As fraudsters and the technology they use becomes more sophisticated and interconnected, traditional rules‑based and siloed approaches struggle to keep pace — creating blind spots, false positives, and slow investigations that results in increasing loss ratios, operational costs, and customer friction.
Delivering a category-defining vision for fraud and financial crime prevention - combining agility, scalability, and proven impact to help insurers lead with data-driven intelligence.
HOW WE SOLVE IT
Unify internal systems and enrich with external data (corporate registries, industry claims etc) to understand risk holistically
Connect data to reveal hidden relationships across customers, claimants, providers, assets, and organizations
Detect even the most sophisticated fraud with scorecards grounded in contextual data for higher accuracy and better prioritization
Accelerate fraud investigations and uncover hidden relationships with more accurate contextual intelligence and AI decisioning
THE IMPACT
the amount of fraud Quantexa has helped organizations detect
in false positive alerts through enrichment
up to 90% increase in fraud impact savings
in loss ratios from improved claims segmentation
WHERE WE HELP
Identify fraud across the full customer lifecycle and all distribution channels.
Block fraudulent payments and stop claims leakage across the claim, billing and payment lifecycle.
Detect insiders engaged in defrauding the insurance organization or the firm’s customers.
Perform complex investigations across all data to identify new and unknown risks.
Build a trusted data foundation to deliver context for decision-making.
Learn moreEnhance customer experience and accelerate revenue growth with a 360-degree connected view of customers.
Learn moreDetect risk in real time to identify unknown risks and deliver more accurate risk ratings.
Learn moreRevolutionize risk assessment with a holistic understanding of borrowers, their counterparties and relationships.
Learn moreTake a unified approach to fighting financial crime and fraud with our Contextual Monitoring solutions.
Learn moreReduce false positives and focus on real risk by modernizing your AML monitoring, detection, and investigation.
Learn moreYes. Quantexa delivers real-time contextualization and decisioning at the point of need whether that's during claims processing, policy underwriting, or payment approval. Our platform ingests and unifies data from across your organization, then applies entity resolution and network analytics in real-time to surface hidden connections, risk patterns, and fraud indicators before decisions are made.
Beyond real-time scoring, Quantexa also supports batch analytics for deep investigative work and historical pattern analysis. This dual capability means your teams get both the speed to act decisively in the moment and the depth to uncover sophisticated fraud rings operating across time.
Quantexa integrates AI and GenAI across three critical layers: entity resolution, network analytics, and investigative acceleration.
Entity Resolution uses probabilistic AI to connect fragmented identities, resolving the same individual across name variations, multiple addresses, and phone numbers that traditional matching tools miss. This unlocks the hidden fraud concealed in data fragmentation.
Graph Analytics applies advanced AI to reveal multi-hop networks and sophisticated fraud rings. Where rules-based systems analyze transactions in isolation, our AI-powered graph intelligence exposes coordinated schemes involving 5-20+ actors across providers, brokers, and policyholders.
Q Assist, our GenAI copilot, transforms investigative workflows. Investigators ask natural language questions like "What are the hidden connections between this policyholder and other high-risk applications?" and receive instant, contextual insights drawn from unified data reducing investigation times and enabling teams to focus on genuine threats rather than false positives.
Our Agent Gateway enables access to contextual data from Quantexa's Decision Intelligence Platform so that agentic decisions can be grounded in context, as well as enforcing governance and explainability across distributed agent networks.
