## Box 1. Theory and practice in the “Resolving Insolvency” Indicator

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### Introduction and purpose
- Insolvency legislation and reforms historically lack a proper empirical foundation; laws often designed without detailed data on system performance or application issues.
- The paper initiates development of data gathering systems to support analysis of insolvency regimes, critiques current methodologies, surveys statistical systems and country experience, and proposes guiding principles for data collection systems.
- Target audiences: governmental institutions that supervise insolvency proceedings, policy makers, insolvency practitioners and advisors, and academics.

### Conceptual framework: effectiveness, efficiency, outputs vs outcomes
- Data are valuable only within a conceptual framework; effectiveness and efficiency define scope.
- Effectiveness: achievement of the objectives of the system.
- Efficiency: relationship between inputs and outputs; achieving objectives with minimum use of resources.
- Distinction: outputs (immediate results of an activity) vs outcomes (effects connected to system objectives).

Key high-level objectives of an insolvency system:
- Primary outcome: allocation of risk among participants in a market economy in a predictable, equitable and transparent manner.
- Close second: protection and maximization of value for the benefit of all interested parties and the economy in general.
- Other possible objectives (context-dependent): preservation of enterprises or jobs.
- Efficient framework: liquidates non-viable businesses and rehabilitates viable ones in a way that minimizes costs and maximizes value; supports rehabilitation when going concern value exceeds liquidation value.

### Standards, indicators, and data
- Effective assessment requires both quantitative and qualitative elements.
- Standards: international benchmarks (UNCITRAL Legislative Guide; World Bank Principles on Effective Insolvency and Creditor Rights Systems); qualitative standards useful but not empirical.
- Indicators: transform facts into norms; design (assumptions, variables, methodology) must be careful to avoid “gaming the indicator.”
- Quantitative indicators represent broader qualities like efficiency and effectiveness through measurable variables.

### Three key quantitative indicators (Djankov et al., 2008)
- Time
  - Defined as the period from the moment the debtor defaults until a solution is found (typically liquidation or reorganization).
  - Related indicator: time to payment — estimated duration, in years, from debtor’s default to the point a secured creditor receives payment.
- Cost
  - Costs of the insolvency proceeding reported as a percentage of the value of the estate, borne by all parties.
  - Cost components: court/bankruptcy authority fees, attorney fees, insolvency administrator fees, accountant fees, notification and publication fees, assessor or inspector fees, asset storage and preservation costs, auctioneer fees, government levies, and other associated insolvency costs.
  - Costs can be included upfront or at the end of the process.
- Recovery rate
  - Measures the return that creditors receive in the insolvency process.
  - Recovery depends on time, cost, and outcome (reorganization vs piecemeal liquidation).
  - Seeks to account for loss of economic value caused by dismantling the enterprise in liquidation procedures.

### Practical implications and cautions
- Qualitative assessments are useful but insufficient; only empirical quantitative data can evidence improvements translating into increased efficiency.
- Indicator design must select variables and methodologies carefully to avoid misleading normative conclusions and perverse incentives for selective reforms.

---

### Methodology and limitations of the Doing Business resolving insolvency indicator

### Hypothetical-case methodology and revisions
- Based on a hypothetical case: insolvency of a hotel in the main business city, underpinned by standard assumptions to enable cross-country comparison.
- Insolvency specialists in each country respond to the hypothetical case; responses are the source for the numerical information in the Doing Business report.
- Revised in 2014 to include a list of qualitative questions based on parts of the international insolvency standard.
- Not based on actual, empirical case-level data; results are derived from hypothetical-case responses and converted into numerical parameters that have “the appearance of actual data.”

### Key methodological assumptions (explicit)
- Too many creditors to reach an out-of-court restructuring agreement.
- Recovery rate calculated only with reference to the secured creditor; all other claims are ignored.
- Secured creditor is fully secured: value of its claim coincides exactly with value of collateral; no unencumbered assets.
- By definition, liquidation cannot yield more than a 70 percent recovery rate for the secured creditor.
- If there is a reorganization plan, the recovery rate is always 100 percent.

### Biases and limitations identified
- Assumptions bias results in favor of systems that give total preeminence to secured creditors.
- Methodology favors systems that privilege reorganization plans over other solutions (including sale as a going concern), irrespective of specific economic outcomes.
- Indicator limitations require caution in reliance for assessing insolvency-system performance.

### Need for empirical data and richer metrics
- Time, cost, and recovery rate indicators should rely on actual data, including recovery rates for all categories of creditors.
- Actual data permit granular assessments to identify bottlenecks or misuse of procedures.
- Data-backed findings enhance objectivity, credibility, and accountability.
- Data collection supports but does not replace expert analysis; statistics cannot fully capture context, history, externalities, or country-specific circumstances.

---

### Judicial statistics: uses, constraints, and examples

### Purpose and limitations
- Primary purpose: evaluate judicial performance, principally to monitor duration of proceedings.
- Judicial statistics are generally ill-suited to assess insolvency-system efficiency because:
  - Data collected mainly to monitor duration (staffing, court processes).
  - Length of proceeding may reflect legal or internal process gaps; procedural filings contain valuable information but courts often lack capacity to extract substantive data (debtor characteristics, size of debt, costs, recovery rates) without training or IT investment.
- Constraints: limited court budgets and lack of skilled personnel.

### CEPEJ standardization and timeliness
- CEPEJ provides data and reports to monitor compliance with Article 6 of the European Convention on Human Rights and key indicators to monitor court efficiency.
- Every two years CEPEJ circulates explanatory notes; national correspondents reply and validate responses.
- Iterative survey and validation is time-consuming; latest CEPEJ report published in October 2018 is based on 2016 data, and only 17 countries provided information about their insolvency systems.
- Two-year lag limits usefulness for timely decision-making.

