eric parrado: gender differences in the chilean banking system

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Cuenta Pública SBIF 2015: Balan ce y Desafíos ! Gender Differences in the Chilean Banking System: #BeBoldForChange Eric Parrado H. (@eric_parrado) Superintendent of Banks and Financial Institutions, Chile OECD Conference on Business Finance and Gender Paris, March 8, 2016

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Cuenta Pública SBIF 2015: Balan ce y Desafíos !

Gender Differences in the Chilean Banking System: #BeBoldForChange

Eric Parrado H. (@eric_parrado)Superintendent of Banks and Financial Institutions, Chile

OECD Conference on Business Finance and GenderParis, March 8, 2016

International Context

Global Gender Gap Index 2016 (Groups of countries)

Average

Low Income Lower Middle Income

The boxes show the percentiles 25 and 75 of distribution and lines of minimums and maximums.

Chile ranks 70 out of 144 countries of the Global

Gender Gap Index.(World Economic Forum).

Upper Middle Income

High IncomeChile0,5

0,6

0,7

0,8

0,9

1,0

The economic dimension is the weakest

Chile’s worst perfomance in the Index is“Economic Participation”

Education

38

Health

39

Political empowerment

39

Economic participation

Position (nº) in the World

Ranking

• Wage equality for similar work

• Estimated earned income

• Labor force participation

133

97

92

119

What can we do as an organization to foster conscious bias in favor of women?

• Apply this bias within the organization, without affecting meritocracy

• Incorporate in the institutional information system a gender approach:

Gender gap in access to financial services

Gender gap in financial labor markets

What are we trying to do?

• Chile is commited to women’s data:

• Chile is the only country in the world that has consistently tracked sex-disaggregated data on its banking system for over 15 years.

Issues covered in the report

Loans Consumer Mortgage Commercial

Savings On sight deposits Time deposits

Cash management

Use of debit products

Integrity Bounced checks Nonperforming loans

Gender Gap: Loans

Numbers of debtors

• Average debt: For every US$ 100 owed by men, women owe US$ 59.

• Consumption: For every US$ 100 owed by men, women owe US$ 53.

US$ 59DEBT

US$ 53

• Mortgages: For every 100 monetary units, the amount assigned to mortgage funding is: 57 men, 61 women.

womenmen

2002

2014

2015

36%

47%

48%

64%

53%

52%

0

10

20

30

40

50

60

5761

CONSUMPTION

2% 0%

-17% -25%

-20%

-15%

-10%

-5%

0%

5%

10%

Rate gap Term gap Amount gap

Gender Gap: Loans

Terms of credit related to mortgage loans

July 20012 / December 2013

Gender Gap: Loans

Terms of credit related to consumption loans

15%

-2%

-32% -40%

-30%

-20%

-10%

0%

10%

20%

Rate gap Term gap Amount gap

Gender gap: Loans

Terms of credit related to commercial loans

17% 28%

-41% -50%

-30%

-10%

10%

30%

50%

Rate gap Term gap Amount gap

Gender gap: Savings

Number of accounts by gender, 2002-2015

women men

46,4%

48,7%

56,2%

67,7%

53,6%

51,3%

43,8%

32,3%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

2002

2015

Voluntary pension savings accounts

Housing savings accounts

Term savings accounts

Time deposits

Voluntary pension savings accounts

Housing savings accounts

Term savings accounts

Time deposits

69,0%37,7%42,8%46,2%

31,0%62,3%57,2%53,8%

0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%

Gender Gap: Cash Management

Number of Cash management accounts

(Checking accounts and sight deposits), 2002-2015

2015

200238%62%

52%48%

Gender Gap: Cash Management

Average deposit balance in cash management accounts (US$ dollars*)

Women hold 26% less than men

Women hold 31% less than men

womenmen

1.150

2.415

1.553

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

20152002

3.475

* Currency at the end of December of each year

Gender gap: Financial Integrity

Bounced checks for every 1.000 checks presented for payment

Non-performing loans, 90 days -1 year (Amount of non performing loans as % of total amount of debt)

womenmen0

3

6

9

12

15

20152014

12,6 12,510,7 10,8

womenmen0

3

6

9

12

15

20152014

12,6 12,510,7 10,8

womenmen

1,0

1,5

2,0

20152014201320122011201020092008

1,75

1,63

1,371,30

1,101,08

Lessons

1. Seek internal buy in, particularly from the top.

2. Balance information needs and opportunity costs.

3. Data is not an end in itself. Think about next steps.

4. Apply a conscious bias in favor of women at all levels:

Within organizations. Finding the gender dimension in their actions and products.

> The SBIF promotes gender equality using data and internal policies and practices.