Public corruption in any form is the misuse of a public or government office for private gain. Its existence is an indication that something has gone wrong in the management of the government office. When public officials disclose their financial integrity, citizens are better equipped to assess if the government is working in their interest. In many countries, public officials are required to file periodic financial disclosure, which can be used for the prevention, detection, investigation, as well as prosecution of corrupt officials. Financial disclosure can promote accountability among public officials, reduce conflict of interest and increase citizen trust in public institutions.
While a well-functioning financial disclosure system exists in some countries, there are many countries where financial disclosure practices are either not standardized or are in a form that is difficult to use for due diligence purposes. This results in inconsistencies and inefficiencies in analyzing the data. Even in cases when data exists, information can be siloed across multiple systems, which impairs the capability of decision-makers to understand the holistic picture of a public official’s risk profile. Furthermore, many systems rely on the data provided by the public officials themselves.
To overcome these limitations, we are proposing a new standardized risk index for public officials. The Public Official Risk Index (PORI) will be developed by a three-pronged technology driven approach.
• E-Filing system for financial disclosure – Create/leverage a web-based platform for public officials to file financial disclosure and link to data from financial intelligence units, tax authorities, and other relevant agencies. Technologies like Smart contracts enabled by blockchain could be used to ensure transparency and integrity of the information, and to improve the resilience of the database. This data portal will also be used for filing case specific disclosures.
The online platform will not only make financial disclosure more transparent to everyone but will also provide details of the various financial interest of public officials and their close family members using government identity numbers or business associations. For example, PAN and AADHAR number in India. The portal will also integrate other relevant data sources such as corporate registration databases.
• Advanced data analytics for risk profiling –To corroborate and complement the data collected through the online process, we propose to leverage machine learning techniques to extract data from unconventional and unstructured data sources like social media or news outlets. The algorithm could correlate news referring to persons and entities of interest and look for link/information on these entities in several other data sources (e.g. social media, transactional databases) to create relevant networks of persons or companies which may be engaged in corrupt practices. This will also help to identify a direct and indirect conflict of interest scenarios.
Deep learning applied to structured data can also provide advantages over other analytical techniques, e.g., by providing insights which can partially compensate the lack of expertise in certain countries.
• Establish a risk framework – Develop and adopt a statistical risk rating model for public officials. The recommendation is to use ordinal logistic regression. The primary objective of this statistical modeling technique is to group public officials into distinct buckets based on risk. We could define new target variables (prominence of public office, risk of corruption associated with the jurisdiction in which an individual holds office, the duration for which they have been out of public office, etc.) or strengthen the model by augmenting additional data sources.
Thanks to these three tools, officials will be rated on a scale of risks from 1 to 5 (from least risky to most risky). This risk categorization will be used to allocate work and projects to help reduce corruption. The tool can help oversight agencies in the fight against corruption.
The proposed project will start implementing the technology solution, which is relatively the simple piece of the puzzle. During the execution of the project, we hope to identify key opportunities and challenges around people, process, cost benefits, change management etc. We will develop a well-rounded implementation model that should help decision makers understand the applicability of the system in a specific scenario.
Advantages and use cases
For procurement use cases, PORI can be used to flag risks at the contract stage, if any of the bidders or contractors belongs to companies or entities where the public official has a financial interest. The visibility of this information could help mitigate corruption risks on such projects. Once PORI sends a risk alert, relevant agencies may investigate the incident.
PORI will substantially capture corruption risks arising from a public official and it will enable preventive measures and shift the present anti-corruption regime from reactive to preventive measures.
PORI could strengthen prevention and assist with enforcement. The data may be used to create a risk profile of a project or sector, reducing the possibility of corruption. PORI will also be helpful for enforcement agencies to access all relevant data for investigations and prosecutions, international asset recovery efforts, the prosecution of illicit enrichment, and the identification of politically exposed persons . The data can be available to the public in a way that is aligned with the data protection Rule s and Regulations of the country.