WCCR 2014_PERC 100714_Final_1(1)
- 2. Impact of Private Credit Bureaus and Comprehensive Reporting on Consumer Credit Market Structure
- 3. Impact of Private Credit Bureaus and Comprehensive Reporting on Consumer Credit Market Structure Michael Turner President PERC Title 3
- 4. Who is ? •A non-partisan, non-profit policy research and development institute devoted to increasing financial inclusion using information solutions. 4 About PERC
- 5. Most economies share data • To share, or not to share credit information is no longer the question – Nearly three-quarters surveyed in the World Bank’s Doing Business 2012, have either one or more private credit bureaus or a public credit registry – Natural response to evidence of importance of credit information sharing – Credit sharing institutions seen as key part of a nation’s financial infrastructure • There has been an increasing trend toward establishment of private credit bureaus – Most private bureaus have been established in the last two decades – Evidence that Private Credit Bureaus increase private credit extension more than public credit registries: Jappelli, Tullio Pagano (2002), PERC (2014) 5
- 6. 6 16 5 8 21 36 0 5 10 15 20 25 30 35 40 Pre 1970 1970-79 1980-89 1990-99 2000-09 Establishment of First Private Credit Bureau in a Nation Private Credit Bureau Establishment Source: GFDR 2013: Credit Reporting Database
- 7. 7 Increasingly hurdles come from lender fears: • How might full-file reporting impact bank concentration? • What are the impacts of private credit bureau competition? • How might the ownership structure of private credit bureaus impact credit reporting? • What are the impacts of particular regulations or regulatory environments on private credit bureaus and data sharing? Private Credit Bureau Establishment Source: GFDR 2013: Credit Reporting Database
- 8. 8 New PERC Study The Impacts of Information Sharing on Competition in Lending Markets Released: October 2014 Examines impacts of shifts to full-file credit reporting on banking concentration Re-examines credit reporting impacts on lending
- 9. 9 New PERC Study Motivation Motivation for Research • Lenders are comfortable with sharing negative information • Lenders have expressed concern that sharing positive data Lenders concerns/fears from sharing positive data: • Crème skimming by competitors • Loss of monopoly over their customers’ data • Increased competition resulting in reduced shares and profits • Other lenders / foreign lenders can make better use of full-file data
- 10. 10 New PERC Study Motivation Given that hurdle to credit reporting is increasingly the fear of lenders, we decided to look at their preconceptions through the following:
- 11. The Impacts of Information Sharing on Competition in Lending Markets 11 • Data – Compiled data from several sources, such as Global Financial Development Database (World Bank), World Development Indicators (World Bank), and Doing Business – Used C3 (share of assets held by the largest three banks), C5 (share of assets held by the largest five banks), and the Lerner Index (a measure of market power in the banking market) created from Bankscope data to measure banking concentration and market power. – Indicator of transition to full-file reporting created using Doing Business, GFDD data – Period covered: 1997-2011 • Methodology – Average and Median Changes of Banking Concentration / Market Power – Linear regressions – Panel Regressions (with and without country fixed effects)
- 12. Key Results 12 Shifts to full-file credit reporting are not associated with meaningful changes in bank concentration/market power • No large or statistically significant changes in bank concentration or market power were found during or following credit-sharing reform for countries that shifted to full-file credit sharing. • This is true controlling for per capita income, market entry barriers, in a linear regression or in panel regression framework (with and without country fixed effects)
- 13. Key Results 13 Shifts to full-file credit reporting are not associated with meaningful changes in bank concentration/market power • The shifts we saw 1 to 5 years out were slight, and the direction wasn't at all discernible. Nor did we see any pattern if we take barriers to foreign entry into account. • Why didn't we see any real shifts? One reason may be that the market for lending expands, reducing the need to 'poach'. In short, the game isn't zero-sum
- 14. Key Results 14 -4.0% -3.0% -2.0% -1.0% 0.0% 1.0% 2.0% 3.0% Avg. Change in C3 Median Change in C3 Avg. Change in C3 Median Change in C3 Avg. Change in C3 Median Change in C3 Avg. Change in C3 Median Change in C3 Avg. Change in C3 Median Change in C3 1 year past change 2 years past change 3 years past change 4 years past change 5 years past change Average Change in Bank Concentration Following Full-file Change
- 15. Key Results 15 Change in Bank Concentration by degree of Entry Barriers -6% -4% -2% 0% 2% 4% 6% 8% 10% 12% Avg. Change in C3 Median Change in C3 Avg. Change in C3 Median Change in C3 Avg. Change in C3 Median Change in C3 Avg. Change in C3 Median Change in C3 Avg. Change in C3 Median Change in C3 1 year past change 2 years past change 3 years past change 4 years past change 5 years past change High Entry Barriers Low Barriers to Entry
- 16. Key Results 16 Consistent with past findings, greater information sharing is associated with increased private sector lending • Private credit bureau are associated with higher rates of private sector lending as a share of GDP, by 24 to 40 percentage points. • For economies that shift to full-file sharing, the boost to private sector lending is 16 percentage points from Year 5 following the transition onward. Drivers of this may be improved and more efficient underwriting and risk management made possible with richer data and the opening up of new market segments.
- 17. Key Results 17 Interpretations / Implications • Credit sharing rules/agreements may exclude prescreening or prospective marketing. This helps reduce the possibility of poaching. • Credit sharing is a two-way street. A bank can also use the full-file credit information for its own customer acquisition purposes. • Lenders may all adapt to the new environment helping keep their relative shares of the market. The transition to full-file data sharing usually takes years, consequently, there is time to acclimate during the transition and the transition itself may not be as radical as feared by lenders. • As consumer credit markets grow, lenders expand their base by lending more to new clients more efficiently. A growing pie with little reduction in shares
- 18. Key Results 18 Other Findings… There has been a global trend to overall banking concentration. However, such market concentration changes result from a long list of factors. To the extent that private credit bureaus and comprehensive/full-file credit reporting might be one component in changing bank concentrations, it appears it would be small and overwhelmed by other factors.
