Regulatory Risks and Challenges

One of the persistent pain points for JEDI investors is around data collection and regulation. Differences in local regulation abound, with varied implications for investors. 

privacy regulations

In many jurisdictions, racial and ethnic identity information collection needs to be based on voluntary disclosure to comply with international human rights principles and other local data, legal and privacy regulations. As such, though there might be an appetite to collect race/ethnicity disaggregated data in order to fully implement an allocator's JEDI lens, this regulatory limitation poses challenges. This is quite relevant in the EU context (refer to box below)

Box: In the EU and the UK, there are currently no legal obligations of JEDI reporting, but this is changing with Financial Conduct Authority and its"Inclusion Measurement Guide" to improve and develop inclusion data metrics and analysis across the UK financial services sector, while the  Non-Financial Reporting Directive in Europe, which operates on a "comply or explain'' system is supporting D&I reporting. While this is mostly at the board diversity level, it is a move in the right direction. 

Data challenges in the EU and UK are around privacy and self-reporting, as compliance with applicable data protection laws is essential. For example, data on racial or ethnic origin, physical or mental health, religion or similar beliefs and sexual orientation is sensitive personal data and as such treated as special category personal data under the UK GDPR and other EU laws. When diving deeper into data and reporting, there are a number of underlying individual protection clauses in place, alongside the need to ensure access to this data is always restricted and safely stored. In Germany for example, while there is a vibrant Afro-descent population, there is currently limited regulation that enables statistical data collection on such minority groups. The combination of these legal restrictions and underlying social context impacts the breadth and depth of JEDI data collection. In some cases, organisations constrained by these legal limitations are leveraging the use of location/geo-mapping and use of postcodes (where certain ethnic and minority groups are concentrated) to ascertain relevant information on social inclusion and social justice projects.

Category mismatch

How people self-identify might not always fit the categories provided, hence the data may not always be 100% accurate. As our global social and cultural fabric continues to evolve, this drives up complexity around self-identification and data collection.

Lack of standardisation

Given different geographies and jurisdictions, a set of racial and ethnic categories that apply in the US or Canadian context may not be valid in the UK or Africa, and so each country has its own set of contextually relevant race/ethnic/caste/tribal categories. One commonality to acknowledge is that there tends to be dominant categories and more marginalised ones. 

The diagram below indicates a collation of  ILPA's diversity metrics template, illustrating the commonality and also the distinction between categories across geographic contexts:

Social and historical context

It is also important to acknowledge these conversations around race, ethnicity and other forms of diverse lived experience are rooted in cultural, historical, political, colonial and other contextual elements. This deeply impacts these conversations and hence ability to openly collect data. For example, in Rwanda, since the 1994 genocide, it is illegal to collect ethnicity information. In other areas, historical context has resulted in denial of any racial discrimination.

Reporting risks

In addition to the prevailing contextual challenges, it is important to acknowledge that for the individual - be it at the organisational, fund manager, entrepreneur, end user, or community member level - there are other risks associated with reporting on categories around race, ethnicity, sexual orientation and more. For some, disclosing data could place them at risk of financial, physical, or mental harm, including gender-based violence, fear of losing jobs, reputational penalties and other pressures. Moreover, in most cases, minority groups are socialised to feel grateful for having any access to jobs and opportunities that they become either too used to discrimination or too fearful to report.

Cost of reporting

As with any measurement, reporting and managing framework, there are costs associated with data collection, analysis and data management, which if not priced into the process, can be prohibitive and corners tend to be cut.