IT for Financial Services in the Age of GenAI-min

IT for Financial Services in the Age of GenAI - with Craig Mackereth of Rimini Street

|Business intelligence and analytics|Cybersecurity|Data analysis
Financial Services Challenges and Solutions
in the Age of Generative AI-min
Finance

Financial Services Challenges and Solutions in the Age of Generative AI - with Fabrizio Burlando of Mastercard

Driving Partnerships and Prioritization Strategies for AI in Financial Services-1-min
Finance

Driving Partnerships and Prioritization Strategies for AI in Financial Services - with Julie Winkler of CME Group

Multichannel Customer Journeys in Financial Services-1
Finance

Multichannel Customer Journeys in Financial Services - with Anuj Maniar of Deloitte

02 – Streamlining Data-Driven Decision-Making in Customer Experiences
for Financial Services@1x-min
Finance

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

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AI transformation in Banking 1200x200Streamlining Data-Driven Decision-Making in Customer Experiences for Financial Services – with Ciprian Porutiu of Marsh McLennan and Mike Borrelli of Uniphore

Trending AI in Banking Context

The Implications of Generative AI on Investment Banking – v.1
Business intelligence and analytics
Finance
Compliance
Financial services
Customer analytics
Government
Data analysis
Law enforcement
Data auditing
Data collection
Data integration
Data management
Enterprise resource planning
Generative AI
Investment
Large Language Models
Risk management

The Implications of Generative AI on Investment Banking – with Andrea Haskell and Val Srinivas 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.
The Future of Customer Interactions in Financial Services
Business intelligence and analytics
Case management
Claim management
Claim management
Compliance
Conversion optimization
Customer analytics
Customer analytics
Customer experience
Customer service
Data auditing
Data collection
Data integration
Data management
Enterprise resource planning
Generative AI
Help desk
Intelligent assistant
Large Language Models
Market segmentation
Marketing and advertising
model development
Risk management

The Future of Customer Interactions in Financial Services – with Ivan Edwards of Cadence Bank and John Thomas 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.
Financial Services Challenges from a Data Perspective – with Bill Waid of FICO@2x-min
Case management
Claim management
Compliance
Customer experience
Customer service
Data auditing
Data collection
Data entry
Data integration
Data management
Enterprise resource planning
Generative AI
Help desk
Intelligent assistant
Investment
Knowledge management
Large Language Models
model development
Natural Language Processing
Process automation
Report generation
Risk management
Training and development

Financial Services Challenges from a Data Perspective – with Bill Waid of FICO

Originally founded as Fair, Isaac and Company, FICO is a data analytics company founded in 1956. Based in Bozeman, Montana, the company is focused on credit scoring services, most notably its FICO score, which measures a person's creditworthiness. 
001 – Embedded Analytics in Banking – Two Use Cases
Business intelligence and analytics
Data analysis
Data integration
Data management
Enterprise resource planning
Generative AI
model development
Natural Language Processing
Predictive analytics and forecasting
Risk management
Search engine

Embedded Analytics in Banking – Two Use Cases

Traditional business analytics has undergone significant changes thanks to the internet revolution, cloud computing and the shift to self-service analytics, contributing to the recent rise of embedded analytics in business operations. Embedded analytics involves embedding and integrating visualizations, dashboards, reports or predictive analytics in everyday business applications. 
OECD-Approved AI Tools and Resources for Financial Services@2x
Business intelligence and analytics
Case management
Compliance
Customer analytics
Data analysis
Data auditing
Data collection
Data integration
Data management
Enterprise resource planning
Knowledge management
Predictive analytics and forecasting
Report generation
Text analysis

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.
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