About Us

We are a group of industry professionals as well as trainers specializing in data and AI. Our objective is to share industry best practices in the area of AI and data governance.

This site is designed as a free global resource to facilitate researchers and practitioners and any interested persons in their research and consulting work relating to AI governance.

We have prepared a compendium of papers (in the form of an e-handbook) which in a single volume compiles publicly accessible materials covering thought leadership on AI governance, frameworks, practices, and software solutions.

This e-handbook targets researchers and practitioners who serve government agencies, companies, organizations and non-profits.

This e-handbook will be edited as a live resource to enable readers to be continually updated.

Students who are new to AI governance would also find the compilation of resources handy for their learning journey.


Copyright in materials

We have sought permission from the respective copyright owners of the materials compiled in the e-handbook.

The copyright in these materials remains with the organizations as indicated in this e-handbook.

The Editor of the e-handbook, Zaid Hamzah, does not claim any copyright over any of these materials.

 

 

Course Outlines

AI Governance


Overview

In recent years, the world has seen significant advances in the sophistication and pervasive use of AI. Governments, enterprises and organizations have begun issuing principles, frameworks and recommendations on AI ethics and governance. The rise of a data and AI-driven economy necessitate enterprises, organizations and governments to build new capabilities on data and AI governance among its employees, partners, vendors and any entities that have any dealing in the deployment of AI. This program seeks to provide a practical overview on the process of designing, developing and implementing an AI governance framework for organizations. It provides real world examples of how AI governance frameworks can be developed in practice.


Who should attend

  • ● ICT professionals including data and AI engineer, data analysts, data scientists
  • ● C-suite executives including CEOs, CTOs, CDOs , CMOs , CLO , CCO s.
  • ● Business executives and government officers (including those with non-technical backgrounds)


Learning Outcomes

At the end of this 1-day program, participants will be able to:

  1. ● Design, develop and implement an AI governance framework that can readily be deployed in practice;
  2. ● Oversee the execution of a sound AI governance program to better manage organizational risks while rolling out AI programs and initiatives;
  3. ● Develop key performance indicators for AI governance frameworks and programs.


AI Governance Framework

      ● Objectives of deploying AI
      ● Nature of an AI Governance
      ● Distinction between data and AI governance framework
      ● AI Governance as part of Corporate Strategy


AI Ethical Principles

  1. 1. Accountability
  2. 2. Accuracy
  3. 3. Auditability
  4. 4. Traceability
  5. 5. Explainability
  6. 6. Fairness
  7. 7. Human centricity and well being
  8. 8. Human rights alignment
  9. 9. Inclusivity
  10. 10. Progressiveness
  11. 11. Responsibility, accountability and transparency
  12. 12. Robustness and security
  13. 13. Sustainability


Internal Governance Structure and Measures

      ● Clear role and responsibilities for ethical deployment of AI
      ● Risk management and internal controls


Level of Human Involvement in AI-augmented Decision Making

      ● Human-in-the-loop
      ● Human-out-of-loop
      ● Human-over-the-loop


Operations Management

      ● Data preparation
      ● Algorithm development
      ● Choose model
      ● Data for model development
      ● Data lineage and provenance record
      ● Ensuring data quality
      ● Probability-Severity of Harm Matrix
      ● Minimizing inherent bias
      ● Selection bias
      ● Measurement bias
      ● Different datasets for training, testing and validation
      ● Periodic review and updating of datasets
      ● Algorithm and Model
      ● Repeatability
      ● Regular tuning
      ● Reproducibility


Stakeholder Interaction and Communication

      ● General disclosure
      ● Policy for explanation
      ● Interacting with consumers
      ● Option to opt-out
      ● Communication channels
      ● Acceptable user policies
      ● Interacting with other organizations
      ● Ethical evaluation


Model AI Governance Framework

The need to be:

      ● Algorithm-agnostic
      ● Technology-agnostic
      ● Sector-agnostic
      ● Scale and Business Model-agnostic


Use Cases and Case Studies in Industry

      ● Facebook
      ● Microsoft
      ● Cujo AI
      ● Mastercard
      ● Suade Labs
      ● Grab
      ● Pymetrics
      ● Symphony Ayasdiai
      ● MSD

Data Governance

How to Design, Deploy and Sustain an Effective Data Governance Program

As more and more organizations move data to the cloud, the comprehensive approach to data governance has become a new organizational imperative, along with well-defined policy framework to ensure organizations meet compliance requirements. Data governance covers the ways people, processes and technology work together to ensure that data is trustworthy and can be used effectively by organizations. This practical course will guide participants on how to design, develop, implement and scale data governance throughout the organization. Using real world practical examples, this course will guide participants on strategies, programs and tools to unlock data value while enforcing security, privacy and governance standards. Through good data governance, organizations can inspire customer trust, identify business efficiencies and enhance the organizations’ competitive offerings.


