When data is compromised in a cybersecurity incident, our team provides rapid insight into the potential severity, quickly defining the extent of exposure and the obligations to the company, customers, employees, and third parties.
Working in partnership with cyber insurance companies, cyber consultancies, and law firms assisting with cyber incident reviews, our team leverages proprietary data mining, AI, technology, and custom designed workflows to rapidly identify private and sensitive information to determine the best path forward in the early and critical timeframes of an incident.
Our global cyber incident review team—the largest in the industry—oversees and coordinates response and resource deployment, driving efficient workflows that allow clients to understand the extent of exposed sensitive data. We work around the clock in collaboration with counsel to prioritize data types for immediate analysis, quickly extracting NPPI, PHI and other sensitive data to develop an accurate notification list.
Our teams continually innovate and refine AI strategies to reduce the time to reporting and notification, while limiting the number of documents requiring review, along with commensurate costs. We leverage proprietary AI and data mining methods to power more inclusive and precise identification of sensitive information in significantly less time, improving review times from days to just hours.
Case study
Entities extracted
Documents reviewed
Documents extracted using proprietary tech stacks
The client faced a large-scale breach investigation spanning hundreds of thousands of documents and tens of millions of entities. Relevant information had to be identified and extracted at scale to support assessment of potentially impacted data and downstream regulatory response.
Volume and complexity made a purely manual, document-by-document approach difficult to scale.
UnitedLex Information Risk applied proprietary technology stacks, analytics and expert review to process and extract information across the dataset. Technology-enabled workflows extracted information from 69% of the document population, while structured review identified and validated relevant information for further assessment and regulatory response.
This technology-led approach allowed expert resources to focus on higher-value assessment and validation.
Scale — Enabled the team to work across 354K+ documents and 31.5M+ entities through a structured, technology-enabled workflow.
Technology-Led Efficiency — Proprietary technology stacks extracted information from 69% of documents, reducing reliance on manual extraction.
Focused Expertise — Enabled human reviewers to concentrate on assessment, validation and regulatory decision-making where expert judgment was required.
We maintain on-premise and cloud-based data processing and hosting environments to provide a flexible and scalable infrastructure to our globally situated clients.
Blending proprietary and industry leading technology with legal and applied analytics expertise, we cull data, report on categories of sensitive data, and provide an analysis of type and density of potentially exposed sensitive information to inform budget and planning.
We apply analytics and AI, including custom data privacy models and client/industry specific data elements, to identify affected data subjects and automate extraction of sensitive information within structured and unstructured data sets.
To ensure completeness and precision of a cyber incident review, our team augments programmatic review with human-assisted extraction, utilizing deeply experienced resources to ensure adherence to the review protocol, consistency of extractions, and quality.
We adhere to stringent extraction and quality processes to ensure “mail-ready” notification lists. This includes data normalization and consolidation, entity resolution and deduplication.
As part of an incident response, or as part of an organization’s ongoing data privacy program, we also can provide our technologies behind corporate firewalls to identify, categorize and report on sensitive personal and business confidential data.
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