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Privacy Symposium The Institute of Law China Academy of Social Science Global Landscape Dr. Michael Turner Economic Considerations in Privacy Law Political & Economic Research Council June 17, 2006 1 The Promise of Information Led Development (ILD) Deloitte estimates that between 2002-2006 $356 billion worth of global financial services will relocate to India, creating 2 million new jobs. (“worldwide sourcing”) In advanced and emerging economies, use of personal information increasing. June 17, 2006 Risk assessment (credit reporting) Marketing (offline and online) Location decisionmaking (retail outlets) Inventory decisionmaking (initial and ongoing) 2 Benefits of Information Sharing Measurement difficulties June 17, 2006 Quantifying economic value of information for national economy impossible US Federal Reserve Bank staff studies (1999) linked productivity gains to use of Information Technology (IT)--subsumed information Empirical and theoretical micro-economic studies highlight value of information flows more narrowly (e.g. financial services sector) 3 Case #1: Apparel Distance Shopping $15 billion clothes sold via direct mail and Internet in US during 2000. Retailers rely on “third-party data”--personal information about existing customers--to target prospective customers. Without access to third-party data, apparel retailers costs increase approximately 7%, resulting in $1 billion additional costs. (ISEC 2001--Michael Turner) June 17, 2006 4 Case #2: Nonprofits and Charities Third-party data used extensively by US nonprofit and charitable organizations to solicit contributions ($80 billion raised via direct mail and telephone). As with merchants, charities append “internal” data on existing contributors with “external” data to develop list of prospective contributors. Without access to third-party data, US charities and nonprofits, costs increase 30%, reducing funds available to charities by $10 billion. (ISEC 2002--Michael Turner) June 17, 2006 5 Why Share Payment Information? Problems facing lenders and how more payment information can help solve them o Too many high-risk borrowers (“adverse selection”) o Not enough incentives to pay (“moral hazard”) o Misidentifying likelihood of paying (“asymmetric information”) June 17, 2006 Consumers o Fairer prices o Wider access to credit o Offers “calibrated” to match credit risk and credit capacity Lenders o Reduced delinquencies o Expand old markets and enter new markets The Economy o Better overall financial performance o Growth 6 Rationale: Finance is Crucial to Economic Growth Established: Financial sector mobilizes savings and allocates capital for investment and consumption growth Some estimates of impact.* If private sector lending, increased by 33% of GDP, results for economy: +1.0% annual per capita GDP growth +0.8% annual per capita capital stock growth +0.8% annual productivity growth June 17, 2006Levine, “Financial Development and Economic Growth: Views and Agenda” Journal of Economic Literature, *Derived from findings of Ross Vol. 25(June 1997), pp. 688–726. Their findings are consistent with those of other studies, see Jose De Gregorio and Pablo Guidotti, “Financial Development and Economic Growth.” World Development, Vol. 23, No. 3, (March 1995) pp. 433-448. Their reported impacts were larger. 7 Estimations: Private Full-File Coverage and Private Sector Borrowing VARIABLE Model I Consta nt Log of GDP per capita (adjusted for PPP) Avg. Change in GDP (1995-2004) Legal Rights of Creditors (from 0 to 10) Credit Information 1 (from 0 to 6) Private Full-file Coverage (0 to 100, as percentage of adults) Private Negative-only Coverage (0 to 100, as percentage of adults) Public Full-fi le Coverage (0 to 100, as percentage of adults) Public Negative-only Coverage (0 to 100, as percentage of adults) R squared F-stat (p value) 0.7075 16.93 (1.88e-012) Residual Standard Error N * p < 0.1 ** p < 0.05 ***p < 0.01 -142.40*** (35.31) 20.31*** (4.65) -1.20* (0.70) 