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Built on technology that puts you in control

Our Technology

Our product allows organisations to resolve entities and build networks dynamically and in batch.

Quantexa® technology is unique; it provides the ability to perform both batch and real time entity resolution and network analytics on billions of records. Our products are underpinned by widely adopted open source technologies, ensuring alignment with your existing investments, reducing cost and allowing you to own, manage and extend the system.

Key features:

  • Real time: dynamically build entities with varied fuzziness to service multiple use-cases.
  • Scalable: able to handle billions of records and scales horizontally and vertically.
  • Open: built on open source technology on non-proprietary data formats and exposes standard REST APIs.

What is “dynamic entity resolution”?

Most entity resolution engines are designed with the goal of creating a single customer view across multiple disparate data sources. There are several challenges with this approach:

  • It assumes that there is a “one size fits all” definition of entities that is suitable for all business applications. However fraud and financial crime, for example, require more fuzzy matching than a risk or marketing use case.
  • It assumes that all business applications use the same data sources. However different departments (e.g. risk/marketing/fraud) will require different data sources.
  • It assumes all data sources have been ingested ahead of time. When responding to a crisis (e.g. Panama Papers) you need to be able to dynamically overlay this on top of the existing data in the system without complex technical integration work.
  • It assumes that all data sources have rich enough linking data. In Financial Crime, you will often have watchlists which have very limited linking information or poor quality data, so you need to be able to go fuzzy on a case-by-case basis.

As a result, organisations have ended up deploying multiple entity resolution technologies (or the same technology multiple times) for different use-cases. This leads to a huge duplication of data, infrastructure and management effort.

Dynamic entity resolution allows you to have a single enterprise-wide entity and network generation engine servicing many business use cases and minimising data replication.

Product Modules

Our product stack can be deployed as a series of modules into a data lake environment, coexisting with Hadoop, other data stores and open source technologies.

Dynamic Resolver

  • Dynamic (real time) entity resolution and network building
  • Dynamically vary the fuzziness of the entities to support multiple use-cases from a single system
  • Build the networks dynamically at the time of request
  • Supports multiple use-cases
  • Scale out architecture, with sub-second response
  • Newly-added data available for entity resolution and network analysis within seconds of loading
  • Apply scoring to the generated entities and networks

Batch Resolver

  • Batch-based entity resolution and network building
  • Proven to scale to multi-billion data sources with unparalleled performance
  • Runs on Apache Spark within your existing Hadoop environment
  • Configurable matching and network building criteria
  • Apply scoring to the generated entities and networks

Analytics Framework

  • Standardised framework to allow data scientists to assemble analytical techniques into an overall detection model
  • Manages analytical metadata, parameters and dependencies
  • Entirely white box, enabling your analysts to own, manage and update models independently from Quantexa

Dynamic scoring engine

  • Standardised framework for deploying analytics across both batch and real time
  • Single codebase for batch and real-time scoring
  • Generation of meaningful score descriptions to give users explanations of the key risks
  • REST APIs for on-demand scoring on top of the dynamically built entities and networks
  • Fully integrated with Quantexa Explorer, highlighting key risk factors as users explore the data

Explorer

  • An extensible HTML5 and JavaScript user interface
  • Visualisation of entities, relationships and networks
  • Explore the network and expand through entities of interest
  • Users can view the internals of the entity to understand how it is built and re-build it on the fly with an increased or decreased level of fuzziness
  • Overlay full transactional data onto the network and understand significant and shared entities such as counterparties
  • Drilldown, map and timeline views
  • Work through lists of alerts raised by the analytical models and take decisions
  • Granular security model
  • Easily integrates with 3rd party case management systems

Search

  • Instant exact and fuzzy search across the entire system

Entity search

  • Apply dynamic entity resolution and network expansions to search results
  • Use graph context refine matches and reduce false positives
  • Apply scoring

Bulk search

  • Initiating an entity search from a CSV file
  • Assess results based on match strength and risk
  • Generate investigations

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