Corruption Perceptions Index

Last updated

Map of the Corruption Perceptions Index, 2024, as scored by Transparency international. A higher score indicates greater transparency (i.e., less corruption). The score ranges are:
Less corrupt
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90-100
80-89
70-79
60-69
50-59
More corrupt
40-49
30-39
20-29
10-19
0-9
No data Map of Countries by Corruption Perceptions Index (2024).svg
Map of the Corruption Perceptions Index, 2024, as scored by Transparency international. A higher score indicates greater transparency (i.e., less corruption). The score ranges are:
Less corrupt
  90–100
  80–89
  70–79
  60–69
  50–59
More corrupt
  40–49
  30–39
  20–29
  10–19
  0–9
  No data

The Corruption Perceptions Index (CPI) is an index published annually by Transparency International, a German registered association, since 1995. [1] It scores and ranks countries by their perceived levels of public sector [2] corruption, as assessed by experts and business executives. [3] The CPI generally defines corruption as an "abuse of entrusted power for private gain". [4] :2

Contents

From 1995 to 2011, the index was scored on a scale of 10 to 0. Since 2012, the Corruption Perceptions Index has been ranked on a scale from 100 (very clean) to 0 (highly corrupt).

Of the 180 countries ranked in the 2024 CPI, published in February 2025, the top scorers included; Denmark (90), Finland (88), Singapore (84), while those perceived as the most corrupt included South Sudan (8), Somalia (9) and Venezuela (10). [5]

Although widely used as a key indicator of corruption, the CPI does not capture all forms of corruption. Perceptions about corruption may differ from actual levels of corruption and index focuses solely on the public sector. For a more comprehensive picture, the CPI should be used alongside other assessments. [6]

Methods

The CPI methodology, revised in 2012, enables consistent comparison of corruption perceptions across countries and years. It involves four stages: selecting data sources, rescaling them to a uniform 0–100 scale, aggregating the results, and estimating uncertainty. [4] :7

Selection of source data

The goal of the data selection is to capture expert and business leader assessments of various public sector corruption practices. This includes bribery, misuse of public funds, abuse of public office for personal gain, nepotism in civil service, and state capture. Since 2012 CPI has taken into account 13 different surveys and assessments [7] from 12 different institutions. [4] :1 The institutions are:

Countries need to be evaluated by at least three sources to appear in the CPI. [4] :7 The CPI measures the perception of corruption due to the difficulty of measuring absolute levels of corruption. [8] Transparency International commissioned the University of Passau's Johann Graf Lambsdorff to produce the CPI. [9] Early CPIs used public opinion surveys. [4] :7

Rescaling source data

In order for all data to be aggregated into the CPI index, it is first necessary to carry out standardization during which all data points are converted to a scale of 0–100. Here, 0 represents the most corruption and 100 signifies the least. Indices originally measuring corruption inversely (higher values for higher corruption) are multiplied by -1 to align with the 0–100 scale.

In the next step, the mean and standard deviation for each data source based on data from the baseline year are calculated (the "impute" command of the STATA statistical software package is used to replace missing values). Subsequently, a standardized z score is calculated with an average centered around 0 and a standard deviation of 1 for each source from each country. Finally, these scores are converted back to a 0–100 scale with a mean of approximately 45 and a standard deviation of 20. Scores below 0 are set to 0, and scores exceeding 100 are capped at 100. This ensures consistent comparability across years since 2012.

Aggregating the rescaled data

The resulting CPI index for each country is calculated as a simple average of all its rescaled scores that are available for the given country, while at least three data sources must be available in order to calculate the index. The imputed data is used only for standardization and is not used as a score to calculate the index.

Reporting a measure for uncertainty

The CPI score is accompanied by a standard error and confidence interval. This reflects the variation present within the data sources used for a particular country or territory.

CPI and economic growth

Research papers published in 2007 and 2008 examined the economic consequences of corruption perception, as defined by the CPI. The researchers found a correlation between a higher CPI and higher long-term economic growth, [10] as well as an increase in GDP growth of 1.7% for every unit increase in a country's CPI score. [11] Also shown was a power-law dependence linking higher CPI score to higher rates of foreign investment in a country.

