Difference between revisions of "Risk, Compliance and Regulation"

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* [[Risk, Compliance and Regulation]]  ... [[Ethics]]  ... [[Privacy]]  ... [[Law]]  ... [[AI Governance]]  ... [[AI Verification and Validation]]
 
* [[Risk, Compliance and Regulation]]  ... [[Ethics]]  ... [[Privacy]]  ... [[Law]]  ... [[AI Governance]]  ... [[AI Verification and Validation]]
 +
 
* [[Case Studies]]
 
* [[Case Studies]]
 
** [[Environmental Science]]
 
** [[Environmental Science]]
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*** [[Improper Payments]]
 
*** [[Improper Payments]]
 
* [[Cybersecurity]] ... [[Open-Source Intelligence - OSINT |OSINT]] ... [[Cybersecurity Frameworks, Architectures & Roadmaps | Frameworks]] ... [[Cybersecurity References|References]] ... [[Offense - Adversarial Threats/Attacks| Offense]] ... [[National Institute of Standards and Technology (NIST)|NIST]] ... [[U.S. Department of Homeland Security (DHS)| DHS]] ... [[Screening; Passenger, Luggage, & Cargo|Screening]] ... [[Law Enforcement]] ... [[Government Services|Government]] ... [[Defense]] ... [[Joint Capabilities Integration and Development System (JCIDS)#Cybersecurity & Acquisition Lifecycle Integration| Lifecycle Integration]] ... [[Cybersecurity Companies/Products|Products]] ... [[Cybersecurity: Evaluating & Selling|Evaluating]]
 
* [[Cybersecurity]] ... [[Open-Source Intelligence - OSINT |OSINT]] ... [[Cybersecurity Frameworks, Architectures & Roadmaps | Frameworks]] ... [[Cybersecurity References|References]] ... [[Offense - Adversarial Threats/Attacks| Offense]] ... [[National Institute of Standards and Technology (NIST)|NIST]] ... [[U.S. Department of Homeland Security (DHS)| DHS]] ... [[Screening; Passenger, Luggage, & Cargo|Screening]] ... [[Law Enforcement]] ... [[Government Services|Government]] ... [[Defense]] ... [[Joint Capabilities Integration and Development System (JCIDS)#Cybersecurity & Acquisition Lifecycle Integration| Lifecycle Integration]] ... [[Cybersecurity Companies/Products|Products]] ... [[Cybersecurity: Evaluating & Selling|Evaluating]]
 +
* [[Cybersecurity Frameworks, Architectures & Roadmaps#Zero Trust|Zero Trust]]
 
* [[Strategy & Tactics]] ... [[Project Management]] ... [[Best Practices]] ... [[Checklists]] ... [[Project Check-in]] ... [[Evaluation]] ... [[Evaluation - Measures|Measures]]
 
* [[Strategy & Tactics]] ... [[Project Management]] ... [[Best Practices]] ... [[Checklists]] ... [[Project Check-in]] ... [[Evaluation]] ... [[Evaluation - Measures|Measures]]
 
* [[Policy]]  ... [[Policy vs Plan]] ... [[Constitutional AI]] ... [[Trust Region Policy Optimization (TRPO)]] ... [[Policy Gradient (PG)]] ... [[Proximal Policy Optimization (PPO)]]
 
* [[Policy]]  ... [[Policy vs Plan]] ... [[Constitutional AI]] ... [[Trust Region Policy Optimization (TRPO)]] ... [[Policy Gradient (PG)]] ... [[Proximal Policy Optimization (PPO)]]
 
* [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
 
* [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ...  [[Algorithm Administration#Automated Learning|Automated Learning]]
 
* [[Algorithm Administration]]
 
* [[Algorithm Administration]]
−
** [[Data Governance]]
+
* [[Data Science]] ... [[Data Governance|Governance]] ... [[Data Preprocessing|Preprocessing]] ... [[Feature Exploration/Learning|Exploration]] ... [[Data Interoperability|Interoperability]] ... [[Algorithm Administration#Master Data Management (MDM)|Master Data Management (MDM)]] ... [[Bias and Variances]] ... [[Benchmarks]] ... [[Datasets]]
−
*** [[Algorithm Administration#Master Data Management (MDM)|Master Data Management (MDM)]]
 
