Jonathan Rusch's guest appearances

Jonathan Rusch

Democracy That Delivers

Compliance Perspectives

Gary Kalman

Michael Hershman

Richard Bistrong

Alison Taylor

Gerry Zack

Jason Ross

Nick Morgan

Richard Lewis

John Riggi

Jonathan Katz

James Green

Angel Romero

Jay Kogen

Willie Garson

Alison Lee

OwlTail

Post By: Adam TurteltaubCorporate anti-corruption efforts are a constant struggle, with compliance teams always searching for new approaches that can mitigate this very dangerous risk.Jonathan Rusch, an Adjunct Professor at Georgetown University Law Center and American University Washington College of Law, sees an opportunity in technology. He is the author of the Coalition for Integrity’s guidance document Using Machine Learning for Anti-Corruption Risk and Compliance.In this podcast he shares that in other areas, such as fraud and anti-money laundering (AML), some kind of Artificial Intelligence (AI), whether rules written by programmers or machine learning, has proven productive. The Coalition for Integrity wanted to know if a similar solution could work for anti-corruption efforts.In his and their research three successful implementations were found: AB InBev, Microsoft and Alexion Pharmaceuticals.When embarking on an effort in this area, he recommends first assessing what approach makes the most sense. For a smaller organization, a simpler, rules-based approach to automation is likely more appropriate.For larger organizations, he suggests building a business case that encompasses what needs to be done, the costs, the ongoing staffing requirements and the overall anticipated ROI.If machine-based learning could be worthwhile for your organization, he advises creating a clear definition of what you want the solution to address. From there it’s time to build your data set, work with the data and train the machine learning model. And, importantly, it’s also time to make sure the model is generating predictions that are accurate and reliable.  Often at the first stages it does not.When it comes to the data set, he notes that there may be more data within the enterprise than is initially thought. Data to consider incorporating into the effort could include spending, sales, accounts receivable, third-party contracts and third-party transactions.Intrigued?  Listen in to expand your learning about machine learning.

Post By: Adam Turteltaub Corporate anti-corruption efforts are a constant struggle, with compliance teams always searching for new approaches that can mitigate this very dangerous risk. Jonathan Rusch, an Adjunct Professor at Georgetown University Law Center and American University Washington College of Law, sees an opportunity in technology. He is the author of the Coalition for Integrity’s guidance document Using Machine Learning for Anti-Corruption Risk and Compliance. In this podcast he shares that in other areas, such as fraud and anti-money laundering (AML), some kind of Artificial Intelligence (AI), whether rules written by programmers or machine learning, has proven productive. The Coalition for Integrity wanted to know if a similar solution could work for anti-corruption efforts. In his and their research three successful implementations were found: AB InBev, Microsoft and Alexion Pharmaceuticals. When embarking on an effort in this area, he recommends first assessing what approach makes the most sense. For a smaller organization, a simpler, rules-based approach to automation is likely more appropriate. For larger organizations, he suggests building a business case that encompasses what needs to be done, the costs, the ongoing staffing requirements and the overall anticipated ROI. If machine-based learning could be worthwhile for your organization, he advises creating a clear definition of what you want the solution to address. From there it’s time to build your data set, work with the data and train the machine learning model. And, importantly, it’s also time to make sure the model is generating predictions that are accurate and reliable.  Often at the first stages it does not. When it comes to the data set, he notes that there may be more data within the enterprise than is initially thought. Data to consider incorporating into the effort could include spending, sales, accounts receivable, third-party contracts and third-party transactions. Intrigued?  Listen in to expand your learning about machine learning.

Jonathan Rusch on Machine Learning and Anti-Corruption Compliance [Podcast]

By Adam Turteltaubadam.turteltaub@corporatecompliance.orgThe words “Socratic Method” tend to conjure up images of law school professors boring into and humiliating ill-prepared students.   But, it shouldn’t necessarily be this way.  Instead, explains Jonathan Rusch, Adjunct Professor at the Georgetown University Law Center and Principal of DTG Risk &amp; Compliance, Socratic questioning is about learning by asking questions about a topic.As he wrote in a recent article and shares in this podcast, the object is to ask questions, listen for the answer and then follow up appropriately to ensure you are getting to the heart of the issue.  In addition, rather than the badgering seen in movies, it’s far better to maintain a measured, even tone.In many ways, it’s an approach reminiscent of the recent DOJ guidance for evaluating compliance programs, which is rich with questions.Listen in to learn more about the importance of doing your homework, carefully structuring questions, actively listening, focusing on topics (vs. individual questions) and being patient.

By Adam Turteltaub adam.turteltaub@corporatecompliance.org The words “Socratic Method” tend to conjure up images of law school professors boring into and humiliating ill-prepared students.   But, it shouldn’t necessarily be this way.  Instead, explains Jonathan Rusch, Adjunct Professor at the Georgetown University Law Center and Principal of DTG Risk &amp; Compliance, Socratic questioning is about learning by asking questions about a topic. As he wrote in a recent article and shares in this podcast, the object is to ask questions, listen for the answer and then follow up appropriately to ensure you are getting to the heart of the issue.  In addition, rather than the badgering seen in movies, it’s far better to maintain a measured, even tone. In many ways, it’s an approach reminiscent of the recent DOJ guidance for evaluating compliance programs, which is rich with questions. Listen in to learn more about the importance of doing your homework, carefully structuring questions, actively listening, focusing on topics (vs. individual questions) and being patient.

Jonathan Rusch on Socratic Questioning and Compliance [Podcast]

This week on Democracy That Delivers, host Ken Jaques is joined by Frank Brown, CIPE’s Director for the Anti-Corruption and Governance Center (ACGC), and guest Jonathan Rusch, lawyer and consultant on corporate-compliance issues, Adjunct Professor at Georgetown University Law Center. Rusch is also the editor of Dipping Through Geometries, a blog focusing on law and compliance issues, and the retired Senior Vice President and Head of Anti-Bribery &amp; Corruption Governance at Wells Fargo.   In this special episode, Rusch discusses how organizations, corporations, governments and leaders can achieve a culture of compliance. He also shares his insight on the four steps to moral ambition:  compliance moral understanding moral maturity moral ambition 

This week on Democracy That Delivers, host Ken Jaques is joined by Frank Brown, CIPE’s Director for the Anti-Corruption and Governance Center (ACGC), and guest Jonathan Rusch, lawyer and consultant on corporate-compliance issues, Adjunct Professor at Georgetown University Law Center. Rusch is also the editor of <a href="https://dippingthroughgeometries.blog/" rel="nofollow" target="_blank">Dipping Through Geometries</a>, a blog focusing on law and compliance issues, and the retired Senior Vice President and Head of Anti-Bribery &amp; Corruption Governance at Wells Fargo. In this special episode, Rusch discusses how organizations, corporations, governments and leaders can achieve a culture of compliance. He also shares his insight on the four steps to moral ambition: <ol> <li>compliance</li> <li>moral understanding</li> <li>moral maturity</li> <li>moral ambition</li> </ol>