Who should attend

      ● ICT professionals including data and AI engineer, data analysts, data scientists
      ● C-suite executives including CEOs, CTOs, CDOs , CMOs , CLO , CCO s.
      ● Business executives and government officers (including those with non-technical backgrounds)


Learning Outcomes

At the end of this 1-day program, participants will be able to:

  1. 1. Design data governance strategies covering people, processes, technologies and tools;
  2. 2. Initiate, develop and implement a data governance framework that can readily be deployed in practice to maximize the benefits and manage the challenges in a data-driven business environment;
  3. 3. Oversee the execution of a sound data governance program to better manage organizational risks while rolling out data-driven programs and initiatives covering among others, data quality and data protection;
  4. 4. Develop key performance indicators for data governance frameworks and programs including building a robust data culture in organizations and ensuring sustainability; and
  5. 5. Implement a practical, cost effective (& money saving) data governance programs


What is Data Governance

        ● The Business Context
        ● Why Data Governance is becoming more critical for organizations
        ● The Business Value of Data Governance – Data governance business case
        ● Big picture (vision, mission) – define business value of data governance program
        ● Business alignment – identify business benefits & metrics, align data governance with business needs
        ● Data monetization
        ● Data as corporate asset
        ● Risk Management & Data Governance
        ● Theft, misuse & data corruption
        ● Examples of successful data governance strategies
        ● Regulatory Compliance: The Challenges of New regulations
        ● Ethical concerns around data use
          ● What Data Governance entails
          ● Scope of Data Governance & Data Management
          ● Policy Framework design and development
          ● Determine baseline policy requirements
          ● Identify use cases to demonstrate value
          ● Holistic approach to data governance
          ● Development Methods
          ● Federation
          ● Core Principles
          ● Policies
          ● Metrics to measure effectiveness, efficiency
          ● Data governance in the cloud
          ● Enhancing Trust in Data
          ● Classification and access control
          ● Data governance versus data
        enablement and data security
        ● Incident handling
        ● Data use cases


Elements of Data Governance Framework

      ● Tools, People and Processes
      ● Data classes, data policies, data cataloguing & metadata management
      ● User authorization and access management
      ● People’s roles & responsibilities
      ● People & processes together: Considerations, issues


Data Life Cycle Management

      ● Phases of Data Life Cycle
      ● Data creation, cleaning, processing, structuring, modelling, deployment, storage, usage, archiving & destruction
      ● Workflow management for data acquisition
      ● Data management plan
      ● Applying governance over the data life cycle
      ● Data assessment and profiling
      ● Improving Data Quality
      ● Lineage tracking, types of lineage
      ● Data quality in big data analytics
      ● Data quality in AI/ML models
      ● Techniques for data quality management
      ● Scorecard
      ● Prioritization
      ● Annotation
      ● Profiling
      ● Cost of data quality issues


Operationalizing Data Governance

      ● Data governance policy
      ● Building internal & external trust
      ● Transparency
      ● Developing policy structure
      ● Engagement & buy in – engagement model
      ● Strategy
      ● Charters, policies and standards
      ● Data governance delivery framework
      ● Architecture and design
      ● Align and prioritize
      ● Identify tools and technology support
      ● Operating framework
      ● Roles and responsibilities
      ● Step by step guidance


Legal and Compliance: Data Protection & Compliance Requirements

      ● Personal Data Protection Act
      ● Cybersecurity Act
      ● Computer Misuse Act


Monitoring of Data Governance Programs

      ● Why perform monitoring?
      ● Data quality monitoring
      ● Data lineage monitoring
      ● Program performance monitoring
      ● Security monitoring
      ● Compliance monitoring
      ● Monitoring system
      ● Analysis in real time
      ● System alerts
      ● Notifications
      ● Reporting & analytics
      ● Customization
      ● Monitoring criteria


