Mastering MiFID II: Turning Buyside Compliance Costs into Strategic Investments

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Key Considerations for Regulatory Data Management

This report explains how strategic IT investment in pursuit of compliance with the second iteration of the EU’s Markets in Financial Instruments Directive (MiFID II) will allow buyside firms to quickly and cost-effectively adapt to future regulatory change. GreySpark believes that asset managers and institutional investors can use these investments to further support the improvement of operational and strategic functions within their organisations, including surveillance and monitoring, human capital costs and liquidity sourcing.

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These investments will also allow buyside firms to engage in the provision of detailed insights from large data sets and to monetise the information contained in the data sets. Recognising that they must excel at data management in order to meet future regulations demanding greater levels of transparency, investment in flexible and modular IT infrastructure and analytical capacity for MiFID II compliance positions the firms to derive a range of operational, technological and business benefits in the future.

Published on: 6 Oct, 2016

Mastering MiFID II: Turning Buyside Compliance Costs into Strategic Investments – Table of Contents

  • 1.0 Contextualising MiFID II Compliance from a Buyside Perspective
    • 1.1 Increased Scope for Data Capture and Management
    • 1.2 Managing New Levels of Engagement with Regulators
  • 2.0 Client and Transaction Data Management
    • 2.1 Record-keeping
    • 2.2 Structured versus Unstructured Data Analysis Capabilities
  • 3.0 Addressing Buyside Technology Debt from a MiFID II Compliance Perspective
    • 3.1 IT Infrastructure
    • 3.2 Data Governance
    • 3.3 Investor Protection
    • 3.4 Market Structure
    • 3.5 Implications for Execution
    • 3.6 Research Unbundling
    • 3.7 Sourcing Functions Externally
  • 4.0 Capitalising on MiFID II Data Opportunities
    • 4.1 Information Portals
    • 4.2 Data as an Asset
    • 4.3 Data Mining, Artificial Intelligence and Machine Learning
    • 4.4 Leveraging Data to Meet Multiple Reporting Mandates
  • 5.0 Appendices
    • 5.1 Glossary of Terms
    • 5.2 Table of Figures