About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

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: Navigating a Complex World: Best Data Practices in Sanctions Screening

As rising geopolitical uncertainty prompts an intensification in the complexity and volume of global economic and financial sanctions, banks and financial institutions are faced with a daunting set of new compliance challenges. The risk of inadvertently engaging with sanctioned securities has never been higher and the penalties for doing so are harsh. Traditional sanctions screening...

BLOG

Data Quality Still Troubling Private Market Investors: Webinar Review

Obtaining and managing data remains a sticking point for investors in private and alternative assets as financial institutions sink more of their capital into the markets. In a poll of viewers during a recent A-Team LIVE Data Management Insight webinar, respondents said the single-biggest challenge to managing private markets data was a lack of transparency...

EVENT

TradingTech Summit New York

Our TradingTech Summit in New York is aimed at senior-level decision makers in trading technology, electronic execution, trading architecture and offers a day packed with insight from practitioners and from innovative suppliers happy to share their experiences in dealing with the enterprise challenges facing our marketplace.

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,...