine) are a subclass of information filtering system that seek to predict the \"rating\" or \"preference\" that a user would give to an item.

Claims and Underwriting Trends in Personalized Insurance with AI – v.1-1
Business intelligence and analytics
Finance
Case management
Financial services
Claim management
Insurance
Claim management
Marketing
Compliance
Media
Customer analytics
Customer experience
Data analysis
Data auditing
Data collection
Data integration
Data management
E-commerce
Enterprise resource planning
Generative AI
Intelligent assistant
Investment
model development
Recommendations
Search engine
Search engine
Social network analysis
Text analysis
Utilization management

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.
02 – Streamlining Data-Driven Decision-Making in Customer Experiences
for Financial Services@1x-min
Business intelligence and analytics
Finance
Case management
Financial services
Claim management
Insurance
Claim management
Marketing
Compliance
Media
Customer analytics
Customer experience
Customer service
Data analysis
E-commerce
Enterprise resource planning
Generative AI
Intelligent assistant
Investment
Large Language Models
model development
Recommendations
Report generation
Risk management

Streamlining Data-Driven Decision-Making in Customer Experiences for Financial Services – with Ciprian Porutiu of Marsh McLennan and Mike Borrelli of Uniphore

This interview analysis is sponsored by Uniphore 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.
01 – Confronting Unique Challenges in Retail and eCommerce Fraud@1x-min
Business intelligence and analytics
Consumer goods
Case management
Entertainment
Customer analytics
Finance
Customer analytics
Financial services
Customer service
Gaming
Cybersecurity
Retail
Data analysis
Data auditing
Data collection
Data integration
Data management
E-commerce
Fraud protection
Fraud protection
Generative AI
Identity theft
Insider threats
Large Language Models
Machine learning infrastructure
Market segmentation
Marketing and advertising
Predictive analytics and forecasting
Recommendations
Research and development
Security

Confronting Unique Challenges in Retail and eCommerce Fraud – with Leaders from Amazon, PayPal, FanDuel, and Riskified

This interview analysis is sponsored by Riskified 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.
AI at Cigna@2x-min
Business intelligence and analytics
Customer analytics
Customer experience
Customer service
Data analysis
Data collection
Data integration
Data management
E-commerce
Predictive analytics and forecasting
Recommendations

Artificial Intelligence at Cigna – Four Use Cases

Founded in 1982, Cigna is a healthcare and insurance company based in Bloomfield, Connecticut. Cigna is a Fortune 15 global company and employs over 70,000 individuals. Cigna offers health, life, and accident insurance. They also offer Medicare and Medicaid products.
Fighting Retail Fraud with Personalization and Classification AI Tools@2x-min (2)
Business intelligence and analytics
Consumer goods
Customer analytics
Professional services
Data analysis
Retail
Data collection
Retail
Data integration
Data management
E-commerce
Fraud protection
Knowledge management
Predictive analytics and forecasting
Recommendations
Search engine optimization

Fighting Retail Fraud with Personalization and Classification AI Tools – with Experts from Instacart, Etsy, and Gap Inc.

This article is sponsored by Riskified, and was written, edited and published in alignment with our transparent Emerj sponsored content guidelines.
AI at Alibaba 950×540
E-commerce
Consumer goods
Recommendations
Retail
Sales

Artificial Intelligence at Alibaba – Two Current Use-Cases

Per Alibaba’s annual report, its revenue in 2021 exceeded 717 billion yuan (approximately 109 billion U.S. dollars), while its active yearly customers reached nearly 1.3 billion people. As of March 2022, Alibaba trades on the NYSE and has an approximate market cap of $225 billion.