### Country change indicators (country followed by change)
- UK (+8%)
- China (+10%)
- Romania (+7%)
- Morocco (+8%)
- Taiwan (+5%)
- Poland (+5%)
- Singapore (+5%)
- New Zealand (+2%)
- Slovakia (+3%)
- Chile (+5%)
- Japan (+1%)
- Sweden (+2%)
- Hong-Kong (+1%)
- Canada (0%)
- Finland (-2%)
- Switzerland (0%)
- Spain (0%)
- Estonia (0%)
- Bulgaria (-5%)
- Australia (0%)
- Russia (0%)
- Norway (-3%)
- South Korea (0%)
- Colombia (-3%)
- US (-2%)
- Luxembourg (-4%)
- Austria (-2%)
- Ireland (-4%)
- South Africa (-3%)
- Turkey (-4%)
- Germany (-4%)
- Belgium (-5%)
- The Netherlands (-5%)
- Lithuania (-5%)
- Latvia (-5%)
- Brazil (-7%)
- France (-7%)
- Portugal (-7%)
- Greece (-10%)
- Italy (-10%)
- Czech Rep (-7%)
- Denmark (-9%)
- Hungary (-12%)

### Examples and limitations of national judicial statistics
- Specialized insolvency courts (e.g., USA, Thailand) facilitate isolation of insolvency cases and measurement.
- United States:
  - Since 1948, AOUSC provides annual statistical information on federal court caseloads.
  - AOUSC reports include total number of bankruptcy filings in each judicial district by type of proceeding and by predominant nature of the debt (consumer or business).
  - Integrated Database (IDB) provides counts of filed, pending, and terminated bankruptcy cases by judicial district.
  - Limitation: database focuses on counts and lacks information on size of debt or debtor characteristics.
  - Private initiatives (e.g., Professor LoPucki’s database) attempt to fill gaps for large corporate cases.
  - BAPCPA required compilation of consumer debtor statistics (28 U.S.C. §159(b)); BAPCPA report includes assets, liabilities, income and expenses but data are self-reported and not validated by courts.

### Sources of substantive insolvency data
- Valuable sources: initial insolvency petitions; confirmed reorganization plans; final insolvency administrator’s report (particularly for costs and creditor recovery rates).
- Extraction requires court clerks or software for electronic filings.

### Statistics of insolvency regulators and other authorities (selected features)
- Insolvency regulators often produce detailed reports focused on oversight and professionals; examples include:
  - England and Wales: Insolvency Service produces quarterly insolvency statistics by type of procedure; Companies House data used for further analysis.
  - Australia: ASIC prepares extensive statistical reports based on compulsory filings by insolvency administrators, including size of company; nominated causes of failure; assets, liabilities and deficiency; unpaid employee entitlements; secured creditors; unpaid taxes; remuneration of administrators.
  - Ireland: Insolvency Service of Ireland (ISI) reports on personal insolvency procedures covering case management, outcomes, amount of debt (secured and unsecured), gender, and geographic distribution.
  - United States: U.S. Trustee produces statistical reports focused on enforcement, fraud cases, and system integrity.
  - Colombia: Superintendencia de Sociedades combines adjudicating authority and regulator roles, enabling comprehensive data on proceedings and administrator performance.
  - Spain: Registro mercantil compiles detailed statistical studies including economic characteristics, plan proposals, median recovery for unsecured creditors, and duration segmented by phases—enabled by deposit of financial statements though extraction is arduous.

### Surveys on management of non-performing loans (NPLs)
- Bank surveys collect detailed information from primary sources on resolution strategies, time, costs, and outcomes.
- Banking supervisors are well placed to administer surveys with input from banks and private experts.
- Effectiveness depends on survey design and ability to account for system-specific features.

---

### Box 3. The Italian survey on the management of NPLs

### Overview and sample
- Conducted in 2015 and published by the Bank of Italy in February 2016.
- Sample: 24 large banking groups holding 78 percent of NPLs in the system.
- Scope: NPLs being liquidated or restructured at the end of the 2014.
- Assessment windows:
  - In-court procedures: recovery rate measured in the period after insolvency proceedings were opened (assessment concluded in 2014).
  - Restructured debts: first four years of the restructuring examined to assess recovery.

### Survey design and content
- Quantitative questions collected:
  - Characteristics of credit recovery and restructuring procedures (amounts in-court and out-of-court, average age of procedures at end of 2014; collateral).
  - Final recovery rate by mechanism (out-of-court agreements, bankruptcies, arrangements with creditors, foreclosures) and percentage of initial credit recovered each year after procedure start.
  - Changes in debtor companies’ position in the four years following restructuring start.
- Qualitative questions captured banks’ opinions on factors negatively affecting credit recovery (court backlogs, procedural complexity, lack of public creditors’ participation, professionals’ fees, access to interim financing, creditor coordination) and internal organization and credit recovery costs.

### Key results and policy implications
- Results distinguished outcomes by:
  - (i) in-court vs out-of-court recovery;
  - (ii) collateralized vs non-collateralized debt;
  - (iii) year of initiation of recovery processes.
- Indicated need for measures to shorten procedures and regulatory changes enabling formal closure of procedures.
- Revealed banks sometimes lacked integrated information systems for NPL management, affecting effectiveness of resolution strategies.
- Provided empirical justification for policy actions based on differentiated recovery mechanisms and outcomes.

### Recommendations for NPL survey design
- Design surveys considering national laws and practices and include resolution methods at minimum:
  - Informal restructuring,
  - Sale of loans,
  - Enforcement (by type of collateral),
  - Insolvency procedures.
- Record sequence when several methods attempted to assess redundancy or abuse.
- Balance granularity against time/cost for banks to respond; banks should use internal systems for responses.
- Surveys can be one-off or periodic; follow-up surveys can assess impact of regulatory or legal reforms.

### Advantages and limitations of bank surveys
- Advantages:
  - Provide a complete picture of methods used to deal with problem loans, including informal restructurings and sales of NPLs.
  - Allow comparisons of relative use and efficiency of resolution methods.
  - Best method to assess creditor costs since information comes directly from banks.
  - Permit targeted qualitative questions answered by professional creditors.
- Limitations:
  - Capture system only from perspective of selected financial institutions.
  - Costly to replicate; lack of continuity complicates assessment over time.