Building a Culture of Data Privacy & Security

      ● Data culture – what it is & why it is important
      ● Leadership – starting at the top & the cascading effects
      ● Benefits of data governance to businesses
      ● Approaches: low profile, central
    controlled, agile or traditional
      ● Maintaining agility
      ● Peoples Dimensions
      ● Business and technical capabilities needed
      ● Roles & responsibilities
      ● Team structure & business units
      ● Organizational persona and perception
      ● Training
      ● Communications
      ● Scaling the data governance process up and down
      ● Data value & sustainability


Data Governance in Practice

      ● Roadmapping (short and long term deployment plans)
      ● Managing discoverability, security and accountability
      ● Assessment (information maturity, change capacity, data environment)
      ● Policy management, simulation, monitoring & change management
      ● Sustaining Plans
      ● Operations and changes
      ● Rollout plans
      ● Technology solutions
      ● Audit & Compliance
      ● Case Studies
      ● Google Internal Data Governance
      ● Microsoft Data Governance Practices

Training Approach


Training Strategy and Pedagogy

All training should result in organizations performing better. In delivering our courses, we adopt a learning and development framework called PEbAAL which stands for Performance-based, Experiential, Adaptive & Agile Learning.


Performance-based, Experiential, Adaptive & Agile Learning

The PEbAAL framework focuses on driving performance for organizations through experiential, adaptive and agile learning.

Our courses are focused on delivering outcomes and are tailored to suit the needs of organizations especially in the area of problem solving or value creation for organizations.

While most of the courses covered in this program are 1-day courses, the programs can be adapted to suit any duration to suit the needs of the organizations based on the principles of learning agility and flexibility.

Typically, C-suite executives attend very short courses lasting 2 to 3 hours only while middle management as well as the operational teams attend courses with a duration of between 1 to 2 days (8 hours per day).


Mode of Delivery

Our courses are typically tailored to suit the needs of the organizations especially the preferred mode of delivery. We typically adopt a hybrid model of learning including instructor-led synchronous as well as asynchronous training.

We also provide a cloud Learning Management System (LMS) system for organizations that requires such cloud systems to manage their learners’ learning journey. Where organizations have their own LMS, we offer services to integrate our contents and pedagogical strategies with their cloud LMS.


Business and Training Needs Analysis

The implementation of our PEbAAL framework typically starts with a business needs as well as a training needs analysis (TNA) involving both the organization as well as the learners, especially those at supervisory levels.

Upon completion of the TNA, we then embark on the learning program design and development before rolling out the program.

We adopt a 7 Step approach in carrying out a strategic review as well gap analysis for organizations before the commencement of any training programs.


Outcome-based Learning

We collaborate with our partners and clients to offer outcome-based learning that focuses on performance based on the key performance indicators for organizations.

For evaluation of training effectiveness, we focus primarily on organizational or business impact as well securing the returns on investment in training and development as shown in the chart below:


Implementation of Learning Outcomes at the Workplace

Under the PEbAAL framework, learning must ultimately lead to better organizational performance. Learnings must therefore be implemented at the workplace in order to secure the required organizational impact.

In our programs, we typically monitor how the learnings are implemented over a period of time (which varies according to the needs of the organization) as shown in the following chart:

 

 

 

 

Advisor


Garret Teoh

Garrett is a data science professional who provides data science consulting services to businesses and governments focusing on strategies, techniques and implementations for data science projects. He has over 15 years of professional experience spanning the biomedical, fintech, government, telco and machine learning verticals. Garrett is currently Head (Senior Director), Data & Analytics, Capgemini Invent where he is responsible for leading and growing the data & analytics practice for multi industries and capability groups across South-east Asia.

Garrett has previously served, among others, as (1) Director of Applied Intelligence, Accenture, where he was responsible for providing analytics consultancy and delivering solutions within the ASEAN region; (2) Head of Artificial Intelligence at Ascend Money, a regional fintech company in Southeast Asia which is part of Thai conglomerate CP where he was responsible for managing all data science and artificial intelligence demands across Ascend group, serving analytics and intelligence to functional teams within local and regional business.

Garrett is an instructor for General Assembly data analytics course and Master Kaggler with 6 medals. Holding a Computer Science bachelor’s degree from Monash University and a MSc from Singapore’s Nanyang Technological University in Biomathematics, Bioinformatics and Computational Biology, Garrett has co-authored several biomedical publications in leading journals. Garrett has deep expertise in most common data science tools which includes R, Python, Tableau, and SQL and capable of writing production level codes, deploy and integrate into business processes and systems.

