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consilient    
a. 符合的,一致的

符合的,一致的


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  • Home » Consilient Federated Learning Technology
    The Consilient Solution Federated learning Industry challenges Use cases Customer benefits Our products Core AML CFT model Correspondent Banking model High-Risk Typology models High-Risk Jurisdictions model KYC AML Risk Rating model About us The founders’ story Our mission Our vision Our values Meet the team Careers Resources
  • Why banks are switching to Consilient’s federated machine learning AML . . .
    Consilient’s new advanced AML CFT Model offers a smarter, more precise way to strengthen compliance, reduce operational costs, and detect financial crime with unparalleled accuracy Built using the most advanced machine learning approach and technology and backed by real-world results—including an 88% reduction in false positives and a 300%
  • What banks did wrong in 2024: Critical AML failures and essential . . .
    Build stronger AML defences with Consilient The lessons from 2024’s AML failures point to a clear conclusion: financial institutions need to fundamentally rethink their approach to compliance The cost of poor AML controls extends far beyond regulatory fines
  • Our Products » Consilient
    Consilient models are crafted to significantly enhance efficiency and effectiveness in identifying risks through the exchange of behavioral patterns and insights, all while preserving data privacy
  • How AI helps governments and businesses tackle AML and economic crime
    AI and federated machine learning are essential to better identify and combat financial crimes across units and boundaries Consilient is uniquely positioned with its expertise and solutions to help the private and public sector overcome hurdles, and these boundaries add a superpower to any financial crime fighter ”
  • Rethinking risk ratings: a collaborative data-driven approach » Consilient
    Consilient works with financial institutions across the U S to deploy federated learning models that improve AML detection, reduce false positives, and support smarter compliance decisions If you’re considering how to modernize CRR — or any other part of your AML framework — we’d love to hear from you
  • Lessons from Starling Bank’s AML fine: A wake up call for banks
    by Laurence Hamilton , Chief Commercial Officer , Consilient The FCA’s recent £41 million fine imposed on Starling Bank for “shockingly lax” AML controls highlights issues that extend beyond the financial crime department, reaching the highest levels of leadership
  • How Consilient’s new models detects hidden high-risk typologies
    Consilient’s High-Risk Typology Model delivers next-generation AML detection, allowing banks to identify undisclosed high-risk activity, enhance compliance, and optimize operations without compromising privacy
  • How model intelligence is transforming financial crime detection
    🔍In fact, in one Tier-1 US Bank’s case, Consilient improved efficiency by 75% Cross-institutional collaboration reveals patterns that individual organizations often overlook Criminal networks operate across borders, exploiting gaps in isolated systems
  • Core AML CFT Model » Consilient
    Consilient utilizes XGBoost (Extreme Gradient Boosting) to deliver fast, accurate, and scalable models ideal for banking transaction data With tools for feature importance, overfitting control, and bias-variance management, XGBoost ensures reliable performance





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