“OpenCorporates’ global company data enables us to resolve entities and piece together complex corporate networks in our knowledge graph – so our customers can uncover risks that wouldn’t otherwise be visible”.
Global Head of Credit Risk Solutions
Managing third party, credit, fraud and other risks is made difficult by the complexity of corporate networks, as risk management teams are often unable to understand the full picture about a potential customer – including who they are connected to.
Today’s risk backdrop is ever more complex and interlinked, as seen through current macro challenges and anticipated global recessions. These risks include supply chain dislocations, energy and commodity price spikes and the indirect effect of cost of living crises on corporations. Financial pressures such as these may lead to a higher risk of fraud, financial crimes and credit events.
Deliberate obfuscation through opaque corporate structures in offshore jurisdictions makes understanding the full picture of risk challenging, as well as the fact that company register data and risk-related datasets are siloed and lack a consistent method to uniquely identify companies.
To overcome this, one way of using Quantexa’s Contextual Decision Intelligence (CDI) platform is to map out complex corporate networks via a knowledge graph so their users can uncover risks hidden behind opaque cross-border structures – such as shell companies and their creators.
Building out these networks required an authoritative data source about the global universe of legal entities that would act as a foundation so other data sources could be resolved against and appended on top of.
Quantexa integrated OpenCorporates transparent company data into the knowledge graph in their CDI platform via our global Bulk Data files so it could act as the authoritative source for companies, their officers and registered addresses.
Transparent company data – data which is up-to-date, unified, traceable to official sources and consumable – enables the CDI platform to resolve references to companies in other datasets back to their relevant legal entity. When combined with other kinds of data, such as transactions, ownership and risk-related datasets, the platform can build up large complex corporate networks that span millions of entities.
But even with just our data, Quantexa’s knowledge graph can analyse the shape of different corporate networks and identify patterns which drive better risk identification.
For example, when the registered address of a company is the same as tens of thousands of other companies, this indicates it could have been formed by a Trust and Company Service Provider (TSCP) – therefore posing a different risk profile than a company with a more conventional corporate network.
Image: How company data enables Quantexa’s platform to build up a graph view of a TSCP
The central node is a highly connected ‘Director Entity’ – the TSCP or Agent – with edges connecting to businesses they have previously incorporated and since transferred ownership to new directors.
Quantexa chose to incorporate OpenCorporates’ transparent company data for 4 main reasons:
- Up-to-date view of the global company universe
Quantexa receives up-to-date information on 210+ million companies and 280+ million officers from 140+ jurisdictions – allowing for cross-border connections to be made. Fresh information was critical to Quantexa as it enables their customers to make effective risk management decisions.
- Unified data that’s easily integrated into a knowledge graph
As the inconsistent data we collect from registries is standardised into a harmonised global schema, it made it easier for Quantexa’s team to integrate it into their knowledge graph.
- Traceable back to official sources
As our data is traceable back to official sources, it provides confidence to Quantexa that their users are making decisions based on high quality data. For this reason, it also made an effective dataset to train Quantexa’s machine learning shell detection engine on.
- Consumable as Bulk Data via a single source
As we provide entire populations of companies as Bulk Data, Quantexa were able to receive the full picture about companies in 140+ jurisdictions to build out their corporate networks – all via a single source.
Our data provides the base layer of company information that Quantexa’s CDI platform uses to resolve entities globally, join the dots to build up complex corporate networks and ultimately provide their users with a 360 degree view of risk.
- Fuller risk picture when looking forwards or backwards
Quantexa’s customers are better able to understand the risk third parties pose as they have access to global data that the CDI platform uses to identify red flags linked to a corporate network that would otherwise be missed.
For example, with the data, customers can identify risky network shapes that could indicate links to shell companies, risky agents or other entities that raise red flags for risk management teams.
This is especially useful in retrospective risk management efforts, such as to identify and root out lending fraud, as with the way the UK’s Cabinet Office has adopted the platform to detect fraud in Covid-19 loan schemes.
Better yet, links to companies or their agents that pose red flags are available from the time they are incorporated – providing Quantexa’s customers with early warning signals from Day 0.
- Drives entity resolution
By referring back to OpenCorporates’ company data, Quantexa’s platform is able to resolve inconsistent references to companies around the world in various datasets back to their corresponding legal entity – as per the record from the relevant official company registry.
Quantexa is a global data and analytics software company pioneering Contextual Decision Intelligence that empowers organizations to make trusted operational decisions by making data meaningful. Using the latest advancements in big data and AI, Quantexa’s platform uncovers hidden risk and new opportunities by providing a contextual, connected view of internal and external data in a single place. It solves major challenges across data management, KYC, customer intelligence, financial crime, risk, fraud, and security, throughout the customer lifecycle.