Reducing Implicit Bias In Investment Decision-Making
According to a US Government Accountability Office report, investment firms owned by women and people of color manage less than 1% of the $70 trillion in U.S. assets under management — despite the fact that 70% of the U.S. population represent women and people of color. Building a better balance is not only the right thing to do for the asset management industry itself; evidence by the Small Business Administration also suggests that fund managers of color are more likely to direct investment capital towards investees of color than their peers, resulting in a ripple affect that supports communities in many ways.
In contrast, a mountain of evidence proves that unconscious or implicit biases negatively affect people of color in all structures and institutions of American society, including those who make decisions on the use capital, from investment staff, to asset managers. These biases are preventing capital from reaching investees of color and underserved communities — without regard to the quality or promise of the investments themselves. As organizations commited to racial equity work towards improving diversity among asset managers, how can we simultaneously work to improve the quality and fairness of decision-making in the existing industry? This resource provides a growing list of ideas and activities to reduce the effects of racial bias, through tools, training, and more.
Click here to see a resource exploring how supporting entrepreneurs of color can ultimately support communities of color, and foundation efforts in this area.
MIE is still learning and relies on the experiences and learning of the the impact investing community. If you have a resource to share for this page, please email us!
Visit our Racial Equity Library for a growing list of resources on racial equity and impact investing. This page also includes general resources on racial equity for early learners on this topic and for individuals who are looking for broad organizational resources that can help all staff, beyond impact investing teams. For example you can see additional examples of implicit bias tools and training for related issues, such as hiring and overall organizational staff, on this page.
Training & Education
- Incorporating implicit bias training into investment staff trainings: As foundations make organization-wide commitments to racial equity and staff participate in broader racial equity education, how can these trainings be particularly targeted to the unique decision-making processes involved in investing? Consider reaching out to CFA Institute and other training programs to learn more about available trainings. If none exist, foundations can also consider funding the creation of these trainings by developing partnerships between existing racial equity and investment management trainers. Very little currently exists on this topic: please reach out to MIE if you have resources or ideas to share.
- Requiring fund managers (indirect or direct) to undergo implicit bias training: In addition to selecting firms committed to progress, are there ways to engage and hold managers accountable to change? Illumen Capital, an impact investment fund, requires that the funds they invest undergo implicit bias training as a condition of their investment. Consider speaking with your asset managers about their own engagement in racial equity.
- Read up on behavioral finance and behavioral economics: Behavioral finance explores how psychology affects the decisions of investors or financial professionals and how that shapes markets. Similarly, behavioral economics studies how these factors affect our economic decisions and their ultimate impact. While these fields of study encompass a wide variety of biases, they can help us understand the extent to which irrational emotions and opinions — including racial bias— affect our decisions.
Although the tools and approaches we create are also often products of our own bias, there is growing interest in the opportunity for well-crafted processes to remove some of the individualized biases that enter our decision-making. For example, Founders Factory, a U.K. startup accelerator, notes that their AI platform identifying high-potential entrepreneurs is intended to avoid the unconscious biases that normally privilege some demographic groups and backgrounds over other.