The research article "The Investigation of the Relationship between Corruption Perception Index and GDP in the Case of the Balkans" [12] from 2020 confirms the positive co-integration relationship in Balkan countries between CPI and GDP and calculates the affecting rate of CPI GDP as 0.34. Moreover, the direction of causality between CPI and GDP was identified from CPI to GDP and, according to this, the hypothesis that CPI is the cause of GDP was accepted.

The working paper Corruption and Economic Growth: New Empirical Evidence [13] from 2019 emphasizes that many previous studies used the CPI for their analysis before 2012 (when the index was difficult to compare over time) and therefore may be biased. At the same time, it presents new empirical evidence based on data for 175 over the period 2012-2018. The results show that corruption is negatively associated with economic growth (Real per capita GDP decreased by around 17% in the long-run when the reversed CPI increased by one standard deviation).

CPI and justice

As reported by Transparency International, there is a correlation between the absence of discrimination and a better CPI score. That indicates that in countries with high corruption, equal treatment before the law is not guaranteed and there is more space for discrimination against specific groups. [14]

It seems that the country's justice system is an important protector of the country against corruption, and conversely, a high level of corruption can undermine the effectiveness of the justice system. Furthermore, as noted by the United Nations Office on Drugs and Crime (UNODC), justice systems around the world are overburdened with large caseloads, chronically underfunded, and in need of more financial and human resources to properly fulfill their mandates. This, in combination with increasing outside interference, pressures and efforts to undermine judicial independence, results in the inability of justice systems to control corruption. The latest edition of the World Justice Project's Rule of Law Index, which shows that in the past year, justice systems in most countries exhibited signs of deterioration, including increasing delays and lower levels of accessibility and affordability, also serves as evidence of the urgency of the situation. Conversely, because corruption implies disproportionate favoring of some groups or individuals over others, it prevents people from accessing justice. For example, a person may rely on personal contacts to change a statutory process.

As shown in the Corruption Perception Index 2023, there is also a positive relationship between corruption and impunity. Countries with higher levels of corruption are less likely to sanction public officials for failing to adhere to existing rules and fulfill their responsibilities. A positive relationship was also shown between corruption and access to justice. [15]

Other phenomena and indices

Thesis The Relationship Between Corruption And Income Inequality: A Crossnational Study, [16] published in 2013, investigates the connection between corruption and income inequality on a global scale. The study's key finding is a robust positive association between income inequality (measured by the Gini coefficient) and corruption (measured by the CPI).

A study from 2001 [17] shows that the more affected by corruption, the worse a country's environmental performance. Measuring national environmental performance according to 67 variables, the closest match is with the 2000 TI Corruption Perceptions Index, which revealed a 0.75 correlation with the ranking of environmental performance.

A 2022 study titled "Statistical Analyses on the Correlation of Corruption Perception Index and Some Other Indices in Nigeria" [18] investigated the relationship between the Corruption Perception Index in Nigeria and other relevant indices. These other indices included the Human Development Index (HDI), Global Peace Index (GPI), and Global Hunger Index (GHI). The result from the analysis carried out on the standardized data set shows that a positive linear relationship exists among all the variable considered except for CPI and GPI holding HDI and GHI constant which indicates a negative linear relationship between them.

A study investigating the relationship between public governance and the Corruption Perception Index [19] found that aspects of public administration like voice and accountability, political stability, and rule of law significantly influence how corrupt a country is perceived to be. This suggests that strong governance practices can be effective in reducing corruption.

Criticism

The CPI has received significant criticism related to its conceptual and methodological limitations, and bias towards devoloped countries.

