Data Analysis: A tool for Customs Enforcement
In the contemporary world, governments are under pressure to perform more efficiently and effectively. Revenue administrations are no exception, as they have to balance the decreasing resources and ever-increasing risks, often in difficult economic circumstances.
While the traditional methods for managing risk had, served the authorities well, the increasingly complex trading environment and concomitant growth in the regulatory framework, has made it incumbent upon them to seek more advanced methods to combat fraud and wasteful resource allocation.
To effectively deal with this scenario, customs administrations are turning to data analysis for improvement in their business processes, resulting in better compliance management and enhanced service delivery. The significance of the data accumulated through Customs clearance applications is important as it covers modes of transportation, frequency of cross-border transaction (both travel and importation), value and source of goods which in combination with information from other agencies can enable customs to look beyond the singularity of the transaction and actually view the profiles of companies, industries or countries.
Since Customs data is based on the globally accepted classification and coding system (HS code), it is particularly convenient to profile changes in industrial behavior as well as macroeconomic analysis. Such datasets can also enable customs to identify anomalies that are indicative ofcommercial fraud or unethical conduct. On the other hand data collected through the Customs clearance applications e.g. WeBOC, ASYCUDA etc. is of great value to other government agencies that are also involved in border activities e.g. transnational organized crime, human smuggling, money laundering etc., just to name a few.
Such agencies can use trade and traveler data to improve their enforcement and compliance levels. However, while customs data is a strong enabler, its linkages with nationally available datasets such as PISCES & IBMS (FIA), national biometric record (NADRA) can substantially enhance the ability of border agencies to effectively tackle the earlier mentioned criminal activities. On the other hand inability to acquire data analysis capabilities would render organizations ineffective in the modern world where regular trade channels are now being used to launder ill-gotten proceeds to safer havens and destinations (acquired through commercial frauds, criminal activities etc).
To achieve absolute compliance through traditional enforcement methods would not only require resources that governments would not be willing to provide but would entail delays and costs to industry that the public would not permit.
In the background of an automated business process, data analysis provides a viable alternative approach to achieve unprecedented and previously unattainable levels of compliance and facilitation. Pakistan Customs has initiated a number of pilot studies for adopting different data analysis tools.
The goal is to empower the organization by developing control dashboards (at the front-end) that allow for intelligent or evidence-based decision making to all operational tiers of the customs hierarchy. At the back-end of the application would be the data-warehouses/marts that would drive the Business Intelligence (BI) tool using different enterprise level tools e.g. ETL, OLAP etc for continual data analysis in real time vis-à- vis the evolving threat/risk environment.
In addition development of the IATA API / Cargo XML interface (betweenWeBOC / Airline systems) would make available advance passenger/Cargo information to Pakistan Customs enabling enhanced targeting of travelers involved in trafficking, fraud, money laundering etc.
In conclusion, data analysis is a force multiplier as it provides a powerful strategic tool to policy makers for deploying resources and establishing priorities to those problems and opportunities that will produce the most significant results.
It places in the hands of the individual customs officer information and perspective oncustoms issues and problems that is international in scope. In the mass of “bigdata”, it allows for a structured approach to data analysis for achieving organizational objectives and brings order to the chaos.
Data analysis is the springboard that boosts customs to new levels of efficiency and effectiveness in the increasingly complex and demanding environment of the international trade supply chain.