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

A-Team Insight Blogs

Alternative Data Moves into The Mainstream Led by Business Insights, Geolocation and Pricing Data

Subscribe to our newsletter

Alternative data is moving into the mainstream, but not without caveats including incomplete datasets, poor quality, limited volume, unverified data and a lack of historical data for back-testing. Selecting valuable datasets in the proliferation of alternative data can also be challenging and calls on firms to focus on what answers they can get from the data that they can’t get elsewhere.

Webinar Recording: How to exploit the opportunities of alternative data

The adoption of alternative data in the trading environment was manifested in the results of an audience poll made during a recent A-Team Group webinar that discussed how to exploit the opportunities presented by alternative data. Some 67% of the audience members said their organisation is using alterative date to some extent, 27% to a small extent, and 7% to the greatest extent possible.

Dale Richards, board and strategy advisor for fintech and data providers, and a webinar speaker, said the the most popular alternative data types at the moment are business insights, geolocation and pricing data. James Cantarella, director of product strategy, news, data and analytics at Dow Jones, concurred, although he added that it will take time for alternative data to come standardised and as useful as more established news and credit card data. There will, however, be more types of data going forward, he said.

Use cases of alternative data range from identifying short-term signals to picking up breaking news on Twitter, or as Mark Ainsworth, head of data insights at Schroders, comments, ‘anything where there is money to be made’.

Featured Download: How to exploit the opportunities of alternative data

While the benefits of using alternative data include gaining unforeseen insights and competitive advantage, the challenges of sourcing and deploying the data successfully can be daunting. A second poll of webinar audience showed 60% of audience members noting integration as a key challenge, 30% unstructured data formats, a further 30% incomplete datasets, 20% unverified data, and 10% no archive for back-testing.

Will this this hold back progress? Highly unlikely, with 67% of audience members saying alternative data will become very important at their organisations over the next few years and 33% saying it will be critically important.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: From Data to Alpha: AI Strategies for Taming Unstructured Data

Unstructured data and text now accounts for the majority of information flowing through financial markets organisations, spanning research content, corporate disclosures, communications, alternative data, and internal documents. While AI has created new opportunities to extract signals, many firms are discovering that value is constrained not by models, but by the quality of the content, architecture,...

BLOG

BMLL and Features Analytics Target Surveillance Benchmarking with Level 3 Order Book Data

BMLL and Features Analytics have partnered to develop new trade surveillance benchmarking and market integrity analytics built on reconstructed historical order book data, signalling a shift towards more measurable, performance-driven surveillance frameworks. Under the agreement, Features Analytics will build and commercialise surveillance benchmarking products on top of BMLL’s harmonised historical Level 3, 2 and 1...

EVENT

Data Management Summit London

Now in its 16th year, the Data Management Summit (DMS) in London brings together the European capital markets enterprise data management community, to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...