### Core insolvency statistics and measurement guidance (from Box 3)
- Required specific statistics:
  - Quantity of insolvency cases and outcomes (reorganization, sale as a going concern, piecemeal liquidation).
  - Number of cases closed because of lack of assets (“no-asset cases”).
  - Frequency of out-of-court restructurings (may require registry or voluntary disclosure).
- Core indicators:
  - Time: duration from commencement to confirmation of reorganization plan or liquidation; in reorganizations, projected payments and monitoring mechanisms.
  - Cost: liquidation costs (court fees, administrator remuneration, experts' fees, asset storage, auctioneer fees, government levies); reorganization costs (court fees, administrator and advisor fees, ongoing operational costs).
  - Recovery rate: secured creditors (compare claim amount and collateral valuation at initiation); privileged creditors (distinguish classes such as workers, tax, social security); unsecured creditors (recovery after claim verification).
- Statistical treatment:
  - Use median values where heterogeneity suggests medians are more informative than averages.
  - Compile data into statistical reports using established methodology.
- Comparative frequency measures:
  - Ratio of number of insolvency cases to number of registered companies.
  - Ratio between number of companies with NPLs and number of insolvency cases.
  - Ratio between GDP and number of insolvency cases (caveat: may overstate use during GDP contraction).
  - Alternative: measure overall value of claims and assets of companies in insolvency combined with number of procedures to account for enterprise size differences.

---

### Box 5. Data collection in the EU draft Directive on preventive restructuring frameworks

### Scope of the draft Directive (art. 29) data requirement
- Member states required to collect data annually based on a standard methodology and transmit it to the EC; objective is compilation of reliable annual statistics. Text subject to negotiations and may be modified before adoption.
- Data to be collected and aggregated nationally include:
  - (a) number of procedures initiated, pending and resolved, broken down by:
    - (i) preventive restructuring procedures,
    - (ii) insolvency procedures such as liquidation procedures,
    - (iii) procedures leading to a full discharge of debt for natural persons;
  - (b) length of the procedure from initiation to payout, separate by types of procedures (preventive restructuring procedure, insolvency procedure, discharge procedure);
  - (c) share of each type of outcome within each restructuring or insolvency procedure, including number of procedures applied for but not commenced for lack of available funds in the debtor's estate;
  - (d) average costs of each procedure awarded by the judicial or administrative authority, in euro;
  - (e) recovery rates for secured and unsecured creditors separately, as well as number of procedures with zero or no more than two percent total recovery rate in respect of each type of procedure referred to in point (a);
  - (f) number of debtors subject to procedures referred to in point (a)(i) who within three years from the conclusion of such procedures are subject to either of the procedures referred to in points (a)(i) and (a)(ii);
  - (g) number of debtors who, after having undergone a procedure referred to in point (a)(iii), are subject to another such procedure or another procedure referred to in point (a).

- For point (e): recovery rates shall be after costs and anonymised data fields shall show both recovery rate and recovery rate linked to time until recovery.

### Required breakdowns and disaggregation
- Member States shall break down statistics by:
  - (a) the size of the debtors involved, by number of workers;
  - (b) whether debtors are natural or legal persons;
  - (c) in respect of discharge and where such distinction is made under national law, whether the procedures concern only entrepreneurs or all natural persons.

### Use of flowcharts, milestones, and data collection points
- Flowcharts map insolvency proceedings to define start/end, decisions, documents and data required; basic flowcharts provide templates for data collection.
- Example milestones:
  - commencement and closure of an insolvency case;
  - initiation of process and moment where creditors receive payment;
  - time from presentation of an insolvency petition to judicial decision accepting that petition;
  - time to resolve an appeal on that decision.
- Data collection points (examples):
  - Insolvency application (debtor or creditors);
  - Court decision to open/terminate proceedings (including appeals);
  - Reports of insolvency administrators;
  - Valuation reports;
  - Avoidance actions; liability actions;
  - Decisions regarding executory contracts;
  - Disclosure statements in reorganization and liquidation plans.

### Additional data to collect and analyse
- Economic and social data:
  - Businesses: enterprise size; turnover; number of employees; years in operation; industry; number of creditors and value of claims; classes of claims (secured claims, tax and social security claims, labor claims); causes of insolvency.
  - Individuals: age; family status; gender; profession; ethnicity; amount of debt; classes of claims; previous insolvency processes.
- Additional legal data and statistics:
  - Type of legal entity;
  - Dismissed cases with breakdown of reasons for dismissal;
  - Numbers of voluntary and involuntary cases;
  - Repeated insolvency filings (within 3/5 years after closing of previous process);
  - Percentage of reorganizations over total insolvency cases;
  - Success of reorganization plans / liquidation cases opened after failure of attempted reorganization;
  - Survival of businesses (successful reorganizations and sales as a going concern);
  - Number of fraudulent cases and identification of elements of fraud;
  - Number of special cases (enterprise group insolvency; cross-border cases) and related data.
- Textual/descriptive information can be collected but requires standardized forms and processing is more challenging than numerical data.

### Design considerations, trade-offs and implementation guidance
- Tailor data collection to national legal architecture; selection of data, milestones and collection points depends on process design.
- Corporate insolvency systems are more complex; household insolvency data collection is comparatively simpler.
- Consider debt enforcement action data (e.g., mortgage enforcement) where relevant.
- Use existing infrastructures where possible (insolvency regulator, judiciary, statistical agency).
- Create special insolvency registries where feasible to design categorized data collection tools.
- Trade-offs:
  - Exhaustive data collection may exceed capacity and be difficult to implement.
  - Legal constraints require anonymization and respect for data protection, banking and commercial secrecy.
  - Prioritization of data needs conserves resources and facilitates analysis.

### Role of data in policy, impact assessment and reform
- Insolvency data feed performance assessments and system design; empirical data are indispensable for assessing effectiveness and efficiency and identifying legal and economic issues.
- Impact assessments aim to identify problems, causes, policy options (including “doing nothing”), and advantages/disadvantages; they may include economic, social, environmental implications and stakeholder views.
- Continuous data collection creates a feedback loop: data → analysis → insolvency law design → post-reform data collection to test effectiveness (Data and Design Loop).
- Quality data are essential for meaningful impact assessments; reforms without empirical backing risk being inefficient or detrimental.

