UBS Evidence Lab
From AltData.wiki, The Alternative Data Encyclopedia
UBS Evidence Lab is an alternative-data and data-analysis function within UBS Investment Bank. Its specialists collect, clean, connect, and structure data for use by UBS Research analysts and authorized institutional clients[1]. It is part of UBS, the Swiss multinational financial-services group whose Investment Bank provides securities, research, capital-markets, and advisory services[3].
Evidence Lab differs from an independent data vendor because its datasets are integrated into the bank's research offering and distributed to eligible clients through UBS Neo[1][2]. UBS states that the unit supplies evidence for analysis but does not itself provide investment recommendations or advice[1].
What It Does
The unit creates analysis-ready datasets intended to address questions about companies, industries, and economic themes. UBS says the team processes billions of data items each month and maintains assets covering thousands of companies across sectors and regions[1]. These scale descriptions are published by UBS and are not independently audited in the cited public material.
UBS Research analysts combine Evidence Lab outputs with conventional company disclosures, industry research, and financial analysis. The bank reports that this collaboration has contributed to thousands of differentiated research reports since analysts began using the unit's expertise in 2014[1].
Data And Methodology
Public descriptions identify harvesting, cleansing, and connecting as core stages in the process[1]. The result is a curated asset intended for analysis rather than an unprocessed feed. Detailed collection methods, licensing terms, sampling limitations, and validation procedures are not disclosed for every dataset on the public overview page.
The catalog spans multiple alternative-data types. Current examples include trackers for artificial-intelligence developers and models, cloud graphics-processing-unit prices, electronics inventories, data-center exposure, trade and exports, maritime activity, United States job listings, and themes extracted from earnings calls[1].
Products
Evidence Lab is presented as a library of datasets rather than a single standardized product. Named assets include the Global AI Developer and Model Tracker, Global Cloud GPU Chips Price Monitor, Global Trade Monitor, China Export Monitor, Global Maritime Trade Monitor, and US Job Listings Monitor[1].
The offering sits within the broader UBS Investment Bank research service. Independent descriptions of UBS identify research as one of the activities of the Investment Bank alongside securities and capital-markets services[3]. Datarade separately lists UBS as a data provider but says its directory profile is unclaimed and contains no published price information; that listing should not be read as a complete catalog of Evidence Lab[4].
Delivery And Pricing
Authorized UBS Investment Bank clients access Evidence Lab through UBS Neo, the bank's institutional digital platform[1][2]. The public Evidence Lab page does not offer unrestricted dataset downloads or a self-service subscription.
No standalone Evidence Lab price schedule is publicly displayed. Datarade likewise reports no published pricing for UBS data services[4]. Commercial access therefore depends on the applicable UBS client relationship, permissions, jurisdiction, and contractual terms rather than a public retail price.
Buyers And Use Cases
Primary users are UBS Research analysts and authorized institutional clients. The datasets can support monitoring of supply chains, labor demand, computing infrastructure, product inventories, trade flows, and corporate communications[1]. Their purpose is to supply observations or structured indicators that can be evaluated alongside financial information.
Because Evidence Lab is a sell-side research capability, users receive data in the context of UBS's regulated investment-banking activities. UBS explicitly separates the provision of data and evidence from investment recommendations, and users remain responsible for interpretation and investment decisions[1][3].