Unique ID: WB5

Division: INTOP
Issue Date: February 13th 2019
Last modified: February 22nd 2019
Collaborative

Analyzing data to identify indicators of corruption, fraud, or collusion in Bank-financed projects or public spending

Analyzing data to identify indicators of corruption, fraud, or collusion in Bank-financed projects or public spending

SDG: 10 - Reduced Inequalities12 - Responsible Consumption & Production16 - Peace, Justice & Strong Institutions

Can we find a methodology to analyze data to identify indicators of corruption, fraud or collusion in Bank financed projects or public spending? Can we find enough data to feed the methodology? INT will use this methodology to identify investigative leads and risk areas. We will share this methodology with partners inside and outside the Bank. The aim is to proactively detect fraud, corruption and collusion risks in Bank-financed projects. Client: INT and partners within the Bank, External anti-corruption authorities with similar objectives. The team is currently working with data scientists at the University of Cincinnati on a project done in conjunctions with OPSOR on Entity Resolution that will be integrated into the new World Bank procurement process, and with the Data Science for Social Good Fellowship at the University of Chicago on modeling of risk using procurement data and case history data.

Project Sources
Project Sources
Type Of Institution: international organization
Region: Global
Country Area: Global
Id Country Regional: global
SDG Indicators
SDG Indicators
SDG Comments: 10.5, 10.6, 12.7, 16.6,
SDG: 10 - Reduced Inequalities12 - Responsible Consumption & Production16 - Peace, Justice & Strong Institutions
Other
Other
Timeframe To Produce Indicator: NA
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