### Conclusions and recommendations (Box 5)
- Data collection is necessary for assessment of insolvency systems; even advanced economies need to increase quality of insolvency-related information.
- Formulating sound insolvency policies requires relevant data and careful empirical analysis.
- States can build data systems on existing infrastructures; where deficient, create specific mechanisms mindful of capacity and resources.
- Capacity and budgetary constraints should not be insurmountable barriers; rationalization of existing sources can improve quality.
- Prioritize data points to balance resource use, respect anonymization and legal constraints, and enable robust empirical assessment of insolvency frameworks.

*Source: wp1927 - Box 1. Theory and practice in the “Resolving Insolvency” Indicator; Box 3; Box 5.*

### Box 1. Theory and practice in the “Resolving Insolvency” Indicator ____________________________ 8

### Box 1. Theory and practice in the “Resolving Insolvency” Indicator

### Introduction
- Insolvency legislation and reforms have long been designed without a proper empirical foundation; insolvency law is often designed without detailed data on actual system performance or application issues.
- Qualitative assessments exist (compliance with international standards or customized indicators), but there are virtually no assessments of insolvency systems based on empirical data.
- The paper represents a first step toward developing data gathering systems to support analysis of insolvency regimes and provides a critique of current methodologies, surveys statistical systems and country experience, and proposes guiding principles for data collection systems.
- Target audiences: governmental institutions that supervise insolvency proceedings, policy makers, insolvency practitioners and advisors, and academics.

### Conceptual framework for the use of data
- Data are necessary but only valuable within a conceptual framework; the concepts of effectiveness and efficiency define the scope of data collection.
- Effectiveness: achievement of the objectives of the system.
- Efficiency: relationship between inputs and outputs; achieving objectives with minimum use of resources.
- Distinction between outputs (immediate results of an activity) and outcomes (effects produced by outputs, connected to system objectives).

Key high-level objectives of an insolvency system (as framed in the source):
- Primary outcome: allocation of risk among participants in a market economy in a predictable, equitable and transparent manner.
- Close second: protection and maximization of value for the benefit of all interested parties and the economy in general.
- Other possible explicit objectives depending on political circumstances: preservation of enterprises or jobs.
- Efficient insolvency framework: liquidates non-viable businesses and rehabilitates viable ones in a way that minimizes costs and maximizes value; supports rehabilitation when going concern value exceeds liquidation value.

### Standards, indicators, and data
- Effective assessment requires both quantitative and qualitative elements; some system features must be assessed qualitatively.
- Interaction of standards, indicators, and data underpins analysis.

Standards
- International standards reflect best practices endorsed by the international community (UNCITRAL Legislative Guide on Insolvency Law and the World Bank Principles on Effective Insolvency and Creditor Rights Systems).
- Assessments of compliance with the international standard can be conducted as standalone Insolvency and Creditor Rights ROSCs or as part of a financial sector assessment (FSAP).
- Qualitative standards-based assessments are valuable but are not empirical and broad standards do not guarantee system effectiveness.

Indicators
- Indicators provide a general, standardized assessment using specific data formats; they transform facts into norms and are thus partly normative.
- Careful design of indicators (assumptions, variables, methodology) is essential to avoid “gaming the indicator.”
- Indicators can be qualitative or quantitative; qualitative indicators often resemble standards and risk being prescriptive without full legitimacy.
- Quantitative indicators use measurable variables to represent broader qualities like efficiency and effectiveness.

### Three key quantitative indicators (Djankov et al., 2008)
- The source identifies three key indicators that inform a general assessment of insolvency efficiency: time, cost, recovery rate.

Time
- Defined as the period from the moment the debtor defaults until a solution is found (typically liquidation or reorganization).
- Related indicator: time to payment — estimated duration, in years, from debtor’s default to the point a secured creditor receives payment.

Cost
- Includes costs of the insolvency proceeding reported as a percentage of the value of the estate, borne by all parties.
- Cost components listed: court/bankruptcy authority fees, attorney fees, insolvency administrator fees, accountant fees, notification and publication fees, assessor or inspector fees, asset storage and preservation costs, auctioneer fees, government levies, and other associated insolvency costs.
- Costs can be included upfront or at the end of the process.

Recovery rate
- Measures the return that creditors receive in the insolvency process.
- Recognizes that recovery depends not only on time and cost but also on the outcome (reorganization vs. piecemeal liquidation) because a debtor’s enterprise is generally worth more as a going concern.
- Seeks to account for the loss of economic value caused by dismantling the enterprise in liquidation procedures.

### Practical implications and cautions
- Qualitative assessments (standards) are useful but insufficient; only empirical quantitative data can evidence improvements in system quality translating into increased efficiency.
- Indicator design must carefully select variables and methodologies to avoid misleading normative conclusions and to minimize incentives for selective reforms aimed solely at improving indicator metrics rather than underlying system quality.

*Source: wp1927 - Box 1. Theory and practice in the “Resolving Insolvency” Indicator*

### Box 1. Theory and practice in the “Resolving Insolvency” Indicator

### Box 1. Theory and practice in the “Resolving Insolvency” Indicator

### Methodology of the Doing Business resolving insolvency indicator
- The indicator is based on a hypothetical case: the insolvency of a hotel located in the main business city of the country, underpinned by a set of standard assumptions to facilitate cross-country comparison.
- Insolvency specialists from each country provide responses to the hypothetical case, and these responses are the source for the numerical information in the Doing Business report.
- The indicator was revised in 2014 to include a list of qualitative questions based on parts of the international insolvency standard.
- The indicator is not based on actual, empirical case-level data; results are derived from the hypothetical-case responses and converted into numerical parameters that have “the appearance of actual data.”

### Key methodological assumptions (explicit)
- There are too many creditors to reach an out-of-court restructuring agreement.
- The recovery rate is calculated only with reference to the secured creditor in the case; all other claims are ignored.
- The secured creditor is fully secured, such that the value of its claim coincides exactly with the value of the collateral; there are no unencumbered assets.
- By definition, liquidation cannot yield more than a 70 percent recovery rate for the secured creditor.
- If there is a reorganization plan, the recovery rate is always 100 percent.

