AI Articles and Analysis in Financial services

Scaling AI Success in Life Sciences and Financial Services Infrastructure with Object Storage @2x

Scaling AI Success in Life Sciences and Financial Services Infrastructure with Object Storage – with Leaders from SAP, Blue Cross Blue Shield, AstraZeneca, Northwestern Mutual, and MinIO

This interview analysis is sponsored by MinIO 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.

Future Vision Highlight_ Integrated CX in Financial Services for GenAI at Scale-min

Future Vision Highlight: Integrated CX in Financial Services for GenAI at Scale – from Shankar Ramanathan at Capgemini

In a global economy where customer experience (CX) is the ultimate competitive battleground for so many sectors, businesses across industries face  daunting challenges in scaling CX solutions effectively. Despite massive investments in customer service technologies, many companies need help to deliver consistent, personalized support that meets user expectations, leading to frustration, lost revenue, and damaged reputations.

Artificial Intelligence at Geico-1x-1-min

Artificial Intelligence at Intuit – Two Use Cases

Intuit, the financial software powerhouse behind popular tools like TurboTax and QuickBooks, acquired Credit Karma in 2020 for approximately $1.7 billion. Intuit's mission is to power prosperity globally by offering innovative solutions that help individuals and small businesses manage their finances effectively. 

Short Term and Long Term ROI for AI in Finance@2x-min

Short Term and Long Term ROI for AI in Finance – with Matthias Steinberg of MindBridge

This interview analysis is sponsored by MindBridge 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.

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

Dozens of GPT-driven products are already on the market, and hundreds more are in development. These tools collectively aim to revolutionize traditional roles and processes, transforming them into dynamic, parallelized workflows using variants of LLM models, such as AutoGPT. Tools like GitHub Copilot, powered by OpenAI's Codex, are demonstrating significant improvements in developer productivity, with some studies showing up to a 55% increase in task completion speed. 

Tires and Data Collection for Autonomous Vehicles-1

Tires and Data Collection for Autonomous Vehicles – with Chris Helsel of Goodyear

Technological advancements have contributed to an increase in more efficient and sustainable transportation solutions. Predictions made decades related to autonomous vehicles were wildly optimistic. The automated transportation industry might not align with those early predictions, but there have still been noteworthy developments. 

Transforming the Enterprise-Level Customer Experience with AI@1x

Transforming the Enterprise-Level Customer Experience with AI – with Jason Aubee of TechSee

Contact centers play a crucial role in delivering exceptional customer experiences (CX) across industries, both B2c and B2b. As customer expectations elevate, organizations increasingly leverage AI to streamline operations and enhance customer service. According to recent reporting in the MIT Technology Review, enterprises generally deploy AI to transform contact centers, usually taking the form of intelligent virtual assistants to obtain predictive customer insights as well as for dispute and fraud management. 

Leveled Approaches to AI for Asset Management Challenges-1-min

Leveled Approaches to AI for Asset Management Challenges – with Aman Thind of State Street

The asset management industry is going through several challenges, like the prolonged low-interest rate environment, dwindling margins, increased cost pressures, and squeezed profitability. Meanwhile, exponential growth in data volumes has overwhelmed legacy data management systems and analytical tools, making it tiring to process and extract valuable insights from the deluge of information.