He mastered statistical techniques and analytical methods whilst serving Agency for Science, Technology and Research as their Lead Bioinformatician for Infectious Disease Lab at Genome Institute of Singapore. The next chapter of his professional advancement revolves around providing pre-sales consultancy advice, leading to the delivery of data science projects, mainly for the government agencies in Singapore, which covers sectors in the transportation, social services, healthcare, defense, national securities, and the education domain.

His involvement in the Fintech and e-Commerce industries covers the design and implementation of various data science initiatives which includes, credit/risk scoring system, recommendation engine, and fraud detections. Until this day, the ‘geek’ side of him still resides in him and he likes to research and experiment new machine learning algorithms, tuning parameters and evaluate model performances during his free time.

 

 

 

 

Advisor


Dr Eric Tham

Dr Eric Tham specialises in AI and data science, with applications in the financial sector. He is currently Senior Lecturer, James Cook University and was formerly a senior lecturer at the National University of Singapore. He has over 20 years of experience in the finance sector and has expertise in natural language processing and machine learning in financial applications.

Prior to his university stint, he has diverse experiences in the financial services in risk, quantitative analysis and energy economics including working with Thomson Reuters, London Metal Exchange, Credit Suisse and Standard Chartered Bank. Eric holds a Phd from EDHEC and has two Masters degrees, one from NUS and another from Columbia University (Financial Engineering). He is a regular speaker in AI and sentiment analysis in finance conferences. He has published articles on Fintech, derivatives pricing and AI, and is presenting writing a book on AI in Finance.

 

 

 

 

Trainers


Zaid Hamzah

Trainer for:

      ● AI Governance
      ● Data Governance
      ● Soft Skills for Data & AI Project Management
      ● Strategic Data Asset Management
      ● Cybersecurity Governance, Risk and Compliance
      ● Strategic Intellectual Property Management
      ● Fintech Commercialization

Admitted as Advocate and Solicitor, Singapore and Solicitor, England & Wales, Zaid is a technology lawyer with 35 years of professional experience in the legal, technology and government sectors. Specializing in data analytics, artificial intelligence and intellectual property in the legal, training and education sectors, Zaid is at present CEO of the Asia Law Exchange, a managed legal service provider specializing in legal innovation platforms. He is a Board member of NIE International Pte Ltd where he focuses on the internationalization and digitalization of NIE’s services. Zaid is active in several AI and data ventures including one in food security.

He has previously served as Director at Microsoft Inc, Chief Legal and Regulatory Officer at publicly listed Telekom Malaysia, Senior Advisor at Singapore Telecommunications Limited (“Singtel). Zaid practised law with Singapore law firm Khattar Wong & Partners. His industry experience in the area of technology, media and telecommunication includes end to end IT services, enterprise apps development, digital transformation services, deployment of internet of things solutions and developing multi-sided data-driven platform businesses.

Zaid has in-depth expertise in strategic legal risk management as well as transactional support in terms of regulatory compliance, corporate governance as well as contract negotiation and management. He provides both strategic as well as operational advice that deals with general corporate/commercial matters, dispute resolution and employment matters. At the operational level, Zaid has experience in developing and implementing personal data protection policies and procedures, corporate policies and standard operating procedures to protect data and intellectual property assets and putting in place control measures to ensure compliance with listing requirements.

A Singaporean national, Zaid graduated with a law degree from the National University of Singapore in 1984 and completed his master’s in international relations at the Fletcher School of Law and Diplomacy, Tufts University, USA in 1992 on a Fulbright scholarship.


Academic Role (part time/Adjunct)

Present

      ● Adjunct Senior Fellow, S Rajaratnam School of International Studies (RSIS), Nanyang Technological University, Singapore, teaching “Cybersecurity Law, Cyber Terrorism and Managing the New Geo-Strategic Risks”.
      ● Trainer in Cybersecurity Law, Governance, Risk & Compliance at Cyber Defence Academy, part of the SSA Academy
      ● Content developer, course designer and trainer in Data & AI in Regulatory Compliance and Financial Crime Compliance for the International Compliance Association.
      ● Trainer, Masterclass on “Cybersecurity & Payment Services” and “Effective Use of Technology in Governance, Risk & Compliance”, International Compliance Association, ICTA


