Survey Shows that More than 90% of Insurers Plan to Increase AI Investment – Top 4 Trends for Insurers in 2024

To glean insights, Gradient AI conducted a survey  among 100+ customers across diverse insurance companies, revealing four noteworthy AI trends influencing the future landscape of the insurance sector.

AI Companies and Applications have a lot to Prove in 2024

In this contributed article, Saad Siddiqui, General Partner at Telstra Ventures, indicates that while there are plenty of risks for VCs in AI right now, they’re overwhelmingly outweighed by the potential benefits. As AI adoption continues to gain momentum, the task in 2024 will be making strategic investments in companies and applications capable of maximizing the value of the most revolutionary technology in the world.

New OneStream Research Finds 80% of Financial Decision-Makers Believe AI Will Increase Productivity

OneStream, a leader in corporate performance management (CPM) solutions for advancing financial close, consolidation, reporting, planning and forecasting, announced the results of its global “AI-Driven Finance“ survey, revealing the majority (80%) of financial decision-makers believe AI will increase productivity in the office of finance.

C-Suite Predicts 2024 to be Watershed Year for Financial Impact of Generative AI in Icertis Survey

Icertis, the contract intelligence company that pushes the boundaries of what’s possible with contract lifecycle management (CLM), released its inaugural AI impact report titled The Future of Generative AI: C-Suite Perspectives for 2024 and Beyond. 500 senior executives at businesses across the U.S. and U.K. shared their perspectives on how AI will transform the workforce, data privacy, the competitive landscape, and more.

IBM Launches $500 Million Enterprise AI Venture Fund

IBM (NYSE: IBM) today announced that it is launching a $500 million venture fund to invest in a range of AI companies – from early-stage to hyper-growth startups – focused on accelerating generative AI technology and research for the enterprise.

The Government Needs Fast Data: Why is the Federal Reserve Making World-altering Decisions on Stale Data? 

In this contributed article, Alex Izydorczyk, founder and CEO of Cybersyn, discusses an important question: Should there ever be “very big surprises” (or any surprises, for that matter) in the data on which the Federal Reserve bases decisions on?

Cash Treasury Trading in the Age of AI

In this contributed article, Shankar Narayanan, Head of Trading Research, Quantitative Brokers, discusses how In the era of artificial intelligence, cash treasury trading presents a unique opportunity to integrate new technologies, enhance trading methodologies and meet the growing demands of a rapidly evolving market. 

Research Highlights: Unveiling the First Fully Integrated and Complete Quantum Monte Carlo Integration Engine

Quantinuum, a leading integrated quantum computing company has published full details of their complete Quantum Monte Carlo Integration (QMCI) engine. QMCI applies to problems that have no analytic solution, such as pricing financial derivatives or simulating the results of high-energy particle physics experiments and promises computational advances across business, energy, supply chain logistics and other sectors.

Financial Institutions are Strengthening Business Intelligence Reporting and Data Warehousing through Workload Automation and Orchestration

In this contributed article, Ryan Dimick, Chief Technology Officer at SMA Technologies, discusses how financial institutions like banks and credit unions are some of the most data-rich organizations in the world. With access to members’ spending habits – from direct deposits and cash inflows to expenditures like mortgages and payments for bills – there’s a treasure trove of data. So, why are some banks and credit unions often disconnected and unable to understand their customers or members?

The Rise of Intelligent Apps in Finance

In this contributed article, Rohit Gupta, CEO and Founder, Auditoria.AI, discusses how the future of finance hinges delicately on the ability to adapt. Unfortunately, the finance department is often the last stop on the progress tour – and sometimes overlooked altogether. Optical Character Recognition (OCR) and Robotic Process Automation (RPA) are two of the most common automation tools in corporate finance today. While both tools serve a specific purpose – RPA is programmed to execute high-volume, repeatable tasks, and OCR helps extract structured data in an automated fashion – as standalone solutions, they no longer pull their weight.