According to political scientist Dan Hough, three flaws in the Index include: [20]

Media outlets frequently use the raw numbers as a yardstick for government performance, without clarifying what the numbers mean. The local Transparency International chapter in Bangladesh disowned the index results after a change in methodology caused the country's scores to increase; media reported it as an "improvement". [21]

In a 2013 Foreign Policy article, Alex Cobham argues that the CPI reflects an elite bias in popular perceptions of corruption, potentially contributing to a vicious cycle and incentivizing inappropriate policy responses. Cobham writes, "the index corrupts perceptions to the extent that it's hard to see a justification for its continuing publication." [22] He noted that "many of the staff and chapters" at Transparency International, "protest internally" over concerns about the index. The original creator of the index, Johann Graf Lambsdorff, withdrew from work on the index in 2009, stating that he was "no longer available for doing the Corruption Perceptions Index." [23]

Recent econometric analyses that have exploited the existence of natural experiments on the level of corruption and compared the CPI with other subjective indicators have found that, while not perfect, the CPI is argued to be broadly consistent with one-dimensional measures of corruption. [24]

In the United States, many lawyers advise international businesses to consult the CPI when attempting to measure the risk of Foreign Corrupt Practices Act violations in different nations. This practice has been criticized by the Minnesota Journal of International Law, which wrote that since the CPI may be subject to perceptual biases it therefore should not be considered by lawyers to be a measure of actual national corruption risk. [25]

Transparency International also publishes the Global Corruption Barometer, which ranks countries by corruption levels using direct surveys instead of perceived expert opinions, which has been under criticism for substantial bias from the powerful elite. [22]

Transparency International has warned that a country with a clean CPI score may still be linked to corruption internationally. For example, while Sweden had the 3rd best CPI score in 2015, one of its state-owned companies, TeliaSonera, was facing allegations of bribery in Uzbekistan. [26]

Scoring

As stated by Transparency International in 2024, [27] the level of corruption stagnates at the global level. Only 28 of the 180 countries measured by the CPI index have improved their corruption levels over the last twelve years, and 34 countries have significantly worsened. No significant change was recorded for 118 countries. Moreover, according to Transparency International, over 80 percent of the population lives in countries whose CPI index is lower than the global average of 43, and thus corruption remains a problem that affects the majority of people globally.

Among the states with the most significant decline in the CPI are authoritarian states such as Venezuela, as well as established democracies that have been rated high for a long time, such as Sweden (decrease of 7, the current score 82) or Great Britain (decrease 3, current score 71). Other countries experiencing sharp declines include Sri Lanka, Mongolia, Gabon, Guatemala, and Turkey. In contrast, the most significant improvements in the CPI score over the last twelve years were recorded by Uzbekistan, Tanzania, Ukraine, Ivory Coast, the Dominican Republic and Kuwait.

2024 scores

Below are the scores for each country in the Corruption Perceptions Index. The scores reflect a country's transparency (i.e., the opposite of corruption), while the bar length demonstrates corruption. [28]

