Practice category: Systems and tools
Contact: Special Investigation Service (STT
Fraud risk(s) countered:
- Conflict of interest
- Avoidance or manipulation of public procurement procedures
Context and objective(s)
The Special Investigation Service (STT) was created in 1997 as the main Lithuanian anti-corruption body. It became an independent law enforcement institution in 2000 accountable directly to the President and the Parliament of the Republic of Lithuania. As a law enforcement body, it conducts criminal intelligence and investigations by detecting and investigating corruption offences, as well as developing and implementing corruption prevention measures. It is also working in anti-corruption education and awareness raising.
The STT presents its annual report to the parliament and regularly issues reports for the attention of the parliament, specific stakeholders or the general public relating to detected corruption cases or corruption risks. These reports form the basis for improving laws and regulations and also support criminal investigations.
In 2018, a new function within the STT was established: the analytical anti-corruption intelligence department. It is composed of a strategic analysis division, a tactical analysis division and an operative analysis division. Whereas the STT analytical activities previously focussed on providing operational support to criminal intelligence and investigations, the new function took a more preventive approach. Knowing that investigations are time-intensive and often costly, the function aims at detecting corruption risks before crimes and damages occur.
To serve this purpose, the STT purchased and adapted several IT systems and trained its staff in their use and programming.
The overall objective is strengthening data-driven corruption risk management by developing a big data analytics model that provides a more effective and timely identification and analysis of corruption risks in order to prevent the manifestation of corruption-related offenses. It enables the analysis of the huge amount of data available to the STT in a more efficient way and of a better quality, as well as various types of analyses, including visualization of a variety of data in different formats, that were so far not possible.
Description of the practice
The STT applied to and was granted funding under the European Anti-fraud Office’s (OLAF) HERCULE III Program with the aim of improving their analytical information system, as well as the analytical skills of the officers to detect corruption risks and its manifestation. As a result, the system helps protecting the financial interests of the Member States and the European Union from corruption. The funding of approx. 450K € was granted in December 2018.
The system was developed during the following 12 months. Its development was kicked off by three round table discussions with:
A total of 46 representatives from 24 different institutions participated in the discussions, and later on were invited to attend the international project closing seminar.
These discussions were aimed at understanding which corruption risks could be spotted early on based on the experience of the participants and the staff of the STT and which systems or practices the different institutions were already using. Through these discussions, the STT could define the technical setup of the system and learn from the knowledge and mistakes of others. The exchange also allowed the other institutions to provide the STT with information about what kind of analysis they would find useful and how the STT might be able to support them in the future.
Furthermore, the STT performed an extensive market analysis to identify existing software programs that could meet their needs without having to develop a new program. As a result, they purchased various analysis and visualization software, e.g.visual associative analytics software (IBM Cognos Analytics), geographic information system (ArcGIS), text analysis software (MaxQDA) and analytical processes management and automation software (IBM Business Automation Workflow). In order to remain independent from any providers and avoid costs for maintenance or software changes, the STT had its technical employees trained in the use and re-programming of the software programs acquired.
The entire project was run by 2 groups, the “project management executive group” and the “project working group”, with the first being responsible for the coordination and the second for the implementation. In total, approx. 15 people were involved out of which 5 represented the core working team (2 people from the analytical anti-corruption intelligence department, 2 from the IT department and 1 from the planning division).
The developed system first collects data from more than 60 different state-owned and non-public data bases (registers and information systems), including for instance information on public procurement contracts and procedures, land registers or from the EU Structural Support Computerized Information Management and Supervision System where all the financial data and administrative data relating to EU funded projects is stored, etc. The data can then be analyzed by the STT using different software programs that allow visual analyses, geographic or text analyses and thus allow to detect corruption risks and possible schemes more quickly and effectively.
The data is not screened on a regular basis for red flags, instead, the employees of the STT each have their specific area of competence they look into, e.g. health care, public procurement, territorial planning and construction, transport and communication sector, municipalities, etc. The strategic analysis division of the STT focusses on national systemic risks, the tactical analysis division is looking for risks in institutions whereas the operative analysis division addresses risks represented by individuals.
The employees run analyses on the provided data to identify relationships that impose corruption risks, test hypotheses or check for fraudulent activities previously detected in other national cases, in other countries or which are identified by means of integrating multiple data sources. If they notice a certain modus operandi, they analyse further whether it represents a one-time deviance or a systematic phenomenon that appears in other cases, too.
