QEDIT for Risk Mitigation
Bolster your fraud detection capabilities, prevent crime and reduce investigation costs through cross-organizational data collaborations with trusted members of your ecosystem.
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Current constraints
In today’s hyper-competitive data economy, AI and business intelligence solutions that rely exclusively on siloed company data to mitigate risk are not sufficiently equipped to provide business-critical insights that can only be acquired through cross-company intelligence sharing. For most institutions, however, data-driven collaborations are deemed impractical due to strict regulatory constraints, confidentiality clauses and other privacy-related business sensitivities.
The way forward
Using innovations in Privacy-Enhancing Technology, companies can now cross-reference their data against external datasets from other businesses in their network, and can do so in a privacy-protected, regulatory compliant environment.
Use Cases
Identity Verification
Enhance Know Your Customer (KYC) processes by cross-referencing data and verifying the integrity of client information collected by other institutions.
Fraud Detection
Compare and analyze datasets derived from loans, claims, customer accounts and policy applications to detect instances of fraud, loan/policy stacking and churning.
Optimize Investigations
Reduce financial losses and save time by automating investigative processes, and translate your efficiency gains into lower fees and more competitive terms.
