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Using Data to Manage Risk with Henry Stott

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Manage episode 456069914 series 3409321
Content provided by Ledn. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ledn or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In this episode of Because of Bitcoin, Mauricio Di Bartolomeo dives into the world of data-driven decision-making and risk analysis with Henry Stott. Henry’s career includes helping Tottenham Spurs with data-driven player selection, pioneering risk analysis models, and flagging FTX as a high-risk exchange months before its collapse. Learn how data transparency in digital assets can revolutionize risk management and why algorithms consistently outperform human experts in decision-making.

Key Topics Covered:

  • Henry’s Career Journey: From a dairy farm in Cheshire to data-driven innovations in finance, sports, and crypto.
  • Algorithms vs. Experts: Why machines are increasingly surpassing humans in complex decision-making.
  • Transparency in Blockchain: How on-chain data enhances risk assessment compared to traditional finance.
  • Spotting FTX’s Risk: Agio Ratings’ innovative approach to identifying high-risk digital asset exchanges.
  • Ledn’s A- Rating: What this top-tier credit rating means for the company and its clients.

Quotes to Remember:

  • "Algorithms beat experts by being consistent, data-driven, and free of emotional biases." — Henry Stott
  • "Transparency in digital assets opens doors for data integration that traditional finance lacks." — Henry Stott
  • "Risk ratings may not make headlines, but they protect participants from pitfalls." — Mauricio Di Bartolomeo

Links and Resources:

Thank You for Listening!

Enjoyed this episode? Please leave us a review and subscribe to Because of Bitcoin on your favorite podcast platform. Stay informed with our weekly newsletter at ledn.io.

  continue reading

34 episodes

Artwork
iconShare
 
Manage episode 456069914 series 3409321
Content provided by Ledn. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Ledn or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ppacc.player.fm/legal.

In this episode of Because of Bitcoin, Mauricio Di Bartolomeo dives into the world of data-driven decision-making and risk analysis with Henry Stott. Henry’s career includes helping Tottenham Spurs with data-driven player selection, pioneering risk analysis models, and flagging FTX as a high-risk exchange months before its collapse. Learn how data transparency in digital assets can revolutionize risk management and why algorithms consistently outperform human experts in decision-making.

Key Topics Covered:

  • Henry’s Career Journey: From a dairy farm in Cheshire to data-driven innovations in finance, sports, and crypto.
  • Algorithms vs. Experts: Why machines are increasingly surpassing humans in complex decision-making.
  • Transparency in Blockchain: How on-chain data enhances risk assessment compared to traditional finance.
  • Spotting FTX’s Risk: Agio Ratings’ innovative approach to identifying high-risk digital asset exchanges.
  • Ledn’s A- Rating: What this top-tier credit rating means for the company and its clients.

Quotes to Remember:

  • "Algorithms beat experts by being consistent, data-driven, and free of emotional biases." — Henry Stott
  • "Transparency in digital assets opens doors for data integration that traditional finance lacks." — Henry Stott
  • "Risk ratings may not make headlines, but they protect participants from pitfalls." — Mauricio Di Bartolomeo

Links and Resources:

Thank You for Listening!

Enjoyed this episode? Please leave us a review and subscribe to Because of Bitcoin on your favorite podcast platform. Stay informed with our weekly newsletter at ledn.io.

  continue reading

34 episodes

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