Use examples

First of all it is worth explaining what our system is NOT for.

We do not recommend using our data resources for due diligence screening of individuals or corporations. The system by definition contains a lot of unverified data (to allow more chances of formulating workable hypotheses and developing new investigation lines) which may lead to false positives. At least PRIVATEPOL should not be used as the only source for checking the research subject’s background.

The services of PRIVATEPOL Data Analytics Inc. are not provided by «consumer reporting agencies,» as that term is defined in the Fair Credit Reporting Act (15 U.S.C. § 1681, et seq.) («FCRA») and do not constitute «consumer reports,» as that term is defined in the FCRA. Accordingly, our services may not be used in whole or in part as a factor in determining eligibility for credit, insurance, employment or another purpose in connection with which a consumer report may be used under the FCRA.

PRIVATEPOL Data Analytics, Inc. is a young company, established in 2017 for the purpose of commercializing the technologies described on this website as a separate business. However, our technologies and datasets have been in operation (and constant development) now for more than 10 years. They are a product of deep cooperation between legal professionals specializing in asset tracing and recovery, detective analysts and IT developers.

Following below are several examples of our technology set application in the past:

  • A very typical application scenario is assistance in location of assets of defaulted and absconded debtors (clients: private individuals, Ukrainian, Russian, Kazakh banks, Swiss, Cyprus, Cayman funds and financial companies). The system merges the available data with the client data within hours and assists the analyst in selecting points for further research. On many occasions it helps uncover companies under the same management and control as the known companies of the investigation target. Back-to-back real estate financing schemes (Eg. French real estate) are detected, leading to the ultimate source of funds. The «economic fingerprint» technology also helps reveal the businesses which the debtor is secretly building while neglecting the creditor’s demands.
  • Multiple cases where the system was used for preliminary assessment of potentially applicable attack / asset recovery strategies (does not substitute legal advice but avails the user of the benefit from the accumulated legal experience, which now is part of the knowledge in our system)
  • Managing the data/analytical side of investigation into a criminal scheme where good assets belonging to a financial institution were substituted by low quality and fake assets. Generating leads for pointed action in offshore centres to reveal information crucial for the subsequent recovery.
  • Assistance to a law enforcement agency in making sense of a vast payments flow information from a failed bank which actively assisted its clients in capital flight and money laundering. Segregating for further investigation the payments which contained leads to the whereabouts of a specific amount embezzled from the bank and its clients.
  • Quick construction of a «regulatory matrix» around the companies, foundations and trusts of the investigation target to determine the likelihood of active opposition by their administrators of potential freezing action and, generally, to assess their robustness against asset recovery effort (multiple cases).
  • Discovering through data the ways to build up legal proof of the fact that the same person controls two outwardly unrelated entities, to counter the application of «bona fidae purchaser» doctrine. The system generates leads which are then followed up by document requests within relevant jurisdictions.

Regulatory Matrix

In our era of regulation almost every professional business involved in creation and administration of legal entities, managing assets, dealing in securities and processing payments is regulated in this or that way by the relevant government authorities. In many cases such regulators number more than one (Eg. for banks). Even lawyers and auditors — the professions previously free from the burden of KYC and related regulation — now have its fair share to tackle.

When a legal entity becomes an investigated object, our system determines its ’regulatory matrix’ — Eg. what are the regulations and regulators over its registered agent, second-tier corporate services provider, bank, auditor etc. Each of them is potentially liable for not spotting illegality or not reporting it when prompted. Drawing up the regulatory matrix thereby becomes an important tool to determine the robustness of the investigation target’s asset protection and concealment arrangements.