Legend

ScoresPerceived as less corruptPerceived as more corrupt
since 2012100–9089–8079–7069–6059–5049–4039–3029–2019–109–0
#Nation or TerritoryScore (2024) Rank
Change (2023)
1Flag of Denmark.svg Denmark
90
Steady2.svg
2Flag of Finland.svg Finland
88
Steady2.svg
3Flag of Singapore.svg Singapore
84
Increase2.svg 2
4Flag of New Zealand.svg New Zealand
83
Decrease2.svg 1
5Flag of Luxembourg.svg Luxembourg
81
Increase2.svg 5
5Flag of Norway.svg Norway
81
Decrease2.svg 1
5Flag of Switzerland (Pantone).svg  Switzerland
81
Increase2.svg 1
8Flag of Sweden.svg Sweden
80
Decrease2.svg 2
9Flag of the Netherlands.svg Netherlands
78
Decrease2.svg 1
10Flag of Australia (converted).svg Australia
77
Increase2.svg 4
10Flag of Iceland.svg Iceland
77
Increase2.svg 9
10Flag of Ireland.svg Ireland
77
Increase2.svg 1
13Flag of Estonia.svg Estonia
76
Steady2.svg
13Flag of Uruguay.svg Uruguay
76
Increase2.svg 5
15Flag of Canada (Pantone).svg Canada
75
Decrease2.svg 3
15Flag of Germany.svg Germany
75
Decrease2.svg 6
17Flag of Hong Kong.svg Hong Kong
74
Decrease2.svg 2
18Flag of Bhutan.svg Bhutan
72
Increase2.svg 8
18Flag of Seychelles.svg Seychelles
72
Increase2.svg 4
20Flag of Japan.svg Japan
71
Decrease2.svg 3
20Flag of the United Kingdom.svg United Kingdom
71
Increase2.svg 3
22Flag of Belgium (civil).svg Belgium
69
Decrease2.svg 6
23Flag of Barbados.svg Barbados
68
Increase2.svg 1
23Flag of the United Arab Emirates.svg United Arab Emirates
68
Increase2.svg 4
25Flag of Austria.svg Austria
67
Decrease2.svg 5
25Flag of France.svg France
67
Decrease2.svg 4
25Flag of the Republic of China.svg Taiwan
67
Increase2.svg 3
28Flag of the Bahamas.svg Bahamas
65
Increase2.svg 2
28Flag of the United States.svg United States
65
Decrease2.svg 3
30Flag of Israel.svg Israel
64
Increase2.svg 3
30Flag of South Korea.svg South Korea
64
Increase2.svg 2
32Flag of Chile.svg Chile
63
Decrease2.svg 3
32Flag of Lithuania.svg Lithuania
63
Increase2.svg 2
32Flag of Saint Vincent and the Grenadines.svg Saint Vincent and the Grenadines
63
Increase2.svg 4
35Flag of Cape Verde.svg Cape Verde
62
Decrease2.svg 5
36Flag of Dominica.svg Dominica
60
Increase2.svg 6
36Flag of Slovenia.svg Slovenia
60
Increase2.svg 6
38Flag of Latvia.svg Latvia
59
Decrease2.svg 2
38Flag of Qatar.svg Qatar
59
Increase2.svg 2
38Flag of Saint Lucia.svg Saint Lucia
59
Increase2.svg 7
38Flag of Saudi Arabia.svg Saudi Arabia
59
Increase2.svg 15
42Flag of Costa Rica.svg Costa Rica
58
Increase2.svg 3
43Flag of Botswana.svg Botswana
57
Decrease2.svg 4
43Flag of Portugal (official).svg Portugal
57
Decrease2.svg 9
43Flag of Rwanda.svg Rwanda
57
Increase2.svg 6
46Flag of Cyprus.svg Cyprus
56
Increase2.svg 3
46Flag of the Czech Republic.svg Czech Republic
56
Decrease2.svg 5
46Flag of Grenada.svg Grenada
56
Increase2.svg 3
46Flag of Spain.svg Spain
56
Decrease2.svg 10
50Flag of Fiji.svg Fiji
55
Increase2.svg 3
50Flag of Oman.svg Oman
55
Increase2.svg 20
52Flag of Italy.svg Italy
54
Decrease2.svg 10
53Flag of Bahrain.svg Bahrain
53
Increase2.svg 23
53Flag of Georgia.svg Georgia
53
Decrease2.svg 4
53Flag of Poland.svg Poland
53
Decrease2.svg 6
56Flag of Mauritius.svg Mauritius
51
Decrease2.svg 1
57Flag of Malaysia.svg Malaysia
50
Steady2.svg
57Flag of Vanuatu.svg Vanuatu
