IDEAS home Printed from https://ideas.repec.org/p/baf/cbafwp/cbafwp26283.html

Data Driven Compliance: A SBR solution for regulated entities

Author

Listed:
  • Andrea Gentilini

Abstract

EU financial regulation obliges supervised entities to report transaction-level, position-level and portfolio-level data at a granularity unmatched in any other regulatory domain. National Competent Authorities (NCAs) have begun converting these flows into Data-Driven Supervision (DDS): reproducible indicators, composite risk scores and triage pathways that allocate scarce supervisory capacity where risk concentrates (Gentilini, 2026a). DDS contributes in an efficient manner to address the fundamental needs of efficient, convergent and consistent supervision, within an architecture that combines a centralised, collegial layer for risk identification and metric design with decentralised, proximity-based application at NCA level (Gentilini, 2026b). This paper argues that the same data, the same indicator logic and the same scoring methodology can — and should — be deployed symmetrically by the entities themselves, as Data-Driven Compliance (DDC): an internal control discipline in which firms compute, monitor and remediate the very indicators their supervisors compute about them. DDC converts regulatory reporting from a terminal cost into a source of compliance assurance, lowers the cost of evidencing compliance, and creates the informational basis for a structured dialogue between entities and NCAs over which data and indicators are fit for purpose. Drawing on case studies across AIFMD, EMIR, MiFIR, MMFR and SFTR reporting — anchored in ESMA’s Data Quality Engagement Framework for the provision of data and follow-up on data quality issues — the paper formalises the DDC construct mathematically and concludes with a single actionable recommendation: ESMA should adopt dedicated Guidelines under Article 16 of its founding Regulation making it mandatory for NCAs to require supervised entities to develop and regularly use the indicator-based controls that constitute ESMA’s Data Quality Engagement Framework, to monitor their outcomes and resolve the issues they flag, and — only where issues were flagged — to report annually to their NCA on the issues identified and their resolution. The proposal is framed as simplification and burden reduction, not as new substantive obligation.

Suggested Citation

  • Andrea Gentilini, 2026. "Data Driven Compliance: A SBR solution for regulated entities," BAFFI CAREFIN Working Papers 26283, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
  • Handle: RePEc:baf:cbafwp:cbafwp26283
    as

    Download full text from publisher

    File URL: https://repec.unibocconi.it/baffic/baf/papers/cbafwp26283.pdf
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • O17 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Formal and Informal Sectors; Shadow Economy; Institutional Arrangements

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:baf:cbafwp:cbafwp26283. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Michela Pozzi (email available below). General contact details of provider: https://edirc.repec.org/data/cbbocit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.