PDF: Beyond banking: Unlocking data value with secure collaboration

Transform how banks analyze sensitive data, detect risk, and collaborate — all while protecting customer privacy.

Banks and financial institutions collect enormous amounts of sensitive data, yet strict privacy requirements and siloed systems often limit its value. What if you could harness that data securely — without exposing underlying information or compromising compliance?

Our Beyond Banking guide shows how financial institutions can use privacy‑preserving technologies like Confidential Computing, Multi‑Party Computation (MPC), and secure analytics to accelerate insights, detect complex fraud patterns, enhance risk models, and collaborate across ecosystems — all while maintaining privacy and trust.

Whether your goals are improving AML efficiency, innovating on digital products, or driving data‑driven decision‑making, this guide provides practical frameworks and real‑world examples tailored to banking and financial services.

What You’ll Discover How privacy‑first collaboration improves fraud detection and AML without exposing raw customer data Approaches to risk modeling and credit scoring using secure aggregated analytics Ways to share insights with partners or regulators while meeting GDPR and other compliance requirements Strategy options for modernizing bank data stacks without massive infrastructure rewrites How decentralized identities and secure computation unlock multi‑party workflows across institutions  and more...