1. Fintech
Chapter 16
Social Issues: Diversity and Inclusion,
Unemployment and Income Distribution

2. Fintech contributions:
Democratization of banking and finance
Reducing friction and other transaction costs
Potential to reduce systemic risks
Increased competition for big banks

3. But There Are Social Issues:
Diversity
Inclusion
Unemployment
Income Distribution

4. Lack of Diversity in Tech
Industry Participation By Gender Sex and Race Groups
High Tech Vs. All Private Industries

5. “Why is Silicon Valley So Awful to Women?” Atlantic, April 16, 2017
CEOs at tech startups backed by VCs: <3% female, <1% black
“… startup teams should be as like-minded as possible. While diversity may benefit a company later on, a startup must work quickly and communicate efficiently. Having a shared view of the world helps in this regard…From the outside, everyone in your company should be different in the same way…[a] co-founder at PayPal says that startups should make their early staff as similar as possible. Startups have limited resources and small teams…”
“mirror-tocracy’ than a “meritocracy”.

6. Diversity
Companies with more diversity are more innovative and have superior performance.
They are 45% likelier to report year over year market share growth
70% more likely to capture new markets.
In diverse companies, leaders value differences and all employees can find leaders to support compelling ideas that might seem too “out of the box”
In those companies with little or no diversity, women are 20% less likely to have their ideas accepted
people of color are 24% less likely
LGBT employees are 21% less likely.
The impact of ignoring these ideas is a significant opportunity cost for the company

7. Hiring a work force with inherent diversity characteristics of gender, ethnicity and sexual orientation
Behavior
Ensuring that everyone is heard
Making it safe to propose new ideas
Giving team members decision-making authority
Sharing credit for success
Giving actionable feedback
Implementing feedback from the team.

8. (lack of) Diversity in VC Funded Startups
Just 7% (of a sample of 2,005 startups funded by VCs) were founded by women
Those startups received an average of $77 million, as compared to $100 million for male-led startups.

9. (lack of) Diversity in VC Funded Startups
Men and women founders seeking funding were asked different questions by VCs
The level of funding was impacted by this discrepancy.
The startups were comparable in terms of quality and capital needs
Male-led startups raised five times more funding than female-led ones.
67% of the questions asked of men were “promotional” (focused on hopes, achievements, advancement, and ideals)
66% of the questions asked of the women were “prevention” oriented (concerned with safety, responsibility, security, and vigilance

10. VCs Ask Different Kinds of Questions of Men and Women

11. The National High-Tech Sector is Less Diverse than Overall Private Industry
High-tech sector employed
A larger share of whites (63.5 percent to 68.5 percent),
Asian Americans (5.8 percent to 14 percent)
Men (52 percent to 64 percent)
A smaller share of African Americans (14.4 percent to 7.4 percent),
Hispanics (13.9 percent to 8 percent),
Women (48 percent to 36 percent).
At Executive level, 83.3 %Whites, African Americans (2 percent), Hispanics (3.1 percent), and Asian Americans (10.6 percent).

12. Leadership Positions by Race and Ethnicity in High Tech
Source: EEOC

13. The National High-Tech Sector is Less Diverse than Overall Private Industry
Women account for only 20% of Executives in High tech vs 29% in overall private sector
Select Job Categories by Sex in High Tech v. All Private Industry

14. Silicon Valley Tech Firms are Less Diverse than Overall Private Industry
Tech Executives are 93 % White and Asian American
57 % White
36 % Asian American
1.6 % Hispanic
<1 % African American
Tech Professionals are 91 % White and Asian American
50 percent Asian Americans
41 percent White
Women account for 49 % of the jobs at non-tech firms while only 30 % in tech
African Americans account for less than 1 % and Hispanic workers account for barely 1.6 % of tech jobs

15. Gender Gap at Top Tech Companies

16. U.S. demographics for technology jobs at major tech companies

17. Lack of Diversity at VCs
NVCA survey of 3,000 VC employees:
Women are 45 % of VC workforce.
Yet, women are only 11% of Partners
Women more likely to fill Administrative (95%) and Investor Relations, Communications, or Marketing positions (75%).
Black or African American employees comprise only 3%
No Investment Partners were Black
Hispanic or Latino employees only 4% of the workforce and 2% of Investment Partners.