Past

      ● Adjunct Faculty at the School of Law, Singapore Management University teaching “Legal Analytics and Artificial Intelligence in Law”
      ● Taught Intellectual Property Management at both the Singapore Management University and the Nanyang Technological University as Adjunct Faculty
      ● Trainer at the IP Academy in Singapore and has participated regularly as a trainer at the World intellectual Property (WIPO) programs in Singapore, Malaysia and China.
      ● At the National University of Singapore, Zaid has previously developed the online course for the Institute of Systems Science’s program for the Certified Information Systems Security Professional certification (CISSP) domain for law, investigation and ethics.
      ● Served as Visiting Associate Professor at the University of Malaya law school where he taught E-Business Law and as an Adjunct Lecturer at Universiti Teknologi Malaysia where he taught E-Security Law & Strategy
      ● Taught “Laws of Investment and Financial Market at RMIT program with SIM GE, Singapore.


    Published Books

    Technology, Intellectual Property & Risk Management

    1. 1. E-Security Law & Strategy, Lexis Nexis, April 2005
    2. 2. Media & Entertainment: A Legal, Business and Strategy Guide, Sweet Maxwell, Oct 2013
    3. 3. Creating Value from Technology Innovation, International Law Book Services, Aug 2011
    4. 4. Strategic Legal Risk Management in an Innovation Economy, Lexis Nexis, Jan 2010
    5. 5. Information Technology Contracts, Lexis Nexis September 2005
    6. 6. Intellectual Property Law & Strategy, Sweet & Maxwell, June 2006
    7. 7. Biomedical Science Law and Practice, Sweet & Maxwell, August 2007
    8. 8. Biotechnology Law & Strategy Lexis Nexis, August 2005 Financial Services
    9. 9. Islamic Private Equity & Venture Capital: Principles and Practice, Islamic Banking & Finance Institute Malaysia, December 2011


    Practice Areas & Research Interest

    1. 1. Legal Analytics and Artificial Intelligence in Law
    2. 2. Cybersecurity Law & Investigation (including legal aspects of computer forensics)
    3. 3. Data Innovation and Monetization
    4. 4. Technology, Media & Telecommunication Law & Policy (including personal data protection)
    5. 5. Smart City Laws
    6. 6. Intellectual Property, Intellectual Capital & Technology Innovation
    7. 7. Venture Capital & Private Equity (including Islamic Finance)
    8. 8. Strategic Futures Thinking & Strategic Learning for Performance


    Garrett Teoh

    AI & Data Science Trainer

    Garrett is a data science professional who provides data science consulting services to businesses and governments focusing on strategies, techniques and implementations for data science projects. He has over 15 years of professional experience spanning the biomedical, fintech, government, telco and machine learning verticals. Garrett is currently Head (Senior Director), Data & Analytics, Capgemini Invent where he is responsible for leading and growing the data & analytics practice for multi industries and capability groups across South-east Asia.

    Garrett has previously served, among others, as (1) Director of Applied Intelligence, Accenture, where he was responsible for providing analytics consultancy and delivering solutions within the ASEAN region; (2) Head of Artificial Intelligence at Ascend Money, a regional fintech company in Southeast Asia which is part of Thai conglomerate CP where he was responsible for managing all data science and artificial intelligence demands across Ascend group, serving analytics and intelligence to functional teams within local and regional business.

    Garrett is an instructor for General Assembly data analytics course and Master Kaggler with 6 medals. Holding a Computer Science bachelor’s degree from Monash University and a MSc from Singapore’s Nanyang Technological University in Biomathematics, Bioinformatics and Computational Biology, Garrett has co-authored several biomedical publications in leading journals. Garrett has deep expertise in most common data science tools which includes R, Python, Tableau, and SQL and capable of writing production level codes, deploy and integrate into business processes and systems.

    He mastered statistical techniques and analytical methods whilst serving Agency for Science, Technology and Research as their Lead Bioinformatician for Infectious Disease Lab at Genome Institute of Singapore. The next chapter of his professional advancement revolves around providing pre-sales consultancy advice, leading to the delivery of data science projects, mainly for the government agencies in Singapore, which covers sectors in the transportation, social services, healthcare, defense, national securities, and the education domain.

    His involvement in the Fintech and e-Commerce industries covers the design and implementation of various data science initiatives which includes, credit/risk scoring system, recommendation engine, and fraud detections. Until this day, the ‘geek’ side of him still resides in him and he likes to research and experiment new machine learning algorithms, tuning parameters and evaluate model performances during his free time.