### Biases and limitations identified
- The assumptions create a bias in favor of systems that give total preeminence to the interests of secured creditors, to the detriment of other creditors or parties.
- The methodology favors systems that privilege reorganization plans over other solutions (including the sale of the business as a going concern), irrespective of the specific economic outcome.
- The inherent limitations require caution in reliance on the indicator for assessing insolvency-system performance.

### Need for empirical data and richer metrics
- Indicators such as time, cost, and recovery rate should rely on actual data; gathering actual data on time, cost, and recovery rates (for all categories of creditors) would permit a more reliable assessment of efficiency.
- Data collection enables more granular assessments than simple indicators: it can identify bottlenecks or misuse of procedural mechanisms.
- Findings backed by reliable data offer objectivity, credibility, and accountability.
- Data collection and statistics support analytical work but do not replace expert and independent analysis; statistics cannot fully capture context, history, externalities, or country-specific circumstances.

### Current data sources to assess insolvency systems — overview and purposes
- Existing mechanisms collect insolvency-related data, but none fully meet needs for assessing and designing insolvency systems.
- Purposes of insolvency data collection may include:
  - (i) general statistics on the number and type of insolvency proceedings for monitoring economic trends;
  - (ii) resolution of non-performing loans and the rate of credit recovery by banks;
  - (iii) measuring effectiveness and efficiency of the insolvency system (including impact of reforms against a baseline);
  - (iv) other purposes (e.g., budgetary resource allocation, key performance indicators for courts).
- Data collected for one purpose may overlap with others (for example: time indicators relevant to both insolvency law efficiency and judicial statistics).

### General insolvency statistics: practice and common traits
- Most advanced economies collect general insolvency statistics as part of national economic health analysis (new business establishment, survival rates, insolvency filings).
- Common traits of national insolvency statistics:
  - Focus on the economy rather than the functioning of the legal system: data on industry, region, years in operation, type of legal entity, turnover, employment.
  - Reports may include length of cases and proportions ending in liquidation versus reorganization.
- Methodologies often involve statistical agencies retrieving data from courts using structured questionnaires.

### Selected national examples (Box 2) — features highlighted
- France (Bank of France): monthly data on enterprise insolvencies, year-to-year variation, economic sector, SME vs large enterprise segmentation, percentage of claims in insolvency as of total exposures declared by banks; methodology includes criteria for size and sector; all types of procedures covered; successive procedures treated as separate.
- Germany (Destatis): monthly data on number of insolvency cases differentiated by business, consumer, self-employed, decedents’ estates, and value of expected claims; annual breakdown by sector and state; online databank details dismissals for insufficiency of assets and accepted debt settlement plans; provides some summary analysis like recovery rate in various proceedings.
- Spain (INE): quarterly data distinguishing enterprise and consumer cases, initiation type (creditor/debtor), ordinary vs simplified procedures, legal form, economic sector, quarterly and yearly variation, enterprise size (assets and liabilities), employees, years in operation, region, and presentation of a plan proposal at initiation; methodology based on a standardized form with variables such as number of proceedings presented, number of bankruptcy orders, tax identification number, type and voluntariness of procedure, existence and content of proposed agreements, active mass (assets), and passive mass (liabilities).
- South Africa (Stats SA): aggregates and publishes monthly data on compulsory and voluntary liquidations for companies and closed corporations by industry; provides data on individual or partnership sequestrations.

### Limitations of national insolvency statistics for policy making
- National statistics are high-level and intended to give a broad-brush view of economic health; gross numbers of liquidations or restructurings do not reveal how legal and institutional frameworks are performing.
- Lack of consistency across countries (different data types, periodicities: monthly, quarterly, annually; differing legal definitions) complicates cross-country comparisons.
- Within-country time series can be consistent, but legal changes can produce discontinuities.

### Use of national statistics by private-sector analysts
- Some financial institutions produce global research based on national statistics (examples cited):
  - Euler Hermes conducts economic research and provides analysis on commercial risks, including insolvency trends (Insolvency Heat Map).
  - Creditreform issues analytical reports on corporate insolvencies in Western and Eastern Europe drawing on national statistics and proprietary analysis.

*Source: wp1927 - Box 1. Theory and practice in the “Resolving Insolvency” Indicator.*

### 2. Judicial statistics

### 2. Judicial statistics

### Purpose and limitations of judicial statistics
- Primary purpose: evaluate judicial performance, principally to monitor the duration of proceedings.
- Judicial statistics are generally ill-suited to assess the efficiency of the insolvency system because:
  - Data are principally collected to monitor duration of proceedings (staffing, court processes).
  - Length of proceeding may reflect legal or internal process gaps that delay decisions—these bottlenecks are of most interest for legal reform.
- Procedural filings with the courts contain valuable information (initial petitions, confirmed reorganization plans, insolvency administrator’s report), but courts may lack capacity to extract and analyze substantive data (debtor characteristics, size of debt, costs, recovery rates) without:
  - training of court personnel, and/or
  - investment in automated IT systems and specialized applications.
- Constraints: limited court budgets and lack of skilled personnel.

### CEPEJ, standardization, and timeliness
- CEPEJ provides:
  - data and reports for Europe to monitor compliance with Article 6 of the European Convention on Human Rights (right to a fair trial within a reasonable period),
  - key indicators to monitor court efficiency, including insolvency cases,
  - “GOJUST Guidelines” to aid member States in organizing data collection.
- Process:
  - Every two years CEPEJ circulates an explanatory note about required data to promote uniformity and consistency.
  - Member States appoint national correspondents to reply to the survey instrument and clarify/validate responses.
  - When discrepancies occur cycle-to-cycle, CEPEJ Secretariat engages with national correspondents; CEPEJ may exclude data if figures are too disparate.
- Standardization challenges:
  - National correspondents may interpret questions differently; definitions (e.g., “insolvency”, “insolvency proceedings”) may differ across judicial systems.
  - Iterative survey dissemination, collection, and validation is time-consuming.
  - Example: latest CEPEJ report published in October 2018 is based on 2016 data, and only 17 countries provided information about their insolvency systems.
  - Two-year lag in producing data limits usefulness for timely decision-making.