4.55** (2.07) -3.87 (2.88) 0.72*** (0.20) -0.02 (0.86) -0.11 (0.41) 0.16 (0.46) June 17, 2006 Model IV (reduced) -130.80*** (32.20) 16.85*** (3.87) 4.80** (1.97) 0.67*** (0.16) 0.6883 44.9 (1.887e-015) 29.45 65 29.12 65 Lesson: what matters? • Wealth • Creditor Rights • Reporting o private o full-file o with widespread participation For a country, going from no adults to having all (100% of) adults with positives and negatives in a private bureau increases private sector lending by more than 60% of GDP. (Without the US and UK, which have high private sector lending, the estimated increase is still more than 45% of GDP.) 8 Participation & Loan Performance Colombia 2005 15% Default Rates 12% 9% 6% 3% 0% 0% 15% 30% 45% 60% 75% 90% Acceptance Rates June 17, 2006 100% Reporting Full File 75% Reporting Full File 25% Reporting Full File 0% Reporting Full File 50% Reporting Full File TransUnion/PERC 2006 9 Data Privacy: When Only Delinquencies Can Be Shared (I) What happens to loan performance? Source: World Bank (Miller and Galindo) June 17, 2006 10 Data Privacy: When Only Delinquencies Can Be Shared (II) What happens to credit access? June 17, 2006 11 Impact on Non-Financials-Change in Acceptance Rates Sample (3.1 million Colombian files) NON -FINANCIALS: ACCEPTANCE RATE Share of furnishers providing positive and negative information Target De fault rate 5% 7% 10% 12% 100% 5.50% 37.30% 61.03% 69.75% 75% 4.00% 29.95% 49.36% 63.27% 50% 2.95% 17.96% 43.14% 57.70% 25% 1.96% 10.07% 36.01% 50.43% Non financials: cell-phones, utilities, rent TransUnion/PERC 2006 June 17, 2006 12 Loan Performance in Japan (2004) A more comprehensive reporting system (TeraNet – similar to proposed D&B model for Australia) reduces the probability of delinquencies (60+ days) by 34.1% for the mean loan. The value of more comprehensive data increases with loan amount (reduces probability of delinquency by 41.3% for the mean large loans). (Waseda University 2004) June 17, 2006 13 Loan Performance in Hong Kong In the four years to 2002, Hong Kong experienced growth in personal bankruptcy of 1,900%. Around 12% of all personal bankruptcy was caused by credit card debt. Credit card write-offs stood at 13.6% by the end of 2002. This was significantly higher than comparable Asian nations such as Singapore and Korea, which had write-off rates of 5.5% and 6.1% respectively. Defaulting customers in Hong Kong had acquired debts up to 55 times monthly income in 2000 and 42 times monthly income in 2002. Following the shift to more comprehensive reporting, Hong Kong Monetary Authority figures show that between December 2002 and December 2004: Credit card write-off ratios declined from 13.6% to 3.76%; and Credit card delinquency ratios declined from 1.25% to 0.44%. June 17, 2006 14 How Information Sharing Helps the Relatively Less Privileged Less participation Less deep Racial minorities, the young, women, and lower income groups suffer relatively worse than racial majorities, older, men, and higher income groups. June 17, 2006 15 What Information Sharing Has Meant for Price of Credit? Share of card account balances by interest rate tier Credit card interest rate tier over 18% and over 18% and over18% and over 18% and over 18% r e voand dnaover %81 99 % 16.5 -17.99 % 16.5 -17.99 % 16.5 -17.99 % 16.5 -17.99 % % 99.7 1- 5.6% 1 16.5 -17.99 49 % 11 – 16.49 % 11 – 16.49 % 11 – 16.49 % 11 – 16.49 % %11 94–.616.49 1 – 11% 99 % 5.5-10.99 % 5.5-10.99 % 5.5-10.99 % 5.5-10.99 % %9 9.01-5.5 % 5.5-10.99 5.5 % < 5.5 % < 5.5 % < 5.5 % < 5.5 % % 5.5 << 5.5 % 20% 60% 00% 8 %60% 06 %80% 04 %20% 02 % 0 20% %80% 40% 0% 0% 40% 20% 40% 60% 80% 0% 40% 0% 1990 June 17, 2006 20% 60% 0% 60% 20% 80% 40% 40% 80% 60% 80% 2002 Declining cross-subsidy from the creditworthy to the credit-risky 16 Conclusions Responsible use of consumer information yields efficiencies and growth across a large number of sectors Overly-restrictive data regimes often worst of both worlds: June 17, 2006 No additional privacy protections Enforced inefficiencies 17