    Horace Wu

    Trainer for:

        ● Legal AI and Analytics
        ● Legal Innovation & Entrepreneurship
        ● Knowledge Management for Lawyers and Law Firms

    Horace is the founder and managing director of Syntheia, an AI-driven knowledge platform for lawyers (www.syntheia.io). Syntheia is a multi-purpose knowledge platform for lawyers that provides easy one-click access to useful legal information. Horace spent over a decade practicing as a banking and finance lawyer and an M&A lawyer for top tier law firms in Australia and the US including King & Wood Mallesons, Shearman & Sterling and DLA Piper. Horace has worked as an in-house legal counsel for listed Australian companies, primarily supporting those companies in global expansion projects, including expansions in the US and in Africa.

    Prior to Syntheia, Horace founded a consumer-facing app that provided users with personalized recommendations for events and entertainment by learning their individual preferences. Originally from Sydney, Australia, Horace relocated to New York in 2019 and has been growing Syntheia’s business internationally, advising on and creating tailored solutions for law firms that leverage legal data. As a platform Syntheia closes the gap between lawyers and the knowledge they need. Syntheia’s natural language processing system recommends relevant and useful examples of legal drafting from documents.

    Horace serves as a non-executive director on the board of the Australian Legal Technology Association, and he is a member of ILTA's (International Legal Technology Association) Knowledge Advisors. Having practiced as a lawyer for many years, Horace has a special interest in creating and building products that make it easy to access, analyze and understand legal data. Horace graduated with a Bachelor of Law as well as a Bachelor of Commerce (Finance) University of New South Wales, Australia (2004)


    David Len

    Trainer for:

        ● AI Governance
        ● Data Governance
        ● Soft Skills for Data & AI Project Management
        ● Strategic Data Asset Management
        ● Cybersecurity Governance, Risk and Compliance
        ● Strategic Intellectual Property Management

    David is a technology lawyer with more than 20 years of professional experience in the legal sector specializing in technology, data, privacy and cybersecurity. David is at present the Senior Legal Director for Technology Asia Pacific at DHL, the largest logistics multinational company in the world with 550,000 current employees worldwide. His core expertise includes (i) legal strategy & advice, (ii) contracts, and (iii) governance, risks management & compliance. David conducts internal compliance programs, training DHL employees across Asia-Pacific.

    Compliance programs include data protection, anti-bribery, anti-competition, conflict of interest and fraud. David graduated with a law degree in Australia and has a Master of Laws specializing in Information Technology & Telecommunications. He is admitted as an Advocate and Solicitor Malaysia and a Legal Practitioner New South Wales Australia.

    To further his knowledge, David has recently obtained, (i) Practitioner Certificate in Personal Data Protection (Singapore) from PDPC Singapore and IAPP (2021), (ii) Graduate Certificate in LegalTech from Singapore Management University (2020) and (iii) Certified Information Privacy Professional Europe (CIPP/E) from IAPP (2019). David is currently teaching part time at the International Compliance Association (ICA) on the Module “Leveraging Data for Business Advantage” where he teaches compliance professionals on data lifecycle, data strategy, data analytics and data visualization.


    Legal Practice Areas

    1. 1. Technology (Cloud, Software, Hardware, Consultancy, SLA, SOW)
    2. 2. Data Governance
    3. 3. Privacy (Data Protection)
    4. 4. Cybersecurity
    5. 5. Telecoms
    6. 6. IoT & AI
    7. 7. Blockchain & Smart Contracts


    Education, Professional Qualifications & Certifications

        2021 – Practitioner Certificate in Personal Data Protection (Singapore) – PDPC SG & IAPP
        2020 – Graduate Certificate in LegalTech – SMU, Singapore
        2019 - Certified Information Privacy Professional / Europe (GDPR) – IAPP
        2007 - Master of Laws (Information Technology & Telecommunications) – Strathclyde, UK
        1996 - Bachelor of Laws (Corporate & Commercial) – Bond, Australia
        2004 - Admitted as a Legal Practitioner, New South Wales, Australia
        1997 - Admitted as an Advocate and Solicitor, Malaysia
        2002 - Postgraduate Diploma in Accounting & Finance – ACCA


