Internet Of Things (IoT) And Machine Learning: Roles And Applications

Innovation

08
Sep 2020

8 September 2020

8:30 am - 5:00 pm

Securities Commission Malaysia

MYR 950 *Fee is not inclusive of 6% SST

Internet-of-Things (IoT) is a network of devices connected through either wired or wireless devices to interact and exchange data. The purpose of communicating amongst devices is to provide consumers with smarter products and services, better customer experience, and higher competitive advantage to the business. McKinsey estimates that the IoT has a potential economic impact of $3.9 trillion to $11.1 trillion a year by 2025. At the top end, that would be equivalent to about 11 percent of the world economy. Gartner on the other hand predicted over 20 billion devices will be connected to IoT by 2020.

How is IoT relevant to the capital markets industry? Think of a large corporate firm that needs to hedge coffee prices (or wheat prices). The reason for the hedge is the price uncertainty at a future date. How much more effective might it be if the risk manager had real-time data from both meteorological stations across the world and probes embedded in the soil on a South American coffee plantage. Modern capital markets operate on extensive implementations of multiple electronic, digital, computational and connectivity technologies. This is entirely appropriate because capital markets generate huge volumes of data on a regular basis.

Consequently, participants such as commercial banks, central banks, insurance operators, and hedge funds are using cutting-edge technologies to process market data. Some participants have deployed Artificial Intelligence (AI) and Machine Learning (ML) technologies to automate trading processes. Others are leveraging custom-designed algorithms to create recommendations for clients to hold or trade in various asset classes. The use of such technologies is also empowering market participants to generate powerful insights into the workings of modern capital markets.

Programme Objective
The aim of this programme is to highlight the roles and applications of both IoT and ML that have created real economic value across many industry verticals. It will also give a sneak peek of the future and anticipated trends in the IoT applications and ML applications, technologies and analytics.

Learning Outcomes
Upon completing the programme, the participant should be able to:

  1. Identify the roles and applications of IoT and ML in the overall industry;
  2. recognise the impact of IoT and ML deployment in business processes;
  3. explain how applications are developed and used in IoT devices;
  4. describe how IoT and machine learning could be leveraged to solve business challenges;
  5. describe how business structure and processes could capitalise on IoT and ML advancements; and
  6. discuss how AI and ML advancements influence the new way of work.

Methodology

Interactive presentations, guided discussions and Question-and-Answer (Q&A) session

Competencies

Functional (Technical) – Digital Technology Application (Level 3)
Foundational (Product) – Capital Market Environment (Level 3)
Behavioural (Self-Management) – Creativity and Innovativeness (Level 3)

Target Audience

Individual 

Directors, C Suite leaders, Key Management, Business owners, Anyone who has an interest in servant leadership

Institutions 

Public Listed Companies (PLCs), Legal Firms, Consultancy Firms, Accounting Firms, Fund Management Companies, Stockbroking Firms, Investment Banks, SMEs

8.30 am Registration
9.00 am Introduction of the Internet of Things (IoT)

  • Underlying technology; enabling technologies for IoT
    • Wireless vs. Wired
    • Technical Standards
  • Trends and Characteristics
    • Intelligence –  IoT devices, Edge/Fog nodes, and cloud computing
    • Architecture –  Tier 1: Devices, Tier 2: The Edge gateway, and Tier 3: The cloud
  • IoT Business Innovation Model
    • Machine-as-a-Service (MaaS) model
    • Blades and razors
    • Value-based Pricing
10.30 am Coffee Break
11.00 am Emerging Applications Using IoT Devices

  • Consumer applications
  • Commercial application
  • Industrial applications
  • Infrastructure applications

Application of Machine Learning in Capital Market

  • Creating the foundations for Robo advisors
  • Intelligence everywhere; cognitive capabilities with automation technologies
  • Fraud detection; cost-saving and boosting brand value for financial institutions
  • Market Prediction; Usage of ML applications and technologies rigorous market research on stock prices and movements

 

Intervention 1: Action learning: Building IoT application in capital market

12.30 pm Lunch Break
2.00 pm Application of Machine Learning in Capital Market (continued)

Analytics & Algorithms:

o   Multidimensional ML analytics driven toolsets

o   Trade surveillance

o   Algorithmic trading platforms using big data

 

Intervention 2: Action learning: Building ML applications in capital market

3.00 pm Coffee Break
3.30 pm IoT in 2020

·       Smart home to smart office IoT

·       Growing IoT applications in healthcare industry

·       The marriage of AI and IoT

·       Voice activation takes Off

ML Trends in 2020:

·       Data lakes and SaaS for business analytics

·       How accurate is Machine Learning algorithms

·       Machine Learning and predictive analytics

·       The future of work

5.00 pm End of Programme

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