Case study: Quantifind powers financial crime investigations using OpenCorporates’ data

“OpenCorporates’ global company data, when integrated into our platform, allows anti-money laundering investigators to make better decisions faster by understanding the wider context behind a subject they are investigating”.

Adam Mulliken, Senior Vice President of Analytics &
General Manager for Financial Crimes
Quantifind

Challenge

Investigations into money laundering and other financial crimes often start when unusual or anomalous transaction activity has been identified – but their success depends on an investigator’s ability to get the full picture quickly.

Quantifind approached OpenCorporates when they were building a machine learning-powered tool designed to automate the assimilation of many different types of information that support a financial crime investigation.

As investigators have long been slowed down by company information that is siloed across many different registries, Quantifind turned to OpenCorporates as an authoritative dataset that enabled access to the world’s official company information in one place.

Solution

Quantifind initially chose to incorporate OpenCorporates’ bulk data file of North American companies and officerships into their platform. More recently, they expanded this to include our full dataset, containing over 180 million companies and 220 million officerships from more than 130 jurisdictions.

Incorporating our data into Quantifind’s platform meant their users can leverage data which is:

  • Multi-jurisdictional: providing global context
    As OpenCorporates’ data contains company information from over 130 jurisdictions, Quantifind’s users can incorporate global legal entity data into an investigation quickly. 
  • High quality: allowing investigators to accurately identify links to subjects
    As our data is a standardised snapshot of the world’s companies, it was uniquely positioned to act as reference data from which to power the entity resolution capabilities Quantifind has built into their platform. This helps their tool to more accurately home in on the correct subject a user wants to investigate via a federated search, where it aggregates information from a range of different sources including watchlists, the open web or social media.

  • Provenanced: meaning information can be leveraged with confidence
    Quantifind’s users can build a case knowing they can prove the company registry data in their supporting evidence is collected directly from official company registers. This is because OpenCorporates provides the source from which all its datapoints originate. As some financial institutions’ policies give preference to evidence from official sources, this makes provenance all the more important.
  • Easily consumed: ready to deploy quickly
    As our data is standardized, this made it easy for Quantifind to ingest and deploy it in their platform.

Results

  • Enables investigators to make better decisions
    With OpenCorporates’ data, Quantifind’s users are able to understand the global context behind a person or legal entity they are investigating – helping them make more informed decisions. During a recent large-scale trial conducted by Quantifind, user data revealed that AML investigators relied heavily on general contextual information from the public domain, such as company registration data.

    Of the search results users chose to highlight for inclusion in a downloadable report, only 15% were assessed as containing inherently risk-related information – with the other 85% containing purely contextual information. This illustrates the valuable role company data plays in helping investigators get the full picture about a subject.
  • Saves time
    Investigators using Quantifind’s platform are able to identify cross-border links between companies and people, which are fundamental in many financial crime typologies, rapidly via a single source. This meant they could focus their time on analysing data and uncovering risk instead of manually collecting company information and assessing the accuracy of each individual result.

Indicative search for a legal entity in Quantifind’s platform, showing results derived from OpenCorporates.

Client: Quantifind

Quantifind is a technology company whose AI platform uncovers risk signals across disparate and unstructured text sources. In financial crimes risk management, Quantifind provides an AI solution for anti-money laundering and fraud detection that uniquely discovers risk by combining internal financial institution data with public domain data. 

Quantifind’s solutions for investigations and customer due diligence are delivered through a combination of APIs and a modern web application. Quantifind complements a Case Management platform implementation with one-click access to linked external data; the integrated capability allows investigators to stay anchored in one platform with access to all of the data needed to conduct a true 360° risk assessment. 

About OpenCorporates

OpenCorporates is the largest open database of company information in the world, containing information on over 180 million companies in 130+ jurisdictions, all from primary public sources. Founded 10 years ago, it is a public-benefit company, whose primary public-benefit mission is to make company information more accessible, more useful and more usable. 

Public-benefit and private organisations rely on OpenCorporates’ data to power investigations into illicit activity, KYC solutions and business intelligence. 

OpenCorporates has a unique structure with a set of world-renowned trustees to guarantee its independence and its public-benefit mission. This governance, data and expertise is allowing it to become the world’s underlying supplier of foundational company data for the good of business and for society.

Start using OpenCorporates’ data today

OpenCorporates provides global legal entity data for major commercial and public-benefit organisations.

Find out more about our data >

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