- The project showed that complex digital transformation requires an iterative and collaborative approach. Solutions are more feasible when they are built on real data, existing workflows and the actual technical environment rather than on abstract models. It also confirmed that technology and institutional development must progress together. Governance, clear ownership, internal analytical capacity, training and change management are as important as software architecture.
- European benchmarking proved valuable when practices were adapted to the local context, while the modular approach offered a realistic path for introducing AI gradually and responsibly.
- Civitta helped translate institutional and operational needs into a coherent future-state model and ensured continuity between the diagnostic, strategic concept, organisational recommendations, technical architecture and procurement requirements.
- The project demonstrates Civitta’s capacity to operate at the intersection of public-sector reform, organisational development, data strategy and complex digital system design.
- The approach is relevant to other customs administrations and public institutions that manage large volumes of operational data, rely on legacy systems and want to introduce AI while maintaining transparency and human accountability. It can also be adapted to tax administrations, border authorities, anti-fraud institutions, financial regulators and other compliance or inspection bodies undertaking data-intensive digital transformation.
Preparing Romania’s Customs Administration for AI-Enabled Risk Management
Client
The Romanian Customs AuthorityClient Overview:
The Romanian Customs Authority operates through central, regional and local structures and manages imports, exports, transit operations and the movement of goods across Romania’s section of the European Union’s external border. The future solution therefore had to respond to the needs of multiple user groups and connect with several national and EU customs systems.
The project was aligned with the EU’s Multi-Annual Strategic Plan for Customs, DG TAXUD guidance and the World Customs Organization’s risk management framework.
The Challenge:
The Romanian Customs Authority needed to prepare the transition from a fragmented risk management system to a modern, integrated and data-driven model. The objective was to design the strategic, operational, institutional and technical foundations for a new system capable of progressively incorporating artificial intelligence, advanced analytics, automated risk identification, anomaly detection and Business Intelligence.
International trade and customs data volumes are increasing, while fraud schemes and risk typologies are becoming more complex. Modernisation of the risk system was therefore essential both for improving the effectiveness of customs controls and for allowing legitimate trade to move more efficiently.
To this end, the Romanian Customs Authority sought to modernise its risk management system by strengthening data integration, automation and advanced data analytics.
The solution had to work within a complex institutional and legacy IT environment, connect with existing national and European systems and avoid disrupting current customs operations. It also had to address data quality, interoperability, governance, skills development and human oversight of AI-supported decisions.
The project outputs were closely interdependent, requiring full consistency between the diagnostic, feasibility study, system concept, architecture, Proof of Concept and procurement documentation.
Our Approach:
As part of a multidisciplinary consortium, Civitta helped connect customs risk management, institutional reform, digital transformation, data analysis and IT system design. The work followed a clear sequence: understanding the existing situation, assessing readiness for AI, defining the future operating model, designing the technical solution, demonstrating its functionality and preparing the institution for procurement and implementation.
The project began with a comprehensive diagnosis of the strategic, organisational, operational and technological dimensions of the existing risk management framework. This was followed by an assessment of the Authority’s digital maturity and readiness to adopt AI.
A European benchmarking exercise examined the experience of customs administrations in Belgium, Estonia, Finland and Hungary. These examples were not copied directly; relevant practices were adapted to Romania’s institutional and technological context.
The methodology combined documentary analysis, interviews, surveys, technical meetings and workshops with central, regional and local stakeholders. Based on this work, the team designed an integrated future system integrating automated processing of EU risk information, alert analysis, anomaly detection, declaration-level risk scoring and an AI Assistant.
The concept was then translated into functional and technical requirements, a modular architecture, an economic justification, realistic Proof-of-Concept scenarios and technical procurement documentation.
The proposed model treats AI as a decision-support tool rather than an autonomous decision-maker. Customs experts remain responsible for validating results and taking operational decisions. The solution combines established rule-based risk profiles with machine learning, anomaly detection and semantic similarity analysis.
A modular and phased architecture was selected so that advanced capabilities can be introduced gradually, without requiring the immediate replacement of all existing systems.
The project was developed through continuous co-creation with the Romanian Customs Authority and the National Centre for Financial Information. Each major output was presented, discussed, validated and adjusted. The work was grounded in real data, actual operational processes and the existing IT architecture, helping ensure that the final solution was both ambitious and implementable.
Results & Impact:
The 16-month assignment delivered all contracted project outputs. Consulting work included stakeholder interviews, workshops for the AI feasibility analysis and preparing the procurement documentation, and two training sessions delivered to customs personnel. The project also included benchmarking with four European customs administrations.
The final project evaluation confirmed that the project objectives had been achieved and that the outputs provided a coherent foundation for the next implementation stage.
The Romanian Customs Authority now has a coherent pathway from diagnosis to implementation, including an AI-readiness assessment, a future operating model, a modular technical architecture, detailed requirements, a Proof of Concept, an implementation roadmap, procurement documentation and an institutional capacity-building framework.
The project also strengthened alignment between risk management and IT stakeholders and created a shared understanding of the future system, its priorities and the institutional changes required to operate it successfully.
The production system was not implemented within this assignment, so operational benefits should be presented as expected impact rather than completed results. Once implemented, the proposed solution is expected to support faster identification of emerging risks, more accurate selection of declarations for control, improved anomaly detection, reduced manual workload and better use of national and EU risk information.
In the longer term, the project provides the foundation for moving toward a more proactive, automated and data-driven customs risk management capability.
