About a-team Marketing Services

A-Team Insight Blogs

Alveo Reviews Costs and Use Cases of AI in Financial Data Management

Subscribe to our newsletter

Adoption of AI across financial services is causing a cost shift from operations to technology and data, with 63% of decision makers expecting AI to result in an increase in the cost of data within their organisation. The cost of hardware and software licences is also likely to rise in response to AI, and 50% of decision makers note technological limitations among the biggest barriers to implementing AI in financial data management, 46% reference a lack of skilled personnel.

On the upside, according to research commissioned by Alveo that surveyed senior decision-makers at financial services organisations in the UK, US and DACH region (Germany, Austria and Switzerland), AI offers huge potential to drive productivity across data management with 53% of the sample ranking data quality management as the area of data management where AI will have the greatest impact.

In terms of today’s use of AI, the survey found financial services firms using AI for different aspects of financial data management, with 55% of firms using it for risk data management, 49% for client data management, 47% for portfolio data management and 46% for master data management.

Commenting on the results, Martijn Groot, vice president of marketing and strategy at Alveo, says: “As the human element in data workflows diminishes due to the next wave of automation, there is a large premium on good quality data. To achieve and maintain the high standard of data quality necessary for effective AI implementation, firms will need financial data management expertise to design, oversee, and refine the infrastructure and processes that feed into AI systems, and ensure all data is accurate, relevant, and timely.”

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: How to organise, integrate and structure data for successful AI

Artificial intelligence (AI) is increasingly being rolled out across financial institutions, being put to work in applications that are transforming everything from back-office data management to front-office trading platforms. The potential for AI to bring further cost-savings and operational gains are limited only by the imaginations of individual organisations. What they all require to achieve...

BLOG

Agentic AI Deployment Presents Potentially Dangerous Data ‘Trust Paradox’

Artificial intelligence deployment in capital markets’ data processes may be approaching an inflection point that, if not managed properly, could introduce dangerous risks to institutions’ operations. The growing deployment of anonymous agents has the potential to hardwire data errors into workflows, magnifying data weaknesses as the automating technology scales processes, according Informatica from Salesforce. The...

EVENT

TradingTech Summit London

Now in its 15th year the TradingTech Summit London brings together the European trading technology capital markets industry and examines the latest changes and innovations in trading technology and explores how technology is being deployed to create an edge in sell side and buy side capital markets financial institutions.

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...