<![CDATA[Stack-to-Street]]>Open-Source Tools for Leaders in Finance.

Stack-to-Street explores open-source tools, AI projects, workflows, and technical builders that can help banks, investment managers, brokerage firms, and private-credit platforms improve decisions, serve clients, and create commercial advantage.

]]>www.stacktostreet.comRiverside.fm (https://riverside.com)Mon, 02 Nov 2026 13:53:15 GMTSat, 19 Sep 2026 19:28:32 GMT60Michael McLaughlin, Path66<p>Open-Source Tools for Leaders in Finance.<br /><br />Stack-to-Street explores open-source tools, AI projects, workflows, and technical builders that can help banks, investment managers, brokerage firms, and private-credit platforms improve decisions, serve clients, and create commercial advantage.</p>episodicMichael McLaughlin, Path66michael.mclaughlin@path66.comno<![CDATA[Lloyd O'Connor: Cybersecurity Is a Business Problem]]>An executive spending a billion dollars a year on cyber protection asked if that guaranteed he would never be breached. Lloyd O'Connor's answer was no.

Lloyd O'Connor helped pioneer Chase Quick Deposit and worked on cybersecurity at JPMorgan and Barclays before founding Aceiss. We talk about why companies of every size struggle to know who has access to their systems, why AI agents make that problem harder, and what leaders can do first.

Guest: Lloyd O'Connor, Founder and CEO of Aceiss
Host: Michael McLaughlin
Episode page: https://www.stacktostreet.com/episodes/aceiss/

Chapters:
00:00 The billion-dollar moat
00:38 Welcome to Stack to Street
01:32 An API key scare
02:11 JPMorgan and hidden access
05:27 Depositing a check with a photo
07:55 Security for smaller firms
08:17 Three basics of cyber hygiene
11:41 AI agents and access
14:14 Customers using consumer agents
15:45 Who is accountable for an agent?
19:03 Assume you will be breached
20:09 Know your systems, least privilege
22:57 Submarines vs. thirty-foot yachts
23:20 Protect your source code first
26:10 You can't protect what you can't see
30:48 Two questions for every executive
31:43 How to find Aceiss

Links:
Aceiss: https://www.aceiss.com
Aceiss on GitHub: https://github.com/aceiss
Stack to Street: https://www.stacktostreet.com

Subscribe for conversations with people building the open-source tools finance teams actually use.

]]>http://www.stacktostreet.combe5e0e91-3836-4fa9-8e3e-e167bf99b63bWed, 28 Oct 2026 16:41:56 GMT<p>An executive spending a billion dollars a year on cyber protection asked if that guaranteed he would never be breached. Lloyd O'Connor's answer was no.<br /><br />Lloyd O'Connor helped pioneer Chase Quick Deposit and worked on cybersecurity at JPMorgan and Barclays before founding Aceiss. We talk about why companies of every size struggle to know who has access to their systems, why AI agents make that problem harder, and what leaders can do first.<br /><br />Guest: Lloyd O'Connor, Founder and CEO of Aceiss<br />Host: Michael McLaughlin<br />Episode page: <a href="https://www.stacktostreet.com/episodes/aceiss/" rel="noopener noreferrer nofollow">https://www.stacktostreet.com/episodes/aceiss/</a><br /><br />Chapters:<br />00:00 The billion-dollar moat<br />00:38 Welcome to Stack to Street<br />01:32 An API key scare<br />02:11 JPMorgan and hidden access<br />05:27 Depositing a check with a photo<br />07:55 Security for smaller firms<br />08:17 Three basics of cyber hygiene<br />11:41 AI agents and access<br />14:14 Customers using consumer agents<br />15:45 Who is accountable for an agent?<br />19:03 Assume you will be breached<br />20:09 Know your systems, least privilege<br />22:57 Submarines vs. thirty-foot yachts<br />23:20 Protect your source code first<br />26:10 You can't protect what you can't see<br />30:48 Two questions for every executive<br />31:43 How to find Aceiss<br /><br />Links:<br />Aceiss: <a href="https://www.aceiss.com" rel="noopener noreferrer nofollow">https://www.aceiss.com</a><br />Aceiss on GitHub: <a href="https://github.com/aceiss" rel="noopener noreferrer nofollow">https://github.com/aceiss</a><br />Stack to Street: <a href="https://www.stacktostreet.com" rel="noopener noreferrer nofollow">https://www.stacktostreet.com</a><br /><br />Subscribe for conversations with people building the open-source tools finance teams actually use.</p>no00:33:56Lloyd O'Connor: Cybersecurity Is a Business Problemfull<![CDATA[Dominic O'Kane: From Physics to Wall Street to FinancePy]]>In 1994, Salomon Brothers' risk system crashed overnight because interest rates went negative, something the models said could never happen. Dominic O'Kane has spent 30 years closing the gap between textbook models and trading-floor reality.


