Fighting subversive crime demands comprehensive insights into organizations and their activities
To repress and prevent labor exploitation, fraud, organized crime, drug production and trafficking, or any other forms of subversive crime, identifying signs of undermining activity is crucial. Being able to discern such signs requires to gather large amounts of company information and detect anomalies which might hide in the smallest details. To avoid generating false positives or negatives, and to substantiate potential risk, information should be correlated against knowledge from past, similar, situations. The breadth and dept of information to collect and process is too important for analysts to be able to process manually and timely.
Pandora Intelligence provides the analytical power to produce comprehensive insights of organizations, their involvement and relation with specific activities, stakeholders or goods. To do so, Pandora Intelligence’s platform collects data from a broad range of sources and corelates it to create relevant intelligence. This intelligence effectively empowers your organization in proactively detecting undermining activity and subversive crime.
Municipalities, safety regions and national police make use of Pandora Intelligence’s platform to prevent subversive crime and its degrading effect on society.
While going through the list of companies registered within their municipality, analysts investigated the establishment and liquidation of a medical service company and noticed that this company only existed for several months before officially ceasing activity. After days of information collection and investigation, it seemed that the company was registered on a residential address from which several other similar companies had been registered before. Each of those companies had only a lifespan of several months, indicating suspicious activity. Unfortunately this investigation was only launched after several years of suspicious activity.
On a recurring basis, registration of companies or company changes are automatically analyzed. Such information is gathered from a wide range of sources and analyzed to detect abnormal changes, reoccurring registrations, important differences with market averages, and domain specific mismatches. All companies are then presented in an overview with respective risk levels, allowing analysts to prioritize their focus on suspicious cases.