Global Report: Enhancing Government Effectiveness and Transparency - The Fight Against Corruption

Page 240

PART II KEY INSTRUMENTS FOR FIGHTING CORRUPTION

CHAPTER 7 GOVTECH

its own right not reduce petty bribes, but follow-up actions may.5 However, given the aggregate nature of these cross-country indicators, measurement is not

straightforward, and therefore may confound more general associations between income levels and a general set of governance indicators.6

BOX 7.1

Brazil’s Tribunal of Accounts Robots AI can serve as a decision support tool for identifying transactions and payments ex ante that are at a high risk of fraud and corruption. However, this technology can only have an impact if it changes the behavior of relevant government personnel, in this case auditors. The Brazilian Federal Court of Accounts (Tribunal de Contas da União, “TCU”), a Brazilian Supreme Audit Institution (SAI), has implemented AI systems since 2015 to analyze the procurement processes of the federal administration. The TCU’s acronyms for the systems translate into robot names: Analysis of Bids, Contracts and Public Calls (ALICE) 4; Analysis of the Dispute in Electronic Bids (ADELE); Integrated Monitoring for Acquisition Control (MONICA); and Guidance System on Facts and Evidence for the Auditor (SOFIA). A more systematic study of auditors suggests that the solutions have not been mandatory, nor has training for auditors. The designers, however, suggested that this was part of a deliberate strategy. They believe that the auditors don’t need to be trained to use the products; if they do, something is wrong. Just as a first-time user doesn’t need to be trained to use Netflix. If the solutions use complex algorithms based on machine learning and cognitive processing, what should matter to the auditor are the results and their reliability for each purpose (Chief Data Officer). Interviews of Audit Managers suggested varying levels of use: ALICE (3/5), followed by SOFIA (2/5), ADELE (1/5) and MONICA (1/5). Most managers were ambivalent about the actual changes or implications the decision support tools brought to their work. Qualitative interviews suggested that many auditors still followed old practices, including a preference for text editors and spreadsheets. While adoption was growing, it was happening at a slow pace. Source: Neves et. al. (2019)

Use of digital technologies involves both opportunities and challenges Digital government transitions, coupled with disruptive technological change, offer both opportunities and risks for anti-corruption. Digital investments (e.g., major 5G or shifts to cloud based services)7 can lead to an increase in complexities and higher scope for corruption, as they might entail new modalities of procurement around notional services

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and data. Valuable resources, such as spectrum licenses can be a source of significant rents and consequently corruption.8 Digital realms also bring a new set of public sector vulnerabilities in terms of abuse of office and capturing illicit gains. Digital transaction platforms (including bitcoin stores) can facilitate a rapid or scaled illicit syphoning of resources. On the

Enhancing Government Effectiveness and Transparency: The Fight Against Corruption


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Box 13.6 Trade of Influence in the Judiciary

55min
pages 362-386

Box 13.5 Court User and Multi-Stakeholder Justice Surveys

3min
page 361

Box 13.3 Specialized Anti-Corruption Courts in the Philippines and Indonesia

2min
page 358

Box 13.4 International Cooperation and Mutual Legal Assistance (MLA

6min
pages 359-360

Box 13.2 Specialized Anti-Corruption Courts: Political Commitment or Implementation Gaps

2min
page 357

Box 10.1 The Extent of Corruption

2hr
pages 303-354

Box 13.1 Romania’s National Anti-Corruption Directorate (DNA

6min
pages 355-356

Box 9.2 The Beneficial Ownership Data Standard (BODS

5min
pages 291-292

Box 9.3 Key Data Questions for Policy Makers to Consider

25min
pages 293-302

Table 7.4 AP’s Transformational Technologies

53min
pages 251-270

Box 9.1 What is a Beneficial Owner?

15min
pages 286-290

Figure 8.2 Final Findings of ANI Reports between 2008 and 2019

15min
pages 279-285

Table 7.2 Major Technology Trends for Public Sector Fraud and Corruption

16min
pages 243-247

Box 6.2 The Extractive Industries Transparency Initiative (EITI

13min
pages 219-223

Table 7.3 Navigating GovTech for Public Sector Fraud and Corruption

8min
pages 248-250

Box 7.2 Singapore’s SkillsFuture Program and Fraud Detection

2min
page 241

Box 7.1 Brazil’s Tribunal of Accounts Robots

2min
page 240

Box 6.1 What Does Open Data Have to Do with Open Government?

9min
pages 216-218

Figure 6.1 Unpacking Open Government

1min
page 215

Table 5.1 Corruption in Public Services: Estimating the Magnitude of the Problem

2min
page 190

Box 4.1 Standard Operating Procedures and Internal Audit Capacities in Latin America

2min
page 166

Figure 4.3 ACD Presence and Main Transit Trade Routes

1min
page 178

Box 4.3 Donor Support to Afghanistan Customs Department

2min
page 179

Box 2.5 Transparency in Renegotiation for Public-Private Partnerships

2min
page 117

Box 3.1 About Empresas Públicas de Medellin

6min
pages 140-141

Box 3.3 The Impact of Operation Car Wash across Latin America

2min
page 145

Figure 2.7 Causes of Renegotiation, based on 48 Projects that experienced Renegotiation

5min
pages 115-116

Figure 1.2 Change in Corruption Risk Indicators as a result of the e-GP Intervention

55min
pages 75-93

Box 2.4 The Open Contracting for Infrastructure Data Standard (OC4IDS

6min
pages 102-103

Box 2.1 IFC’s Integrity Due Diligence (IDD

10min
pages 94-97

Figure 2.6 Making Infrastructure Data Useful for Planners, Implementers and Policy Makers

19min
pages 106-113

Figure 2.5 Multi-Stakeholder Working at the Project Level

2min
page 105

Box 2.2 The Evolution of Multi-Stakeholder Approaches to Accountability in Infrastructure

2min
page 99

Box 2.3 The Role of the CoST Secretariat

1min
page 100

Box 1.1 Timeline on Somali National Army Rations Re-tendering

16min
pages 68-73
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