Solutions > Supervisory Technology > Regulators

Regnology SupTech

More efficient and effective on-site and off-site supervision through automation and improved data quality.

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Make faster and more confident decisions by collecting the right data, identifying risks and gaining a better understanding of the market

Key benefits

  • Increased Efficiency

    End-to-end software enables you to automate your full workflow from collection to screening, validation, workflow management and analysis to the final remittance of regulatory and statistical data.

  • Early Risk Detection

    Leverage the highest quality data with best-in-class risk frameworks to support risk-based supervision and early risk detection.

  • Greater Market Insight

    Flexible, rich, real-time analysis and reporting capabilities enable you to make informed decisions, grow markets, and reduce volatility.

  • High Scalability

    A proven solution for over 30 central banks and supervisory authorities worldwide, the highly scalable platform can effectively handle rapidly growing data volumes and policies, complex data rules and an unlimited number of entities.

Regnology’s platform helped us to manage our prudential data collection and the licensing of financial institutions. Our regulated entities can now upload their data automatically via API, decreasing the amount of human interaction when submitting the data.

Michael Mensah Director of ICT
Bank of Ghana

Regnology’s solution best met APRA’s need for a modern, efficient and user-friendly data collection system that would adapt as technology evolved. We are confident that the partnership will allow financial companies to report data to APRA more quickly, efficiently and accurately.

Sean Carmody Executive Director for the Cross-Industry Insights and Data Division
APRA

Features

  • Optimized communication

    Support automated push & pull of data in industry-standardized formats (JSON, XML, XBRL, CSV) with both automated notifications/reminders and ad-hoc online communication between regulators and regulated entities.

  • Early Warning Reports

    Automatically calculate KRIs for an entity, combine them with other insights and compare these KRI values to peer groups or sectors to generate early warning reports.

  • Automated Licensing

    End-to-end integrated software enables you to automate licensing processes and easily maintain the master data profile of each regulated entity.

  • Master Data Repository

    Easily update, search and view a complete entity profile including historical changes for each regulated entity, as well as their relationships with other parties.

  • Broad Coverage

    Full coverage of international regulatory regimes as defined by BCBS, IMF, ECB, EBA, EIOPA, IAIS, IOSCO and IFRS.

  • Regulatory Community

    Be part of Regnology’s community of supervisory authority customers for access to our online community forum, regular webinars, panel discussions and product workshops to stay on top of regulatory change and industry trends.

  • Technology

    Cloud-native, secure, micro-service architecture that can be deployed on-premises or in the cloud for optimal availability, scalability, and configurability.

Regulatory coverage

  • Insurance

    EIOPA Solvency II (ORSA, RSR)

  • Insurance

    IFRS 17

  • Banking

    COREP

  • Banking

    FINREP

  • Banking

    Basel III Finalisation (Basel IV)

  • Pensions

    EIOPA Pension Funds

  • Pensions

    EIOPA Pan-European Personal Pension Product (PEPP)

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Related resources

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    A SupTech transformation: using tech to support the full supervisory lifecycle

    Central banks are facing a big data problem, the number of firms and disclosures they must supervise is increasing rapidly and is straining limited resources.

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  • Regulatory reporting: The role of technology in connecting the regulators and the regulated

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    An conversation between Sidharta Dash, Chief Researcher at Chartis Research, and Rob Mackay, CEO of Regnology.

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  • Becoming a Data-Centric Organisation: the case of Bank of Lithuania​

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    Becoming a Data-Centric Organisation: the case of Bank of Lithuania​

    Dive into the major overhaul of Bank of Lithuania's data architecture aiming to finalise a centralized structure for data reporting and analysis by 2025.

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