In Latin America and the Caribbean (LAC), one in five people report experiencing or knowing of sextortion — the exchange of sex, rather than money, for a public service — in their dealings with the state. In Kenya, women seeking public services are more than four times as likely as men to be asked directly for sexual favors. Numbers like these are why anticorruption data cannot afford to be gender-blind. Corruption does not affect everyone equally.

Transparency International (TI) and Equal Rights Trust define discriminatory corruption as the point where corruption creates or exploits discrimination, disproportionately affecting women and other traditionally marginalized groups. It can take the form of gatekeeping through networks, unequal demands for money or sexual favors, or higher risks of retaliation. Reliable, disaggregated, experience‑based data play a central role in designing anticorruption policy that responds to how corruption intersects with discrimination and limits access to services, justice, and opportunities including jobs and economic mobility.

Corruption perception indices helped put corruption on the development agenda, but experience-based data makes it actionable by showing where corruption occurs, how people and firms encounter it, and who is most affected. The World Bank Group led the way in advancing this approach through governance and anticorruption surveys, which has since been expanded by organizations including the Praia Group and UNODC. These surveys ask households, firms, and public officials directly about their own experiences with corruption, rather than relying on general perceptions.

Disaggregated, experience-based data has deepened our understanding of corruption—revealing its many forms (The Many Faces of Corruption), how its impacts vary across groups, and why tailored solutions are needed. It has also brought hidden patterns to light, including gendered and discriminatory corruption.

At a panel on harnessing data for inclusive and effective anticorruption efforts during the most recent Conference of the State Parties to the UN Convention against Corruption (COSP11), representatives,  from statistical offices, anticorruption agencies, international organizations, and civil society examined how better data can drive more inclusive and effective anticorruption action.

Main takeaways include:

• Repeated, standardized surveys identified high‑risk institutions over time.
• Informed training and legal review and transparent survey processes strengthened credibility and encouraged use of data or
• Gender-disaggregated surveys uncovered sextortion risks that general corruption surveys missed. 

Sextortion illustrates why targeted, disaggregated data matter. Researcher Ortrun Merkle describes it as a gendered abuse of power at the intersection of corruption and sexual violence, with risks shaped by poverty, insecurity, and access to services. Transparency International’s Global Corruption Barometer surveys show the scale of the problem. In Latin America and the Caribbean, one in five people report experiencing or knowing of sextortion in public services. Evidence from LAC and the Middle East and North Africa also shows that sextortion remains underreported, underscoring the need for survivor-safe data that identifies who is affected, where it occurs, and through which services.
 

Different approaches to measure and address sextortion: The experience of Ghana, Kenya, Nigeria

Panelists also shared country experiences demonstrating how better data is helping governments identify corruption risks and target reforms.

In Ghana, a recurring 2024–2025 panel survey conducted by the Ghana Statistical Service and partners found that women and persons with disabilities faced higher bribery rates than the national average. Between survey waves, the share of women reporting exchanges of sexual favors rather than money for a public service rose from 6.6% to 17%, a sextortion signal that conventional bribery surveys would have missed.

In Kenya, the government used a mixed-method, data‑driven approach that combined constitutional reporting, outcome‑based budgeting, parliamentary oversight, and the 2025 National Gender & Corruption Survey, disaggregated by age, gender, disability, income, locality. The survey found that 3.4 percent of women, compared with 0.8 percent of men, had been directly asked for sexual favors in exchange for a public service, with risks concentrated among young, unemployed, and lower-income women in counties near Nairobi. These findings informed targeted training and disciplinary measures for public officers, plus a legal review to explicitly criminalize sextortion.

In Nigeria, successive national surveys backed by strong data governance showed declines in some contact rates and increases in reporting. UNODC‑supported analysis also found that men were more  exposed to monetary bribe demands, while women faced disproportionate exposure to sexual corruption in particular contexts. Even so, awareness outpaces disclosure: 41 percent of respondents believe sextortion happens frequently, yet most remain uncomfortable reporting it — underscoring why safe, confidential reporting channels matter as much as measurement itself.

Although these countries used different data-collection approaches, their experiences point to a common set of lessons for practitioners:

1) Measure explicitly and regularly. Include sextortion modules and gender and disability disaggregation in corruption surveys and administrative datasets; run annual or semiannual surveys to track trends and evaluate reforms. Given the sensitivity of sextortion, use a survivor‑centered, do‑no‑harm approach, with confidential and where feasible anonymous, responses, trained enumerators, and safeguards against stigma or retaliation.

2) Institutionalize open data. Publish anonymized microdata, metadata, and process reports in machine‑readable formats so that media, civil society, and researchers can analyze and use the evidence. For sensitive topics like sextortion, this means data aggregated by ministry, service, or geographic area — never at the individual level — so it protects survivors while still showing where the problem is worst.

3) Target high‑risk services. Use sector‑level evidence—such as health, education, licensing, justice, and social protection—to co‑design survivor-safe reporting channels, strengthen supervision, and apply sanctions.

4) Align prevention with equality. Connect integrity and equality indicators to ensure that  reforms address both corruption and discrimination that citizens face. For example, pairing corruption indicators with inequality measures such as the Gini coefficient can show whether anticorruption reforms are also narrowing — or widening — the gap between groups.

5) Communicate for uptake.  Highlight progress and gaps, and use stories  to show how discriminatory corruption affects people and why inaction is costly.

Effective anticorruption policies begin with evidence that reflects people’s lived experiences. Disaggregated, experience-based data reveal who is most affected, where risks are concentrated, and how governments can target reforms more effectively. As countries negotiate new commitments under the UN Convention against Corruption, the experiences of Ghana, Kenya, Nigeria, and other partners show that inclusive data lead to more inclusive, and ultimately more effective, anticorruption policies.

Source : World Bank