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David Anderson - Talking Market Data

David Anderson - Talking Market Data

Written by: David Anderson
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If you work in financial 'Market Data' be you Data Vendor; Exchange; Technology/Service Provider; and especially if you work in a customer firm - we will be discussing all the burning issues and educating on core elements.

© 2026 David Anderson - Talking Market Data Economics Management Management & Leadership
Episodes
  • Episode 54 Robert Juguda (Universal Investment)

    Episode 54 Robert Juguda (Universal Investment)
    Oct 6 2026

    https://www.linkedin.com/in/robert-jaguda-fia-8a0814170/

    David Anderson speaks with Robert Jaguda about treating market data as strategic infrastructure rather than a back-office cost. Drawing on 15 years in financial services, Jaguda explains that reference, pricing, corporate-actions and other data underpin settlement, revenue calculations, regulation and client service. One incorrect value can trigger operational breaks and losses.

    Quality failures may stem from weak sources, incomplete coverage, delayed updates or manual errors. Because vendors often disclaim completeness and accuracy, firms must manage the risk. Jaguda recommends clear KPIs, monitoring delivery against an agreed universe, regular vendor dialogue and, where justified, comparing primary feeds with secondary or third sources to build a reliable golden copy.

    Commercial pressure also comes from rising prices, vendor dependency and cost-cutting. Firms should identify the data, fields and usage rights they genuinely need, then negotiate from evidence. Cutting spend without assessing risk can harm operations and profitability. Licensing terms must become practical guidance, supported by training and controls for internal, external, derived and non-display use.

    AI can flag anomalies and compare datasets, but skilled professionals remain essential across technology, operations, procurement, compliance and strategy. Jaguda urges newcomers to gain operational experience and firms to invest intelligently in contracts, governance and constructive provider relationships.

    DAVID ANDERSON -- https://www.linkedin.com/in/atradia/
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    59 mins
  • Episode 53 Andrea Young of KingsleyWood

    Episode 53 Andrea Young of KingsleyWood
    Sep 1 2026
    David has a conversation with Andrea Young a lawyer specilising in Market Datahttps://www.linkedin.com/in/andrea-c-e-young/https://www.kingsley-wood.com/This episode explores how market data licensing has become more complex, why a legal perspective matters, and where AI is starting to reshape both contracts and compliance. David Anderson speaks with Andrea Young, a lawyer building a market data practice, about the practical problems facing suppliers and data consumers. We discuss why legacy agreements are so hard to manage, why standardization remains elusive, and why AI is likely to force faster modernization across the industry.Key topics• Andrea Young explains her path into market data over the past five years, moving from corporate compliance into data compliance after working in Bermuda and London.• She shares why lawyers are still rare in market data and why the industry cannot be learned from textbooks alone.• David and Andrea discuss the gap between legal drafting and real market data use cases, especially when in-house legal teams do not fully understand licensing nuance.• Andrea describes why simplified licensing is best practice and why one exchange’s streamlined approach stood out as a model.• They unpack how decades of addendums, schedules, and outdated MSAs have created compliance chaos, especially when contracts still reference CD-ROMs and floppy disks.• The conversation covers why audit pressure makes the market more adversarial and why vendors often prefer ambiguity that strengthens their position.• They examine why industry-wide standards are unlikely, since exchanges and vendors monetize data differently and define terms like non-display use differently.• AI becomes the major focus toward the end, especially how it affects licensing, derived data, storage, distribution, attribution, and purge obligations.• Andrea argues that AI needs its own separate policy rather than being bolted onto existing non-display or derived data terms.• They discuss practical AI issues such as external versus internal models, training versus inference, retrieval augmented generation, and whether data can ever truly be purged from a model.• The episode closes on pricing pressure, with David arguing that AI will make more data valuable and more contentious, while Andrea warns that suppliers and consumers both need to stay proactive. Timestamps00:00 - Welcome and Andrea Young’s market data background01:25 - From corporate compliance to market data licensing03:15 - Why lawyers are rare in market data04:11 - Building a market data practice inside a law firm05:52 - How legal and M&A work intersect through relicensing06:54 - Drafting contracts versus compliance after the fact08:18 - Why clarity is the best licensing practice09:31 - Why market data contracts became so messy11:15 - Old MSAs, addendums, and unreadable contract archives13:25 - When messy licensing may benefit vendors in audits17:01 - Why standard contracts are unlikely to happen18:08 - Why definitions like non-display use still vary20:17 - Digital rights management and why automation is still far off23:31 - Why AI cannot yet read legacy licensing cleanly25:58 - Why advice depends on whether you serve suppliers or consumers26:44 - How audits are making the market more adversarial27:36 - Streamlining licensing for long-term business value28:46 - Advice for newer businesses and FinTechs30:34 - Why even large institutions often lack data governance visibility31:12 - The two AI buckets: business usage and operational usage33:13 - How AI is changing the legal field already34:15 - Why AI touches derived data, redistribution, and storage all at once37:03 - Why AI needs its own licensing policy38:36 - Training versus inference, and where RAG fits in40:12 - Purge clauses and the problem of deleting model-trained data41:32 - Whether contracts will need to name technologies like LLMs and RAG44:50 - How vendors are starting to package AI-specific data offerings46:25 - Attribution, watermarking, and AI-generated content47:27 - Copyright questions around AI-generated text48:25 - Why AI is useful but still needs human judgment49:52 - Using AI for search, productivity, and everyday work50:42 - The risk of losing junior talent if AI replaces entry-level work52:45 - The pricing question: whether AI makes older data more valuable55:13 - Why AI could make the market even more contentious56:44 - Why legal expertise in market data is becoming more important58:16 - Final advice: stay proactive, don’t wait for audits or AI incidents59:26 - Training the next generation of lawyers in market data60:50 - Closing thoughts and thanksDAVID ANDERSON -- https://www.linkedin.com/in/atradia/
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    1 hr and 1 min
  • Episode 52 Mike Salk

    Episode 52 Mike Salk
    Aug 4 2026

    Mike Salk - LinkedIn - https://www.linkedin.com/in/mikesalk

    In this episode, Mike Salk shares his extensive experience in market data, discusses the evolution of AI and its impact on financial markets, and explores the challenges of data quality, standardization, and trust in the industry.
    key topics:
    • The evolution of AI and its application in financial markets
    • Challenges of data quality, metadata, and standardization
    • The role of MCP and data protocols in data delivery
    • Trust and transparency between data vendors and consumers
    • The impact of AI on data management and cost efficiency

    DAVID ANDERSON -- https://www.linkedin.com/in/atradia/
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    58 mins
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