50
Decrease2.svg 4
59Flag of Greece.svg Greece
49
Steady2.svg
59Flag of Jordan.svg Jordan
49
Increase2.svg 4
59Flag of Namibia.svg Namibia
49
Steady2.svg
59Flag of Slovakia.svg Slovakia
49
Decrease2.svg 12
63Flag of Armenia.svg Armenia
47
Decrease2.svg 1
63Flag of Croatia.svg Croatia
47
Decrease2.svg 6
65Flag of Kuwait.svg Kuwait
46
Decrease2.svg 2
65Flag of Malta.svg Malta
46
Decrease2.svg 10
65Flag of Montenegro.svg Montenegro
46
Decrease2.svg 2
65Flag of Romania.svg Romania
46
Decrease2.svg 2
69Flag of Benin.svg Benin
45
Increase2.svg 1
69Flag of Cote d'Ivoire.svg Ivory Coast
45
Increase2.svg 18
69Flag of Sao Tome and Principe.svg São Tomé and Príncipe
45
Decrease2.svg 2
69Flag of Senegal.svg Senegal
45
Increase2.svg 1
73Flag of Jamaica.svg Jamaica
44
Decrease2.svg 4
73Flag of Kosovo.svg Kosovo
44
Increase2.svg 10
73Flag of East Timor.svg Timor-Leste
44
Decrease2.svg 3
76Flag of Bulgaria.svg Bulgaria
43
Decrease2.svg 9
76Flag of the People's Republic of China.svg China
43
Steady2.svg
76Flag of Moldova.svg Moldova
43
Steady2.svg
76Flag of the Solomon Islands.svg Solomon Islands
43
Decrease2.svg 6
80Flag of Albania.svg Albania
42
Increase2.svg 18
80Flag of Ghana.svg Ghana
42
Increase2.svg 10
82Flag of Burkina Faso.svg Burkina Faso
41
Increase2.svg 1
82Flag of Cuba.svg Cuba
41
Decrease2.svg 6
82Flag of Hungary.svg Hungary
41
Decrease2.svg 6
82Flag of South Africa.svg South Africa
41
Increase2.svg 1
82Flag of Tanzania.svg Tanzania
41
Increase2.svg 5
82Flag of Trinidad and Tobago.svg Trinidad and Tobago
41
Decrease2.svg 6
88Flag of Kazakhstan.svg Kazakhstan
40
Increase2.svg 5
88Flag of North Macedonia.svg North Macedonia
40
Decrease2.svg 12
88Flag of Suriname.svg Suriname
40
Decrease2.svg 1
88Flag of Vietnam.svg Vietnam
40
Decrease2.svg 5
92Flag of Colombia.svg Colombia
39
Decrease2.svg 5
92Flag of Guyana.svg Guyana
39
Decrease2.svg 5
92Flag of Tunisia.svg Tunisia
39
Decrease2.svg 5
92Flag of Zambia.svg Zambia
39
Increase2.svg 2
96Flag of The Gambia.svg Gambia
38
Increase2.svg 2
96Flag of India.svg India
38
Decrease2.svg 3
96Flag of Maldives.svg Maldives
38
Decrease2.svg 3
99Flag of Argentina.svg Argentina
37
Decrease2.svg 1
99Flag of Ethiopia.svg Ethiopia
37
Decrease2.svg 1
99Flag of Indonesia.svg Indonesia
37
Increase2.svg 16
99Flag of Lesotho.svg Lesotho
37
Decrease2.svg 6
99Flag of Morocco.svg Morocco
37
Decrease2.svg 2
104Flag of the Dominican Republic.svg Dominican Republic
36
Increase2.svg 4
105Flag of Serbia.svg Serbia
35
Decrease2.svg 1
105Flag of Ukraine.svg Ukraine
35
Decrease2.svg 1
107Flag of Algeria.svg Algeria
34
Decrease2.svg 3
107Flag of Brazil.svg Brazil
34
Decrease2.svg 3
107Flag of Malawi.svg Malawi
34
Increase2.svg 8
107Flag of Nepal.svg   Nepal
34
Increase2.svg 1
107Flag of Niger.svg Niger
34
Increase2.svg 17
107Flag of Thailand.svg Thailand
34
Increase2.svg 1
107Flag of Turkey.svg Turkey
34
Increase2.svg 8
114Flag of Belarus.svg Belarus
33
Decrease2.svg 16
114Flag of Bosnia and Herzegovina.svg Bosnia and Herzegovina
33
Decrease2.svg 6
114Flag of Laos.svg Laos
33
Increase2.svg 22
114Flag of Mongolia.svg Mongolia
33
Increase2.svg 7
114Flag of Panama.svg Panama
33
Decrease2.svg 6
114Flag of the Philippines.svg Philippines
33
Increase2.svg 1
114Flag of Sierra Leone.svg Sierra Leone