 
* [[Analytics]] ... [[Visualization]] ... [[Graphical Tools for Modeling AI Components|Graphical Tools]] ... [[Diagrams for Business Analysis|Diagrams]] & [[Generative AI for Business Analysis|Business Analysis]] ... [[Requirements Management|Requirements]] ... [[Loop]] ... [[Bayes]] ... [[Network Pattern]]
 
* [[Analytics]] ... [[Visualization]] ... [[Graphical Tools for Modeling AI Components|Graphical Tools]] ... [[Diagrams for Business Analysis|Diagrams]] & [[Generative AI for Business Analysis|Business Analysis]] ... [[Requirements Management|Requirements]] ... [[Loop]] ... [[Bayes]] ... [[Network Pattern]]
 
* [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless, Generators, Drag n' Drop]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]
 
* [[Development]] ... [[Notebooks]] ... [[Development#AI Pair Programming Tools|AI Pair Programming]] ... [[Codeless Options, Code Generators, Drag n' Drop|Codeless, Generators, Drag n' Drop]] ... [[Algorithm Administration#AIOps/MLOps|AIOps/MLOps]] ... [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)|AIaaS/MLaaS]]

Revision as of 09:51, 14 July 2023

Youtube search... ...Google search


Risk

Youtube search... ...Google search


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Getting Started with Machine Learning in Risk Management
This week on Office Hours (https://officehou.rs), our OG hosts Dan Zitting and Kevin Legere are back and are ready to talk machine learning. We get a lot of questions about where to start with machine learning... lots of people in audit, risk, compliance, etc. are talking about it in principle but very few have started on a single practical use. In this episode, Kevin will show you where he actually got started using fancy words like k-means clustering to put machine learning to work in his actual job. Also, his Blue Jays hat in the shot is really gross (no one likes the Blue Jays) but Dan looks like he started combing his hair into a combover. Enjoy! ABOUT SERIES Office Hours is a work of passion to share strategies, technology ideas, and real-world stories that inspire governance, risk management, compliance, and audit professionals to live their biggest impact! Our channel is dedicated to delivering the best stories and strategies in developing GRC programs we've seen across 7,000 organizations in 140 countries around the world. In every episode we'll drill down on a topic that can help you level up - risk management, compliance automation, data analytics, next-generation auditing, robotic process automation, artificial intelligence, etc.

Artificial Intelligence (AI) in risk management - IBM, 4th-IR, Microsoft & Google
Imperial College Business School, Trestle Group and the IRM gathered experts from IBM, 4th-IR, Microsoft, and Google. - Bernhard Janischowsky (Trestle) - 00:00:05 - Tarun Ramadorai (Imperial) - 00:01:36 - Nicola Crawford (IRM Chair) - 00:04:25 - Raza Sadiq (IRM SIG Chair) - 00:05:47 - Grace Brasington (IBM) - 00:06:50 - Frank Luijckx (4th-IR) - 00:17:45 - Martin Moeller (Microsoft) - 00:26:26 - Matt McNeill (Google) - 00:33:43 - Panel discussion - 00:45:50

Machine Learning A revolution in risk management and compliance
Training on Machine Learning A revolution in risk management and compliance for FRM part 2 Current Issues including topics like Process of Machine Learning, Machine learning approaches, Application of machine learning approaches within the financial services sector, Application of machine learning in Credit risk and revenue modelling, Application of machine learning in Fraud Application of machine learning in Surveillance of conduct and market abuse in trading by Vamsidhar Ambatipudi

97 How might artificial intelligence affect risk management?
There's a lot of talk about artificial intelligence (AI) these days, and how it might change the world in the near future. Can AI help us manage risk better? David's answer is Yes and No!

AI Governance & Risk Management | Kartik Hosanagar | Talks at Google
Join Talks at Google for a conversation with Kartik Hosanagar, John C. Hower Professor of Technology and Digital Business at Wharton, about his new book A Human’s Guide to Machine Intelligence. The book is the result of years of Professor Hosanagar’s research, and explores the impact of algorithmic decisions on our personal and professional lives, and their unanticipated consequences. Kartik will explore how firms can make use of the tremendous opportunities and potential offered by machine learning and automated decision-making, while also doing their part to ensure algorithms are responsibly deployed. About Kartik: Kartik Hosanagar is the John C. Hower Professor of Technology and Digital Business at the University of Pennsylvania’s Wharton School of Business. Professor Hosanagar’s research focuses on the digital economy, in particular the impact of analytics and algorithms on consumers and society, Internet media, Internet marketing and e-commerce. Kartik has been recognized as one of the world’s top 40 business professors under 40.