- 19. 19 New PERC Study Credit Bureaus in Emerging Markets: Overview of Ownership & Regulatory Frameworks Released: September 2014 Examines impacts of private credit bureau ownership structures Examines Credit Reporting Regulatory Frameworks
- 20. 20 Ownership
- 21. 21 Stage Examples of Services Stage 1 Database, Provision of Basic Data Stage 2 Credit Reports, Alerts and Some Add-On services Stage 3 Initial Score and Decision Tools, Initial Custom Analytics Stage 4 Fraud & Identity Management, Marketing Services & Collections Management, Commercial Credit Report Stage 5 Consumer Reports, Consumer Scores Credit Monitoring Consumer Education Stage 6 Auto, Utility, Telco Solutions, Rental Screening, Employment Screening Healthcare, Small Business Insurance, Government Solutions Very mature scoring, Decision Tools, and Custom Analytics Stage 7 Big Data Solutions, Peer to peer lending, Equity Financing Equity valuation, Secondary Market, and Macro Factors Based Models Stages of Credit Bureau Development
- 22. 22 Phase Description Early / Initial Build Phase Bank/Data furnisher ownership can be used to develop data sharing, as well as revenues Middle / Scale Phase Transitions away from core data of owners, benefit of bank ownership decreases and becomes a drag on development, begins to focus more on new data sources and value added services Mature / Optimal Phase Independent credit bureau(s) are optimal, proper incentives to serve all users, has data furnishers and customers across many segments, most revenue comes from value added services Ideal Transition for Bureaus that Begin as Furnisher Owned
- 23. 23 Private bureau ownership by independent third parties (not data furnishers or data users) is seen as the optimal ownership structure to enable long-term bureau and credit information sharing development. However, many different private bureau ownership structures and not all perform as well over time.
- 24. 24 3rd-Party (Independent) Some Degree of Data Furnisher Ownership General Type of Data Furnisher Ownership No direct or little practical ownership Minority Data User- Furnisher Ownership Association (Majority) Ownership Majority Diffuse Data User-Furnisher Ownership Majority Concentrated Data User- Furnisher Ownership Example(s) Equifax (USA) Veda (Australia) Experian (Australia) Credit Bureau Singapore CIBIL prior to 2014 (India) Buro de Credito (Mexico) Advantages Decisions focused on earnings, bureau business and serving users Ease of acquiring data from data furnishers that are owners Disadvantages May be challenging enlisting data furnishers Bureau decisions may skew to serve interests of the data furnisher owners, which are likely a subset of all potential users. Data furnisher owners may be less willing to report to other bureaus, reducing competition and segmenting data
- 26. 26 Domain of Activity Regulated by… Government Agency Industry Code Both Data Accuracy/Integrity 16 2 5 Data Security 14 3 6 Consumer Dispute Process 17 1 5 Data User Credentialing 13 2 4 Permissible Use/Data Access 16 1 6 Domain of Regulation by Mode of Regulation PERC Survey, N=23
- 27. 27 9% 5% 5% 5% 23% 18% 36% 0% 10% 20% 30% 40% Weekly Monthly 3-4 Times per year 1-2 Times per year Yearly Less than Yearly Other Frequency of government/ regulator examination PERC Survey, N=23
- 28. 28 Responsiveness of oversight agencies to appeals PERC Survey, N=23 13% 57% 26% 4% 0% 10% 20% 30% 40% 50% 60% Very Responsive Moderately Responsive Minimally Responsive Unresponsive
- 29. 29 4% 48% 30% 17% 0% 10% 20% 30% 40% 50% 60% Very costly/cumbersome Moderately costly/cumbersome Costly/cumbersome to a minor extent Not costly/cumbersome at all PERC Survey, N=23 How costly/cumbersome is the oversight and audit process
- 30. • The regulator could socialize changes in regulation as they pertain to the impact on the operation of the company with the credit bureaus. • The laws are not sufficiently clear nor are its rules. Clarification upon request would be helpful. • The regulations should be based on business standards and self- regulation. • Regular reviews and upgrades of code in the light of technological developments. • Better understanding of the Credit Reference Agencies practices. 30 How to improve the audit process and/or make regulations more effective PERC Survey, N=23 Survey Says…
- 31. 31 Variance in regulatory approaches suggests: Policymakers and regulators in emerging markets (while surveying global practices) are developing models of regulatory implementation and oversight based on their specific concerns, needs, and capacities. …which seems entirely appropriate Finding
- 32. 32 Variance in regulatory approaches also suggests: • What works well in one market may not be ideally suited for another market; • Regulatory frameworks are organic and evolutionary; • Abundant opportunities to improve and customize rules given particular market circumstances: • APFF “Pathfinder” market; and, • WBG. Finding
- 33. 33 New PERC Study The Consequences of Heterogeneity In CRA Data Expected Release: Q1 2015 Examines impacts of data fragmentation across CRAs for lenders and consumers Forthcoming
- 34. 34 Forthcoming PERC Study • Data Fragmentation – Across financial sectors • Japan – Within financial sectors • Russia, maybe Mexico • Usually furnisher owned CRAs – Across types of data (financial vs non-financial) • NCTUE in US • Growing trend of mobile operators across world • Data Fiefdoms – Ebay, Alibaba using their own transaction data, MNOs – Regional differences in US (legacy) and voluntary reporting (big providers considering exclusive arrangements) – Can result result from lender market power, bad regulations, CRA data monopoly, desire to leverage own data (era of “Big Data”)
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