33
Decrease2.svg 6
121Flag of Angola.svg Angola
32
Steady2.svg
121Flag of Ecuador.svg Ecuador
32
Decrease2.svg 6
121Flag of Kenya.svg Kenya
32
Increase2.svg 5
121Flag of Sri Lanka.svg Sri Lanka
32
Decrease2.svg 6
121Flag of Togo (3-2).svg Togo
32
Increase2.svg 5
121Flag of Uzbekistan.svg Uzbekistan
32
Steady2.svg
127Flag of Djibouti.svg Djibouti
31
Increase2.svg 3
127Flag of Papua New Guinea.svg Papua New Guinea
31
Increase2.svg 6
127Flag of Peru.svg Peru
31
Decrease2.svg 6
130Flag of Egypt.svg Egypt
30
Decrease2.svg 22
130Flag of El Salvador.svg El Salvador
30
Decrease2.svg 4
130Flag of Mauritania.svg Mauritania
30
Steady2.svg
133Flag of Bolivia.svg Bolivia
28
Steady2.svg
133Flag of Guinea.svg Guinea
28
Increase2.svg 8
135Flag of Eswatini.svg Eswatini
27
Decrease2.svg 5
135Flag of Gabon.svg Gabon
27
Increase2.svg 1
135Flag of Liberia.svg Liberia
27
Increase2.svg 10
135Flag of Mali.svg Mali
27
Increase2.svg 1
135Flag of Pakistan.svg Pakistan
27
Decrease2.svg 2
140Flag of Cameroon.svg Cameroon
26
Steady2.svg
140Flag of Iraq.svg Iraq
26
Increase2.svg 14
140Flag of Madagascar.svg Madagascar
26
Increase2.svg 5
140Flag of Mexico.svg Mexico
26
Decrease2.svg 14
140Flag of Nigeria.svg Nigeria
26
Increase2.svg 5
140Flag of Uganda.svg Uganda
26
Increase2.svg 1
146Flag of Guatemala.svg Guatemala
25
Increase2.svg 8
146Flag of Kyrgyzstan.svg Kyrgyzstan
25
Decrease2.svg 5
146Flag of Mozambique.svg Mozambique
25
Decrease2.svg 1
149Flag of the Central African Republic.svg Central African Republic
24
Steady2.svg
149Flag of Paraguay.svg Paraguay
24
Decrease2.svg 13
151Flag of Bangladesh.svg Bangladesh
23
Decrease2.svg 2
151Flag of the Republic of the Congo.svg Congo
23
Increase2.svg 7
151Flag of Iran.svg Iran
23
Increase2.svg 2
154Flag of Azerbaijan.svg Azerbaijan
22
Steady2.svg
154Flag of Honduras (2022-present).svg Honduras
22
Steady2.svg
154Flag of Lebanon.svg Lebanon
22
Decrease2.svg 4
154Flag of Russia.svg Russia
22
Decrease2.svg 13
158Flag of Cambodia.svg Cambodia
21
Steady2.svg
158Flag of Chad.svg Chad
21
Increase2.svg 4
158Flag of the Comoros.svg Comoros
21
Increase2.svg 4
158Flag of Guinea-Bissau.svg Guinea-Bissau
21
Steady2.svg
158Flag of Zimbabwe.svg Zimbabwe
21
Decrease2.svg 9
163Flag of the Democratic Republic of the Congo.svg Democratic Republic of the Congo
20
Decrease2.svg 1
164Flag of Tajikistan.svg Tajikistan
19
Decrease2.svg 2
165Flag of the Taliban.svg Afghanistan
17
Decrease2.svg 3
165Flag of Burundi.svg Burundi
17
Decrease2.svg 3
165Flag of Turkmenistan.svg Turkmenistan
17
Increase2.svg 5
168Flag of Haiti.svg Haiti
16
Increase2.svg 4
168Flag of Myanmar.svg Myanmar
16
Decrease2.svg 6
170Flag of North Korea.svg North Korea
15
Increase2.svg 2
170Flag of Sudan.svg Sudan
15
Decrease2.svg 8
172Flag of Nicaragua.svg Nicaragua
14
Steady2.svg
173Flag of Equatorial Guinea.svg Equatorial Guinea
13
Decrease2.svg 1
173Flag of Eritrea.svg Eritrea
13
Decrease2.svg 12
173Flag of Libya.svg Libya
13
Decrease2.svg 3
173Flag of Yemen.svg Yemen
13
Increase2.svg 3
177Flag of the Syrian revolution.svg Syria
12
Steady2.svg
178Flag of Venezuela.svg Venezuela
10
Decrease2.svg 1
179Flag of Somalia.svg Somalia
9
Increase2.svg 1
180Flag of South Sudan.svg South Sudan
8
Decrease2.svg 3