18. Lack of Diversity at VCs
NVCA survey of 3,000 VC employees (cont):
Only 27% of responding firms had a Human Capital strategy, 15% had a Diversity Strategy and 17% had an Inclusion Strategy
The study concludes that education and tenure do not explain the gender gap.
Only 27% of responding firms had a Human Capital strategy, 15% had a Diversity Strategy and 17% had an Inclusion Strategy.
Most firms’ recruitment and promotion practices rely on notifying peers or searching internally, instead of conducting a wider search for the best available candidates.

19. Other Indicators
2016 Forbes list of leading tech investors: only 5% women
Bias lawsuits

20. But Some “get it”:
“I would be remiss if I did not address the diversity issue. A number of us have been public about the fact that we wanted to add some diversity into our partnership and that is what we have done. And we are not done. We will continue to look for diversity across our organization and that means diversity of all kinds. We are not doing this for optics or public pressure. We believe that different perspectives, life experiences, and orientations in a partnership will lead to better decisions. “ Fred Wilson

21. Is it a Pipeline Problem? A Bias Problem? Both?
EEOC: some truth in pipeline, or available talent pool, but many other factors
Minority groups are 9% of grads, but only 5% of tech hires
Urban Institute:
The U.S. educational system provides more than enough STEM grads.

22. Is it a Pipeline Problem? A Bias Problem? Both?
Survey of 557 female scientists:
Two-thirds of women (and three- fourths of Black women) report having to prove themselves over and over; their success discounted, and their expertise questioned.
Thirty-four percent (forty one percent for Asian women) reported pressure to play a traditionally feminine role,
Fifty-three percent reported backlash from speaking their minds directly or being outspoken or decisive.
Women, particularly Black and Latina women, are seen as angry when they fail to conform to female stereotypes
Almost two thirds of women with children say their commitment and competence were questioned and opportunities decreased after having children.
Three fourths of women surveyed said that women in their workplace supported each other; one fifth said they felt as if they were competing with women colleagues for "the woman spot".
Isolation is a problem: 42 percent of Black women, 38percent of Latinas, 37 percent of Asian women and 32 percent of White women agreed that socializing with colleagues negatively affect perceptions of their competence.

23. Unemployment Impact
State Street Bank estimates that 20% of jobs will be lost in 2020
Citigroup: more than 1.8 million U.S. and Euro bank workers could lose their jobs within 10 years
Former Citi CEO predicts 30% of all banking jobs to disappear by (770,00 in U.S. and over 1 million Euro.

24. Income Distribution Effects
Many Fintech services improve life for the worse off
M-Pesa
Charitable activities
But…
“Winner take all” payoff structure creates “Superstar” firms
“Rising tide of hatred of the one percent”
Real estate prices
Political backlash

25. Income Distribution Effects
Globalization-horizontal. It takes existing products and services to new markets
Technology-vertical. Improves on previous ways of doing things
Both are forces which are increasing income disparity

26. Income Distribution Effects
BLS employment forecast:
Annual employment sector growth
Total 0.7%
Comp sci and math: 13.5%

27. Income Distribution Effects
Bernanke:
Equality of opportunity,
No guarantee of equal outcomes
Some insurance against the most adverse outcomes

28. Income Distribution Effects
Policy solutions:
Limiting growth of startups (and restricting trade) do more harm than good
Foster dynamic growth
Provide transitional assistance to those most negatively affected
Retrain and remove employment frictions

29. Income Distribution Effects
Education and training:
More STEM degrees and non-degree skilled jobs
Microsoft: “we need to innovate to promote inclusive economic growth that helps everyone move forward”
IBM: “New collar” jobs. 1/3 of employees have less than a 4 year degree
Amazon: apprenticeships
MIT: “Inclusive Innovation Competition”

30. Income Distribution Effects
Robot Tax
“Right now, the human worker who does, say, $50,000 worth of work in a factory, that income is taxed, and you get income tax, social security tax, all those things. If a robot comes in to do the same thing, you’d think that we’d tax the robot at a similar level”
The Robot Tax proposal recognizes the threat of tech to employment, but it will make robots more expensive, limiting innovation.

31. Income Distribution Effects
Its important for people to feel needed and to be needed. Robots doing the work, on a robot schedule, with transfer payments to unemployed is not enough. A world with people working beside robots could be fine as long as the role of people is truly necessary. But robots can work 24/7, don’t take breaks, don’t have children’s plays and ball games to attend. Solution is not to roll back technology and revert to less efficient means of production. It’s to engage in serious discussion recognizing that technological change is inevitable and will continue, and social welfare depends on finding a way for human efforts to continue to be valuable and rewarded appropriately.