Report laying groundwork for developing data solutions for investors to help address modern slavery.
This report, entitled Data for Investor Action on Modern Slavery: A Landscape Analysis, was developed by Florian Ostmann and Alex Harris from the Alan Turing Institute and Nyasha Weinberg, Irene Pietropaoli and Lise Smit from the Bingham Centre for the Rule of Law. The outputs of the project include a full report, brief Research Summary and a catalogue of data resources on modern slavery that the research identified as potentially relevant for investors.
Recent years have seen a rapidly growing recognition of the role of investors in addressing modern slavery in business contexts, but investors often find it difficult to obtain information needed to exercise this role effectively. Actionable insights on modern slavery that meet investors' information needs are often difficult to come by.
This report maps out the potential of data in enabling investors to take effective action on modern slavery by analysing the kinds of insights investors need and examining the role that different kinds of data can play in arriving at these insights.
Based on consultation with investors, the analysis identified two main types of insights that investors need: information on the significance of modern slavery in the context of a given company and information on the company's performance in managing modern slavery risks. The research mapped out data sources with relevance to these types of insights, grouping them into four categories: general information about the occurrence of modern slavery; information about legal and societal expectations on companies; information controlled by investee companies (such as Modern Slavery Statements); and company-specific information from independent sources (such as company ratings, information about independent audits, or information about company-specific controversies).
The report found that although recent years have seen progress in developing data resources on modern slavery, there are significant obstacles to obtaining the kinds of actionable data-driven insights needed by investors. These include data being incomplete (for example covering only certain companies or sectors), difficult to compare, or taking unstructured forms (for example in the case of Modern Slavery Statements). The fact that access to data from commercial providers often requires payment is another factor that contributes to a fragmented data landscape.
The research sought to identify strategies for overcoming these obstacles. The resulting analysis lays the groundwork for developing new and improved data solutions that cater to investors' information needs.