- Country change indicators (as presented in source graphics; country followed by change in parentheses):
  - UK (+8%)
  - China (+10%)
  - Romania (+7%)
  - Morocco (+8%)
  - Taiwan (+5%)
  - Poland (+5%)
  - Singapore (+5%)
  - New Zealand (+2%)
  - Slovakia (+3%)
  - Chile (+5%)
  - Japan (+1%)
  - Sweden (+2%)
  - Hong-Kong (+1%)
  - Canada (0%)
  - Finland (-2%)
  - Switzerland (0%)
  - Spain (0%)
  - Estonia (0%)
  - Bulgaria (-5%)
  - Australia (0%)
  - Russia (0%)
  - Norway (-3%)
  - South Korea (0%)
  - Colombia (-3%)
  - US (-2%)
  - Luxembourg (-4%)
  - Austria (-2%)
  - Ireland (-4%)
  - South Africa (-3%)
  - Turkey (-4%)
  - Germany (-4%)
  - Belgium (-5%)
  - The Netherlands (-5%)
  - Lithuania (-5%)
  - Latvia (-5%)
  - Brazil (-7%)
  - France (-7%)
  - Portugal (-7%)
  - Greece (-10%)
  - Italy (-10%)
  - Czech Rep (-7%)
  - Denmark (-9%)
  - Hungary (-12%)

### Examples and limitations of national judicial statistics (including the United States)
- Few jurisdictions assign insolvency cases exclusively to specialized insolvency courts; where they do (e.g., USA, Thailand), it is easier to isolate insolvency cases and measure courts’ workload and performance.
- United States:
  - Since 1948, by law, the Administrative Office of the U.S. Courts (“AOUSC”) provides annual statistical information on federal court caseloads.
  - AOUSC reports include total number of bankruptcy filings in each judicial district by type of proceeding (e.g., liquidation under Chapter 7; reorganization under Chapter 11) and by predominant nature of the debt (consumer or business).
  - AOUSC publishes numbers of filed, pending, and terminated bankruptcy cases by judicial district; time series provides general filing trends.
  - This information is part of the Integrated Database (IDB) of the Federal Judicial Center.
  - Limitations: the database focuses on counts of cases filed, terminated, and pending, and does not provide additional information such as size of the debt or characteristics of the debtor.
  - Private initiatives (e.g., Professor LoPucki’s database at UCLA) have attempted to fill data gaps for large corporate insolvency cases.
  - Longstanding proposals to improve judicial bankruptcy statistics include using standard forms and gathering data from electronic filing/electronic case management; concerns about expense constrain progress.
  - Initiatives to collect consumer bankruptcy data have had limited success.
  - Under the Bankruptcy Abuse Prevention and Consumer Protection Act of 2005 (BAPCPA), the AO was required to compile, analyze, and publish statistics on consumer debtors annually (28 U.S.C. §159(b)); the BAPCPA report includes debtors’ assets, liabilities, income and expenses but the data are self-reported and not validated by the courts.

### Sources of insolvency data and data collection
- Valuable substantive data sources in insolvency proceedings:
  - initial insolvency petitions,
  - confirmed reorganization plans,
  - final insolvency administrator’s report (particularly valuable for costs and creditor recovery rates).
- Extraction of substantive data requires court clerks (for paper filings) or software applications (for electronic filings).

### Statistics of insolvency regulators and other authorities
- Insolvency regulators frequently produce statistical reports focused on oversight functions and insolvency professionals (e.g., number of appointments, administrator reports, disciplinary actions). Such reports often provide more specific and relevant insolvency information than general judicial statistics.
- Level of detail varies by jurisdiction. Examples:
  - England and Wales:
    - Insolvency Service produces quarterly insolvency statistics by type of procedure for companies and individuals.
    - Further analysis extracts scope of company activity from Companies House.
  - Australia:
    - Australian Commission (ASIC) prepares extensive statistical reports based on compulsory filings by insolvency administrators.
    - Data include: (i) size of the company; (ii) nominated causes of failure; (iii) possible misconduct and documentary evidence; (iv) assets, liabilities and deficiency; (v) unpaid employee entitlements; (vi) secured creditors; (vii) unpaid taxes and charges; (viii) unsecured creditors; and (ix) remuneration of administrators.
  - Ireland:
    - Insolvency Service of Ireland (ISI) produces reports focused on personal insolvency procedures (DRN, DSA, PIA), covering case management, outcomes, type of debts, profile of applicants, number of cases, amount of debt (secured and unsecured), gender, and geographical distribution.
  - United States:
    - The U.S. Trustee produces statistical reports in addition to judicial bankruptcy statistics, focusing on enforcement actions and fraud cases and the U.S. Trustee role in ensuring efficiency and integrity of the bankruptcy system.
  - Colombia:
    - Superintendencia de Sociedades combines adjudicating authority and insolvency regulator roles, enabling data and reports that cover general insolvency proceedings and performance of insolvency administrators; statistics show characteristics of insolvent businesses (size, number of employees, location).
  - Spain:
    - Registro mercantil produces detailed statistical studies including economic characteristics of insolvent enterprises (size, sector, age, viability, solvency), distinction between debtor- and creditor-commenced cases, changes in management control, details about reorganization plans, median recovery for unsecured creditors, and duration segmented by phases—enabled by deposit of financial statements and official notifications to the registry, though extraction is arduous and time-consuming.

### Surveys on management of non-performing loans (NPLs)
- Bank surveys focus on use of debt resolution tools by banks and can assess effectiveness and efficiency of debt resolution mechanisms, including insolvency processes.
- Advantages of bank surveys:
  - collect detailed information from primary sources,
  - triage data by resolution strategy, time, costs, and other factors affecting debt resolution,
  - allow comparison of a bank’s NPL stock and work-out strategy with peers.
- Effectiveness of findings depends on survey design and ability to account for system-specific features.
- Banking supervisors are best positioned to administer bank surveys, with input from banks and private sector experts.

*Source: wp1927 - 2. Judicial statistics (PDF chapter).*

### Box 3. The Italian survey on the management of NPLs

### Box 3. The Italian survey on the management of NPLs

### Overview of the survey
- Conducted in 2015 and published by the Bank of Italy in February 2016.
- Sample: 24 large banking groups holding 78 percent of NPLs in the system.
- Scope: NPLs being liquidated or restructured at the end of the 2014.
- Assessment windows:
  - In-court procedures: recovery rate measured in the period after insolvency proceedings were opened (assessment concluded in 2014).
  - Restructured debts: the first four years of the restructuring were examined to assess recovery of claims.