Dominic is a physicist turned Wall Street quant. He led quantitative research in Europe at Lehman Brothers, wrote the book on credit derivatives, and taught finance for nearly two decades. We talk about what a sell-side quant actually does, how correlation risk drove bonus pools before 2008, and why he built FinancePy, a free, open-source Python library for pricing derivatives.


If you're a quant, a student, or on the buy side and want to check a price, this one is for you.


Chapters

00:00 When Interest Rates Went Negative

00:36 Introduction to the Podcast and Guest

01:12 From Physics to Wall Street

04:29 Lehman Brothers and Credit Derivatives

08:13 The Role of a Sell-Side Quant

13:15 Why Dominic Built FinancePy

17:25 Why Transparency Matters in Models

19:07 The Models in FinancePy

21:56 Correlation Risk and Overnight Risk Runs

28:04 How the Quant Role Has Evolved

32:06 Who Should Use FinancePy


Mentioned in this episode

FinancePy on GitHub: https://github.com/domokane/FinancePy

QuantLib: https://www.quantlib.org

Numba: https://numba.pydata.org

Dominic's book: Modelling Single-name and Multi-name Credit Derivatives (Wiley)

Options, Futures and Other Derivatives by John Hull


Subscribe to Stack to Street for more conversations with the people building software worth watching.

]]>http://www.stacktostreet.com06d74dc6-4534-4d76-a1f2-47932437931bSun, 18 Oct 2026 17:37:37 GMT<p>In 1994, Salomon Brothers' risk system crashed overnight because interest rates went negative, something the models said could never happen. Dominic O'Kane has spent 30 years closing the gap between textbook models and trading-floor reality.</p><p><br /></p><p>Dominic is a physicist turned Wall Street quant. He led quantitative research in Europe at Lehman Brothers, wrote the book on credit derivatives, and taught finance for nearly two decades. We talk about what a sell-side quant actually does, how correlation risk drove bonus pools before 2008, and why he built FinancePy, a free, open-source Python library for pricing derivatives.</p><p><br /></p><p>If you're a quant, a student, or on the buy side and want to check a price, this one is for you.</p><p><br /></p><p>Chapters</p><p>00:00 When Interest Rates Went Negative</p><p>00:36 Introduction to the Podcast and Guest</p><p>01:12 From Physics to Wall Street</p><p>04:29 Lehman Brothers and Credit Derivatives</p><p>08:13 The Role of a Sell-Side Quant</p><p>13:15 Why Dominic Built FinancePy</p><p>17:25 Why Transparency Matters in Models</p><p>19:07 The Models in FinancePy</p><p>21:56 Correlation Risk and Overnight Risk Runs</p><p>28:04 How the Quant Role Has Evolved</p><p>32:06 Who Should Use FinancePy</p><p><br /></p><p>Mentioned in this episode</p><p>FinancePy on GitHub: <a href="https://github.com/domokane/FinancePy" rel="noopener noreferrer nofollow">https://github.com/domokane/FinancePy</a></p><p>QuantLib: <a href="https://www.quantlib.org" rel="noopener noreferrer nofollow">https://www.quantlib.org</a></p><p>Numba: <a href="https://numba.pydata.org" rel="noopener noreferrer nofollow">https://numba.pydata.org</a></p><p>Dominic's book: Modelling Single-name and Multi-name Credit Derivatives (Wiley)</p><p>Options, Futures and Other Derivatives by John Hull</p><p><br /></p><p>Subscribe to Stack to Street for more conversations with the people building software worth watching.</p>no00:36:592Dominic O'Kane: From Physics to Wall Street to FinancePyfull<![CDATA[Your Firm’s Most Valuable Data Is Trapped in Meetings]]>Finance runs on meetings, but the knowledge from those meetings often has no real home.


In this first episode of Stack-to-Street, Michael McLaughlin talks with Dmitry Grankin, founder of Vexa, about turning live meeting conversations into company knowledge that firms can control, search, and use inside their own workflows.


For leaders in banking, credit, investing, and financial services, the question is simple: if meetings are where trust is built and decisions are made, who owns the data after the call ends?

]]>8f962055-52ca-4427-8209-788b9bfd6f51Mon, 05 Oct 2026 12:01:39 GMT<p>Finance runs on meetings, but the knowledge from those meetings often has no real home.</p><p><br /></p><p>In this first episode of Stack-to-Street, Michael McLaughlin talks with Dmitry Grankin, founder of Vexa, about turning live meeting conversations into company knowledge that firms can control, search, and use inside their own workflows.</p><p><br /></p><p>For leaders in banking, credit, investing, and financial services, the question is simple: if meetings are where trust is built and decisions are made, who owns the data after the call ends?</p>no00:17:511Your Firm’s Most Valuable Data Is Trapped in Meetingsfull