    Books Published, Accolades & Awards

        ● Co-Author, “Information Technology Contracts - Singapore Precedents & Forms”, Lexis Nexis (Sep 2005)
        ● ● Co-Author, “Information Technology Contracts - Malaysia Precedents & Forms”, Lexis Nexis (Sep 2005)
        ● Contributing Author, “Valuation of IP” – Media & Entertainment – A Practical Legal, Business & Strategy Guide by Zaid Hamzah, Sweet & Maxwell (Sept 2013)
        ● Contributing Author, “Valuation of IP” - Biomedical Science Law & Practice by Zaid Hamzah, Sweet & Maxwell (Dec 2007)
        ● Contributing Author, “Valuation of IP” - IP Law & Strategy by Zaid Hamzah, Sweet & Maxwell (Jun 2006)
        ● Contributing Author, “Bankers’ Confidentiality and Personal Data Protection - Malaysia’s Perspective” - Personal Data & Privacy Protection by Abdul Raman Saad, Lexis Nexis (Oct 2005)
        ● Contributing Author, “International Aspects of Computer Crimes” - E-Security Law & Strategy by Zaid Hamzah, Lexis Nexis (Apr 2005).
        ● Listed in Asialaw Profiles 2006 as “Notable Expertise” under the IT, Telecommunications and Media section for Malaysia
        ● Listed in IP Profiles 2006 as “Notable IP Practitioner” for Malaysia.
        ● Obtained a Japanese Government Scholarship for attending the “Expert Intellectual Property Course for Practitioner” in Tokyo, August 2001 (3 weeks).
        ● Part-Time Lecturer on “IT Security Laws, Investigation & Ethics” at the Centre for Advanced Software Engineering, Technology University of Malaysia (UTM), 2007/2008, 2008/2009 academic year.


    Michael Lew

    Trainer for:

        ● AI & Data Governance
        ● Cyberforensics
        ● Soft Skills for Data & AI Project Management
        ● Strategic Data Asset Management
        ● Cybersecurity Governance, Risk and Compliance
        ● Fintech Commercialization

    Michael has over 20 years of extensive consulting experience in technology risk management, cyber forensics, e-Discovery, data analytics, financial crime and in recent years, blockchain or cryptocurrencies investigations. He is regarded as a leading e-discovery expert in Asia and an avid digital forensics investigator who provides expert testimonies in both the courts of Singapore and Malaysia.

    Upon graduating from the London School of Economics (LSE) with a master’s in Information Systems, Michael started his career with a barrister’s chamber at Lincoln’s Inn, a leading law firm in Asia and was previously a Director at a Big4 advisory firm and had led their Southeast Asia Cyber Forensics team. He is currently the CEO at Rajah & Tann Technologies, a leading Legaltech advisory services provider in the Region and the Head of Cyber Forensics at Rajah & Tann Cybersecurity.

    In 2017, he founded AI-driven legaltech startup LegalComet, which was since acquired by Rajah & Tann Technologies. Following his interest in the use of AI and predictive data analytics, he had a stint with the National University of Singapore (NUS) as a researcher in the field of AI and blockchain and worked directly with distinguished professors and data scientists.

    Michael is currently the Chairman, Cyber Risk sub-committee of the Singapore Fintech Association (SFA), a founding board member of ASEAN Legaltech (ALT) and was the Past President of the High Technology Crime Investigation Association (HTCIA Singapore Chapter).


    Legal Technology Areas

    1. 1. Technology Risk Management
    2. 2. Information Governance
    3. 3. Data Analytics
    4. 4. Cybersecurity and Incident Response
    5. 5. Electronic Discovery
    6. 6. Cyber/Digital Forensics
    7. 7. Financial Crime Investigation
    8. 8. Blockchain and Artificial Intelligence


    Education, Professional Qualifications & Certifications

        2021 - Certified Cryptocurrency Investigator (CCI) - Blockchain Intelligence Group
        2013 - AccessData Certified Examiner (ACE) - AccessData
        2012 - EnCase Computer Forensics I & II - Guidance Software
        1999 - Master of Information Systems - London School of Economics, UK
        1998 - Bachelor of Business Administration (2nd Upper Class Hons) – Middlesex Uni, UK


    Books Published, Accolades & Awards

        Ranked among the top 30 people to watch in Asia in the Business of Law, Asia Law Portal (2021)
        Co-Author, “A Practical Guide to E-Discovery in Asia", LexisNexis (2017)

Contact

To contact us regarding our resources and course offerings, email Zaid Hamzah (Mr), our Founder and lead trainer at [email protected].

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