### Survey design
- Included both quantitative and qualitative aspects.
- Quantitative questions collected data on:
  - Characteristics of credit recovery and restructuring procedures (amounts involved in-court and out-of-court procedures, average age of the procedures at the end of 2014; collateral).
  - Final recovery rate by different mechanisms used (e.g., out-of-court agreements, bankruptcies, arrangements with creditors, and foreclosures) and the percentage of initial credit recovered in each year after the procedure was started.
  - Changes in debtor companies’ position in the four years following the start of the restructuring procedure.
- Qualitative questions sought banks’ opinions on factors negatively affecting credit recovery (e.g., court backlogs, procedural complexity, lack of public creditors’ participation in restructuring, professionals’ fees, access to interim financing, and creditor coordination issues) and enquired about internal organization and credit recovery costs.

### Key results and policy implications
- Results distinguished outcomes by:
  - (i) debt subject to in-court recovery procedures vs. out-of-court;
  - (ii) collateralized vs. non-collateralized debt;
  - (iii) year of initiation of recovery processes.
- Indicated the need for:
  - Measures to shorten procedures.
  - Regulatory changes enabling formal closure of procedures.
- Revealed that banks’ responses sometimes reflected lack of integrated information systems for NPL management, which impacted effectiveness of NPL resolution strategies.
- Provided justification for policy actions based on empirical differentiation of recovery mechanisms and outcomes.

### Recommendations for designing bank NPL surveys
- Carefully design surveys considering national laws and practices and the different mechanisms for debt resolution.
- Ensure resolution methods covered include at least:
  - Informal restructuring,
  - Sale of loans,
  - Enforcement (by type of collateral),
  - Insolvency procedures.
- Where several resolution methods were attempted, record the sequence of attempts to assess redundancy or abuse.
- Weigh the optimal granularity of collected data against time and cost for banks to respond and the survey’s objective.
- Banks should use their own internal systems to produce their responses.
- Surveys can be one-off or regular/periodic; follow-up (more limited/targeted) surveys can assess the impact of regulatory measures or legal reforms.

### Advantages and limitations of bank surveys
- Advantages:
  - Provide a complete picture of methods used to deal with problem loans (including informal restructuring agreements and sales of NPLs, often absent from insolvency statistics).
  - Allow comparisons of relative use and efficiency of resolution methods.
  - Best method for assessing the cost to creditors of each mechanism since information is obtained directly from banks.
  - Allow inclusion of qualitative and targeted questions answered by professional creditors.
- Limitations:
  - Capture the system only from the perspective of selected financial institutions, limiting assessment of general debt collection functioning.
  - Costly to replicate and lack of continuity complicates assessment of insolvency system performance over time.

### Connection to specific insolvency statistics and broader data needs
- Existing data sources (general insolvency statistics, judicial statistics, insolvency regulator reports, NPL surveys) have different objectives and no single source suffices for comprehensive evaluation of insolvency regimes.
- Specific insolvency statistics are needed to assess overall effectiveness, including:
  - Quantity of insolvency cases and their outcomes (reorganization, sale as a going concern, piecemeal liquidation).
  - Number of insolvency cases closed because of lack of assets (“no-asset cases”).
  - Frequency of out-of-court restructurings (requires registry of agreements or voluntary disclosure).
- Core indicators required to measure insolvency system efficiency:
  - Time: duration from commencement to confirmation of a reorganization plan or liquidation; in reorganizations, projected payments in the plan and monitoring mechanisms are relevant.
  - Cost:
    - Costs of liquidation: court/bankruptcy authority fees, insolvency administrator remuneration, experts' fees, asset storage and preservation costs, auctioneer fees, government levies.
    - Costs of reorganization: court fees, fees of insolvency administrators and advisors, and ongoing operational costs (can be assessed from company financial statements).
  - Recovery rate:
    - Secured creditors: measure by comparing claim amount and valuation of collateral at initiation (or first verification); evaluate satisfaction of the secured portion.
    - Privileged creditors: distinguish among creditor classes; privileged claims (e.g., workers, tax, social security) affect recovery available to unsecured creditors.
    - Unsecured creditors: recovery determined by disproportion between estate value and total claims; measure how the system affects unsecured recovery after claim verification.
- Statistical treatment and granularity:
  - Use appropriate statistical measures (median values can be more informative than averages due to heterogeneity between large complex and small cases).
  - Compile data into statistical reports using an established methodology.
- Comparative measurement approaches for frequency of insolvency use:
  - Ratio of number of insolvency cases to number of registered companies.
  - Ratio between number of companies with NPLs and number of insolvency cases.
  - Ratio between GDP and number of insolvency cases (caveat: may overstate use during GDP contraction).
  - Alternative: measure overall value of claims and assets of companies in insolvency combined with number of procedures to account for enterprise size differences.

*Source: Box 3, "The Italian survey on the management of NPLs," wp1927.*

### Box 5: Data collection in the EU draft Directive on preventive restructuring

### Box 5: Data collection in the EU draft Directive on preventive restructuring frameworks

### Scope of the draft Directive (art. 29) requirement
- Member states required to collect data annually based on a standard methodology and transmit it to the EC; objective is the compilation of reliable annual statistics. Text subject to negotiations and may be modified substantially before adoption.
- Data to be collected and aggregated nationally by member states include:
  - (a) the number of procedures which were initiated, pending and resolved, broken down by:
    - (i) preventive restructuring procedures,
    - (ii) insolvency procedures such as liquidation procedures,
    - (iii) procedures leading to a full discharge of debt for natural persons;
  - (b) the length of the procedure from initiation to payout, separate by types of procedures (preventive restructuring procedure, insolvency procedure, discharge procedure);
  - (c) the share of each type of outcome within each restructuring or insolvency procedure, including the number of procedures applied for but not commenced for lack of available funds in the debtor's estate;
  - (d) the average costs of each procedures awarded by the judicial or administrative authority, in euro;
  - (e) the recovery rates for secured and unsecured creditors separately, as well as the number of procedures with zero or no more than two percent total recovery rate in respect of each type of procedure referred to in point (a);
  - (f) the number of debtors subject to procedures referred to in point (a)(i) who within three years from the conclusion of such procedures are subject to either of the procedures referred to in points (a)(i) and (a)(ii);
  - (g) the number of debtors who, after having undergone a procedure referred to in point (a)(iii) of this paragraph, are subject to another such procedure or another procedure referred to in point (a) of this paragraph.
- For point (e): recovery rates shall be after costs and anonymised data fields shall show both recovery rate and recovery rate linked to time until recovery.

