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Eric Parrado: Gender differences in the Chilean banking system

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This presentation was presented at the OECD's Conference on Business, Finance and Gender on 8 March 2017. More information: http://oe.cd/wmn

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Eric Parrado: Gender differences in the Chilean banking system

  1. 1. 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
  2. 2. 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 Income Chile0,5 0,6 0,7 0,8 0,9 1,0
  3. 3. 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
  4. 4. 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
  5. 5. 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.
  6. 6. 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
  7. 7. 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$ 59 DEBT US$ 53 • Mortgages: For every 100 monetary units, the amount assigned to mortgage funding is: 57 men, 61 women. women men 2002 2014 2015 36% 47% 48% 64% 53% 52% 0 10 20 30 40 50 60 57 61 CONSUMPTION
  8. 8. 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
  9. 9. 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
  10. 10. 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
  11. 11. 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%
  12. 12. Gender Gap: Cash Management Number of Cash management accounts (Checking accounts and sight deposits), 2002-2015 2015 2002 38% 62% 52% 48%
  13. 13. 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 women men 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
  14. 14. 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) women men0 3 6 9 12 15 20152014 12,6 12,5 10,7 10,8 women men0 3 6 9 12 15 12,6 12,5 10,7 10,8 1,0 1,5 2,0 20152014201320122011201020092008 1,75 1,63 1,37 1,30 1,10 1,08
  15. 15. 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.

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