List by region

The following table lists the average CPI score for each region since 2012.

Transnational corruption in states with high CPI scores

The advanced economies of Northern and Western Europe, North America, and Asia and the Pacific tend to top the rankings over the long term. This means that these countries are perceived as having a low level of corruption in the public sector. These nations also generally have well-functioning judicial systems, a strong rule of law, and political stability – all factors that contribute to perceptions of clean governance. However, while these top-ranked countries have strong domestic institutions, their commitment to fighting corruption appears to be weak when it comes to their own financial systems and regulations affecting the international environment. [30] The CPI doesn't capture transnational corruption, so corrupt foreign business practices by companies from these countries don't affect their CPI scores. The example of the Netherlands highlights this issue. Despite a high CPI score, the Netherlands has a poor record of prosecuting companies that bribe foreign officials to win contracts, as seen in the Nigerian oil bribery case. [31]

The report Exporting Corruption 2022, [32] which assesses foreign bribery enforcement in 43 of the 44 signatories to the OECD Anti-Bribery Convention, as well as China, ZAO Hong Kong, India and Singapore, reinforces this concern. It found a significant decline in foreign bribery enforcement. Only two out of 47 countries are now in active enforcement category. Other key findings were that no country is exempt from bribery by its nationals and related money laundering. Moreover, according to the report, weaknesses remain in legal frameworks and enforcement systems are not adequately disclosed by most countries information on enforcement, victim compensation is rare and international cooperation is increasing but still faces significant obstacles. This calls for a more comprehensive approach to tackling corruption, addressing both domestic and international aspects.

See also

References

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  2. "Corruption Perception Index". transparency.org. Retrieved 28 January 2020.
  3. "Corruption Perceptions Index: Frequently Asked Questions". Transparency International. 2024. Archived from the original on 3 June 2024. Retrieved 20 July 2024.
  4. 1 2 3 4 5 Corruption Perceptions Index 2010: Long Methodological Brief (PDF) (Report). Transparency International. Retrieved 30 March 2024.
  5. "CPI 2024". Transparency International. 11 February 2025. Retrieved 14 February 2025.
  6. Andy McDevitt. (2016). How-to guide for corruption assessment tools (2nd edition). U4 operated by Transparency International.
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  8. Transparency International (2010). "Frequently asked questions (FAQs)". Corruption Perceptions Index 2010. Transparency International. Archived from the original on 2 September 2011. Retrieved 24 August 2011.
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  10. Shao, J.; Ivanov, P. C.; Podobnik, B.; Stanley, H. E. (2007). "Quantitative relations between corruption and economic factors". The European Physical Journal B. 56 (2): 157. arXiv: 0705.0161 . Bibcode:2007EPJB...56..157S. doi:10.1140/epjb/e2007-00098-2. ISSN   1434-6028. S2CID   2357298.
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