AWS re:Inforce 2019: Leadership Session: Governance, Risk, and Compliance (GRC326-L)
Vice President of Security Chad Woolf, Director of Global Security Practice Hart Rossman, and Security Engineer Rima Tanash explain how governance functionality can help ensure consistency in your compliance program. Some specific services covered are Amazon GuardDuty, AWS Config, AWS CloudTrail, Amazon CloudWatch, Amazon Macie, and AWS Security Hub. The speakers also discuss how customers leverage these services in conjunction with each other. Additional attention is paid to the concept of ""elevated assurance,"" including how it may transform the audit industry going forward. Finally, the speakers discuss how AWS secures its own environment, as well as talk about the control frameworks of specific compliance regulations.

Using Historical Incident Data to Reduce Risks

  • cfxGenie | CloudFabrix ...Find your IT blind spots, assess problem areas or gain new insights from a sampling of your IT incidents or tickets

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CloudFabrix cfxGenie | Free IT Assessment Tool to Find Problem Areas & Accelerate AIOps Adoption
CloudFabrix Software Inc Find your IT blind spots and accelerate AIOps adoption with cfxGenie - Map/Zone incidents into quadrants to identify problem areas for prioritization - Cluster incidents based on symptoms and features to understand key problem areas. Get started now with your AIOps transformation journey. Signup for free cfxGenie Cloud Access, visit https://www.cloudfabrix.com/cfxgenie/

Compliance

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Transforming Compliance With Artificial Intelligence
Learn and grow with more BrightTALK webinars and Talks on FinTech Security right here: https://bit.ly/2q4NciN Join our live webinar to learn which elements of AI are driving value for risk and compliance? (i.e. ML, NLP, RPA). Also learn about AI in practice - how regulated financial institutions are utilizing AI today, why why AI is the only answer to addressing big data compliance challenges, at scale. We will also go over what happened when RegTech met SupTech – how are regulators are applying AI to ease and accelerate compliance processes.

Compliance.ai Introduction
Compliance.ai provides focused regulatory insight. Saving time, reducing cost & risk, while giving compliance officers much needed peace of mind.

AI augmenting compliance processes
Jorg Schaper, Global Head of Proposition, KYC & Future Screening Platform, Thomson Reuters, talks about the main challenges organisations are facing with compliance screening, the impact of artificial intelligence and machine learning on KYC and AML compliance processes and how regulation and technology will evolve in the coming years.

Machine learning: The future of compliance? - Sibos 2016
Machine Learning or Artificial Intelligence is gaining greater public and business awareness. From self-driving cars to cancer research, the long-predicted benefits are becoming reality. Machine Learning’s core characteristics – self-learning, intelligent yet consistent decision-making and managing complexity – are all attractive from a compliance perspective. What new technologies and approaches might support compliance programmes in the (near) future? Is the regulatory environment suitable for their adoption? How can the industry fully leverage the potential benefits?

Regulation

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AuditXPRT: AI Solutions for Regulatory Compliance and Audit
A brief introduction to AuditXPRT's iXPRT Platform, a unique Artificial Intelligence solution to automate regulatory compliance and audit. Automate the Mundane. Focus on the Value

Artificial Intelligence - AI - applied to Regulatory Compliance
https://BPA.Solutions applies Artificial Intelligence to regulatory compliance. The virtual AI Bot guides end-users to report an incident with their mobile device and log it in the BPA app on Microsoft Office 365.

Why do we need machine learning to effectively approach regulatory requirements?
avide Boselli, Senior Regulatory Analytics Consultant EMEA, Experian, picks apart the problems of using machine learning to meet regulatory needs. Visit RiskMinds International's official content site for the latest insights into risk management and for more exclusive thought leadership: https://bit.ly/2sav1ZI

How does AI have the potential to transform regulatory compliance?
IBM Global Vice President of Watson Financial Services, Vivek Bajaj, participates in an Ask Me Anything where he discusses how artificial intelligence and cognitive computing can augment, but not replace human tasks in regulatory compliance. For more information, please visit: ibm.com/regtech

CognitiveScale - Certifai

YouTube Search ...Google search

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Tech Showcase Demo: Cognitive Scale | VB Transform 2019
Tech Showcase Demos: Cognitive Scale, Applied Brain Research, integrate.ai, AI Foundry, D-ID

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