For instance, the STT was able to create a dashboard with aggregated data about the number of funds involved in projects administered by different public institutions. This allowed to see that in some institutions the majority of projects went to only a few companies. The STT informed the responsible persons who were authorized to make decisions concerning the reduction and prevention of corruption in a particular institution, sector or nationwide about the risks detected, and also performed checks on the individual projects.
In order to support their analytical anti-corruption intelligence, the STTis also allowed to demand financial information from banks about specific legal persons in case it suspects illegal activities. This information can be demanded even without an official investigation ongoing. Financial information relating to natural persons however can only be obtained once an investigation has been opened.
In addition to this preventive data analysis approach, the analysts can also be contacted by other STT departments with requests for assistance either for ongoing investigations or for further analyses into specific matters. In a specific case, as part of an STT ongoing criminal investigation, the analytical anti-corruption intelligence department was asked to look into a hospital with a suspected untransparent public procurement process. It found out that legal entities acting as sponsors of the hospital were also the ones who received the public contracts. The analysts then checked for similar risks in the health care sector focussing on the relationships between sponsorships and awards of public contracts and could identify further cases. The information was published in a report and presented to the Parliament, the Ministry of Health and the public. As a reaction, legislative amendments to increase transparency in the areas of public procurement procedures were made and a framework for providing and receiving charity and sponsorship, as well as its accounting and control was developed to strengthen the pro-activeness of the public sector in managing conflicts of interest.
As a result of their work, the STT issues reports about risks identified in the system, linked to institutions, processes, events and persons and thereby informs the decision makers for anti-corruption policies/laws. They also provide information to their internal criminal intelligence and criminal investigation departments – to support investigations, and to the corruption prevention and anti-corruption education departments – to tailor their measures.
- Independent anti-corruption body that alongside with a law enforcement function also performs corruption prevention and anti-corruption education, and that uses big data analyses models for evidence-based anti-corruption policy making
- Access to huge amount of data to analyse and to check whether a given risk was repeated in other parts of the country or sectors
- Preventive data analysis approach to detect corruption risks early on
- Close cooperation with law makers to improve the legal framework
Outcomes and results
Tangible results include:
- Improved work of the STT allowing more efficient and effective analyses
- Increased number of reports issued to the public and parliament compared to period before 2018
- Provision of information to decision makers in a timelier, more concrete and more understandable way, i.e. using visualization software
- Identification of loopholes in the laws, e.g. regulations that favour opaque public procurement practices, and insights on how to amend the regulatory and institutional framework
- Ability to respond quicker to requests for assistance
- Detection of potential conflicts of interest, bribery and collusion cases
- Provision of data for evidence-based anti-corruption measures (at STT and national level)
Expected long-term results expected:
- Lowering the risks and threats of corruption concerning EU financial interests
- Decreasing the frequency of actual corruption cases
- Limiting the damage to the national and EU financial interests
- Enhancing the awareness and integrity culture in the public and private sector
Key success factors
- Interdisciplinary team combining people from the analytical anti-corruption intelligence department and the IT department of the STT
- Collaboration and exchange with other institutions to understand what systems they use and which corruption risks they encounter
- Constant collaboration with practitioners, academia and NGOs about corruption risks, needs for investigation and needs for improvement in the analyses and reports provided
- Political will to fight corruption, e.g. expressed in the extensive access to data bases and financial information the STT has
Challenges encountered & lessons learned
- Key to perform a thorough market analysis about what kind of systems already exist and could be used
- No need to develop an inhouse solution as numerous powerful software programs already exist
- Important to ensure that the software could be successfully integrated within the existing IT platform
- Crucial to train employees not only in the use of software programs but also in their adaptation
- Data protection must be considered during all parts of the project
Potential for the transferability
The success of the STT analytics system is, on the one hand, based on the existence of the STT as an institution in the first place. Such an independent anti-corruption body that investigates and issues data-driven reports about corruption does not currently exist in most EU countries.
On the other hand, the system can only operate since the STT has access to numerous state-owned registers and can get access to certain financial information even without an ongoing investigation. This is not possible in most other EU countries.
Nonetheless, the concept of the STT information system is still transferable as long as it is integrated in the institutional and legal set up of another Member State. Other countries could also use different available data sources to detect suspicious relationships, recurring patterns or anomalies and investigate corruption risks before corruption crimes occur. They could inspire themselves on the example of the STT.