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Foundation in Big Data Analytics for the Banking Sector
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Foundation in Big Data Analytics for the Banking Sector
  • Overview
  • Objectives & Outline
  • Methodology
  • Participant Profile
  • Trainer
  • Overview
    PROGRAMME DETAILS

    Duration

    1 day

    TIME

    9:00 AM – 5:00 PM

    VENUE

    Asian Banking School
    8
    AICB
    CPD HOURS
    With the proliferation of data analytics initiatives by various governments, businesses and social media platforms, it becomes paramount to understand the fundamentals of Big Data Analytics and its applications to the banking sector. Big Data is not just about extracting and storing data but consists of many technologies and processes working hand-in-hand to derive useful information and actionable insights from huge volumes of data. As data is being created, collected and stored faster than ever, it is important for bankers to have a foundational understanding of such technologies, including use cases that can be applied to benefit the banking sector.
    LEARNING LEVEL
    Foundation
    PROGRAMME FEE

    AICB MEMBER

    MYR

    1,100*

    / PAX

    NON-MEMBER

    MYR

    1,400*

    / PAX

    *Subject to 6% Service Tax

  • Objectives & Outline
    LEARNING OBJECTIVES
    By the end of this programme, participants will be able to gain a deeper knowledge and understanding of Big Data through various modules:

    • Overview of Big Data
    • Big Data in Banks: Use Cases
    • Introduction to Tools and Technologies
    • Big Data Maturity in the banking sector and how to get started

    PROGRAMME OUTLINE
    Module 1: Overview of Big Data
    • Definition of Big Data
    • Differences with existing approaches: Data Warehouse, Data Mining and predictive analytics
    • Variety of data: internal, external, structured and unstructured
    • Dealing with data veracity: when to use Big Data

    Module 2: Big Data in Banks: Use Cases
    • Increase in Revenue / Customer Driven:
      • Single customer view
      • Micro-segmentation
      • Targeted marketing
      • Voice of customer
    • Minimise Risk
      • Know Your Customer (KYC)
      • Transaction fault detection
      • Anti-money laundering / counter terrorism financing
      • Early warning of risk 

    Module 3: Big Data and Fast Data Technologies
    • Differences between big data and fast data
    • Introduction to tools and technologies
      • Hadoop
      • Hive
      • Spark
      • NoSQL (MongoDB)
      • StreamSets
      • R and Python
    •  Open-source versus proprietary solutions

    Module 4: Big Data Maturity in the Banking Sector and How to Get Started
    • Assess internal capabilities
    • Form Center of Excellence (CoE)
    • Determine use cases for pilot
    • Data acquisition
    • “Land-and-Expand” approach: build on a series of quick-wins
    • How to contribute if you are not IT

  • Methodology

    Combination of classroom learning, case studies, group discussions and presentations

  • Participant Profile
    Banking professionals up to mid-level managers
  • Trainer

    Kew Yoke Ling

    Yoke Ling is the Founder and Executive Director of KewMann Sdn. Bhd., a Big Data analytics and behavioural science company headquartered in Singapore, with offices in Malaysia and Hong Kong. Yoke Ling has more than 18 years’ experience working with the financial services sector and government organisations to provide innovative solutions.
    He has assisted multiple clients with their digital transformation needs, from the on-premise era to cloud or mobile applications, from data mining to artificial intelligence. Notable clients include ICBC (Asia), Mastercard Asia Pacific, NTUC Income, Lembaga Hasil Dalam Negeri Malaysia (LHDN) and CyberSecurity Malaysia (CSM). Before founding KewMann, Yoke Ling held management positions in CallidusCloud (Asia Pacific), and was with Oracle for more than 8 years. Yoke Ling has a BSc (Hons) in Computing, and a post-graduate diploma from the Chartered Institute of Marketing (CIM).

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