### Required breakdowns and disaggregation
- Member States shall break down the statistics by:
  - (a) the size of the debtors involved, by number of workers;
  - (b) whether debtors are natural or legal persons;
  - (c) in respect of discharge and where such distinction is made under national law, whether the procedures concern only entrepreneurs or all natural persons.

### Use of flowcharts, milestones, and data collection points
- Insolvency proceedings can be mapped with flowcharts to define start/end, decisions, documents and data required; basic flowcharts provide templates for data collection.
- Milestones (examples):
  - commencement and closure of an insolvency case;
  - initiation of process and moment where creditors receive payment (payments in liquidation or schedule of payments under reorganization plan);
  - time from presentation of an insolvency petition to judicial decision accepting that petition;
  - time to resolve an appeal on that decision.
- Data collection points (examples where relevant information can be gathered):
  - Insolvency application (by the debtor or by creditors)
  - Decision of the court to open and to terminate the proceedings (including appeals)
  - Reports of insolvency administrators
  - Valuation reports
  - Avoidance actions; liability actions
  - Decisions regarding executory contracts
  - Disclosure statements in reorganization and liquidation plans

### Examples of jurisdictional flowcharts referenced
- Figure 3: Basic Flowchart of a Typical Insolvency Process (stylized example).
- Figure 4: Flowchart for Chapter 11 Reorganization (USA) — includes items such as First Day Orders; Preparation of plan (120d -180d); Disclosure statement; Voting on the plan (by classes); Court Confirmation; Plan Implementation; Appeal; Dismissal; Liquidation.
- Figure 5: Flowchart for Corporate Resolution Process (India) — includes items such as Application (Debtor/Financial Creditor/Operational Creditor); NCLT Decision; Appeal (10d); Moratorium; Appt Interim RP; Committee of creditors 30d; Resolution plan (Debtor/Creditor); Liquidation; Implementation.

### Additional data to collect and analyse
- Economic and social data:
  - For businesses: enterprise’s size; turnover; number of employees; years in operation; industry; number of creditors and value of claims; classes of claims (especially, secured claims, tax and social security claims, labor claims); causes of the insolvency situation.
  - For individuals: age; family status; gender; profession; ethnicity; amount of debt; classes of claims; previous insolvency processes.
- Additional legal data and statistics:
  - Type of legal entity;
  - Dismissed cases, with a breakdown of the different reasons for dismissal;
  - Numbers of voluntary and involuntary cases;
  - Repeated insolvency filings (within 3/5 years after closing of the previous insolvency process);
  - Percentage of reorganizations over the total of insolvency cases;
  - Success of reorganization plans / liquidation cases opened after the failure of an attempted reorganization;
  - Survival of businesses (combining successful reorganization plans and sales of enterprises as a going concern);
  - Number of fraudulent cases, and identification of elements of fraud;
  - Number of special cases (enterprise group insolvency cases; cross-border insolvency cases) and related data.
- Textual/descriptive information can be collected but requires standardization in forms and reports; processing text information is considerably more challenging than numerical data.

### Design considerations, trade-offs and implementation guidance
- Tailor data collection mechanisms to national specifications: selection of data, milestones and collection points depend on legal architecture of insolvency process.
- Corporate insolvency systems present greater design difficulties due to multiple procedures and complexity; household insolvency data collection is comparatively simpler but depends on detail required.
- Consideration of creditor rights system may require data on debt enforcement actions (e.g., mortgage enforcement cases).
- Capacity and resource constraints influence sophistication; use existing infrastructures where possible (insolvency regulator, judiciary, statistical agency or other authorities).
- Creation of special insolvency registries offers opportunity to design categorized data collection tools.
- Trade-offs:
  - Virtually exhaustive data collection is possible in theory but may exceed capacity and face implementation challenges.
  - Legal constraints require respect for data protection rules, banking and commercial secrecy; anonymization of data is essential.
  - Prioritization of data needs conserves resources and facilitates analysis.

### Role of data in policy, impact assessment and reform
- Insolvency data feed into performance assessments and the design of insolvency systems; empirical data are indispensable for assessing effectiveness and efficiency and identifying legal and economic issues.
- Impact assessments in law reform:
  - Aim to identify problems, causes, policy options (including “doing nothing”), and advantages/disadvantages of options; may include economic, social, environmental implications and stakeholder views.
  - Impact assessments are widely used in other fields but remain rare and underdeveloped in insolvency reform primarily due to lack of hard data.
- Continuous collection and analysis of data create a feedback loop: data → analysis → insolvency law design → post-reform data collection to test effectiveness (Data and Design Loop).
- Quality data are essential for meaningful impact assessments; reforms without empirical backing risk being inefficient or detrimental.

### Conclusions and recommendations
- Collection of data is necessary for assessment of insolvency systems; even advanced economies need to increase quality of insolvency-related information.
- Formulating sound insolvency policies requires relevant data and careful empirical analysis.
- States can build data systems on existing infrastructures; where deficient, create specific mechanisms mindful of capacity and resources.
- Capacity and budgetary constraints should not be insurmountable barriers; rationalization of existing sources can improve quality.
- Prioritize data points to balance resource use, respect anonymization and legal constraints, and enable robust empirical assessment of insolvency frameworks.

*Source: Box 5, "Data collection in the EU draft Directive on preventive restructuring frameworks," wp1927.*

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*Source: wp1927 - References*

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_Source: https://www.imf.org/-/media/files/publications/wp/2019/wp1927.pdf_