Agenda

TIME AGENDA
Morning
09:00 – 12:30 WORKSHOP A: Applied Machine Learning And Deep Learning In Risk Management And Audit
 

This workshop will give you a comprehensive roadmap to using machine learning and deep learning to automate risk and fraud detection and enhance your accuracy of audit data. You will also learn how to use deep learning to train neural networks and solve problems with minimal supervision. By the end of the workshop, you will be able to demonstrate your knowledge in AI and develop unique applications that will immediately deliver benefits to your organization.

  Afternoon
 
13:30 – 16:45 WORKSHOP B: Utilizing Artificial Intelligence And Machine Learning To Detect Fraud, Suspicious Transactions And Anti Money Laundering
   This workshop will give you deep insights on applying supervised and unsupervised machine learning techniques in identifying patterns to detect fraud and suspicious transaction. You will also learn how to build a system for your organization that could better predict fraud and giving you upper hand to prevent it happen. With the enhanced Fraud Detection Predictive Models, you will be able to expand the efficiency and accuracy to operationalize anti-money laundering models by following a process that is user-centric.

 

TIME AGENDA
09:00 Welcoming Speech, Opening Remarks & Thank You Sponsor Speech by Conference Producer
 
09:05 Conference Introduction and Day 1 Highlights by Chairperson
 
09:15 Why Artificial Intelligence is a Game Changer in Risk Management, Audit, Fraud and Compliance
 
  • AI’s Bigger Ability in Handling and Evaluating Unstructured vs Structured Data
  • How Machine Learning Can Improve Risk Segmentation, Evaluation and Detection
  • Ability of AI to Use Advanced Algorithms to Analyze Text in order to Derive Insights and Social Media Sentiment from Unstructured Data
 
10:00 Developing Next Generation Risk and Fraud Management Systems with AI, Analytics and Unstructured Data
 
  • How to Embed Deep Learning in Your Organization’s Existing Technology Development Life-Cycle
  • Key Mechanism of Developing Your Machine Learning System Design – the Model, the Parameters and the Learner
  • Devising a Successful Machine Learning Strategy
 
  Morning Refreshments & Networking Session
 
11:00 Chief Risk Officers Panel: How AI, Machine Learning and Advanced Analytics Are Transforming Risk Modeling, Fraud and Claims
 
  • Impact of AI in Risk Modeling
  • Types of Structured and Unstructured Data Used in AI, Machine Learning and Advanced Analytics for Risk Modeling
  • Supervised vs Unsupervised Learning
  • How to Assess Effectiveness of the Model
  GORDON-SONG-rounded
GORDON SONG
SVP, Head of Group Risk & Internal Audit
Lazada Group
Lazada Group
 
 
11:45 Transforming Regulatory Compliance, Risk & Fraud Management and Governance Landscape with AI and Robotic Process Automation: OCBC Case Study
 
  • How  OCBC is Reducing the Number of Fraud Alerts
  • How OCBC Segment their Large Sets of “Noisy” Data and Alert Management for Better Risk Management
  • OCBC’s Integration of Blockchain, Smart Contracts and IoT in Detecting Risk of Legal Regulation Breach and Reduce Compliance Cost
 
12:30 Project Showcase
 
   Networking Luncheon
 
13:30 Mastercard Case Study: How MasterCard is Using AI to Improve the Accuracy of its Fraud Protection
 
  • How Mastercard Leverages on Real Time Approvals to Increase Its Accuracy of Genuine Transaction Detection and Reduce False Declines
  • How Mastercard’s Decision Intelligence Guarantee Fraud Reduction for Its Merchants
  • Challenges in Development and Education of Its Machine Learning Program
  • Benchmarking ROI from Mastercard’s Decision Intelligence Deployment
 
14:15 Deloitte Case Study: How Deloitte is Leveraging AI to Automate its Audit Processes
 
  • How AI is Used to Improve Quality and Efficiency of Audit for Deloitte
  • How AI is Used to Streamline Data Capture from Contracts by Identifying the Relevant Clauses for Accounting Treatment
  • How Deloitte is Connecting AI to Robotic Process Automation and Chatbots in order to Enhance the Quality of Audits
  SAM-CAMMISS-rounded
SAM CAMMISS
Innovation Director
Deloitte
Deloitte
 
  Afternoon Refreshments & Networking Session
 
15:15 NTUC Income Case Study: How NTUC Income is Utilizing Big Data, Predictive Analytics and Machine Learning to Improve Underwriting, Loss & Claims
 
  • How Big Data and Machine Learning Can Be Used to Improve Underwriting
  • How AI Can Improve Claims Processing and Help to Spot Fraud
  • Leveraging on Existing Data and Analytics to Generate Deeper Risk Insights
  • Automating Underwriting Processes
 
16:00 Live Demonstration: How AI Can Now Improve Claims in Less Than 60 Seconds
 
  • How AI Identify Complex or Severe Claims Instantly Through Rules-Based Processes
  • How AI Can Advise Adjusters with Best Action Plan in Reaction to Complex Claims
  • Generating Context of Predictions and Enhance Your AI Solutions Through Continuous Feedback
 
16:45 Chief Technology Officer Panel: Lessons Learnt From Artificial Intelligence Implementation
 
  • Reviewing Challenges and Lessons Learnt from Existing AI Projects
  • How Can We Accelerate AI Implementation in a Sustainable Manner?
 
17:30 Q&A Session & Closing Remark by Conference Chairperson
 
17:45 Champagne Networking Session
  champagne Networking

Enjoy a glass of champagne whilst networking with other like-minded individuals on topics that are of most interest to you and fellow delegates.

 

 

TIME AGENDA
09:00 Conference Introduction and Day 2 Highlights by Chairperson
 
09:10 Deep Learning and Fraud Detection: Real Examples of How Real Life Fraud Algorithms Works
 
  • Key Drivers for Danske Bank’s AI Deployment in Their Fraud Detection System and Setting a Benchmark to Other Enterprise
  • How Danske Bank Achieved a Low 40 Percent Fraud Detection Rate with Their Deep Learning and AI Deployment
  • How Deep Learning Improves Probability Predictions, Identify Higher Percentage of Fraud Cases and Reduce False Alarm
  VISHAL SINGHVI
APAC Ecommerce Payment & Risk Lead
Microsoft
Microsoft
09:55 Head of Artificial Intelligence Panel: Understanding the Limitations of Machine Learning in Risk Management, Detecting Fraud, Underwriting and Claims
 
  • What Are the Acceptable Failure Rate of an AI Fraud Detection?
  • Can AI Replace the Human Touch and Gain Trust on Client?
  • Why Is Westpac Holding off Their AI Deployment?
 
  Morning Refreshments & Networking Session
 
11:00 RegTech: How AI is Transforming Legal, Regulatory, Tax  and Compliance Landscape
 
  • Collaborating with RegTech in Redefining a Simpler Compliance with Financial Crime Controls, Efficient Adherence to Conduct Rules and Basel III Reporting Requirements
  • How RegTech Could Use AI to Help Enterprises Achieve Better Compliance and Regulatory Risk Detection, Assess Risk Exposure and Anticipate Future Threats
  • Applying AI to Facilitate Due Diligence and KYC Procedures
  • Counterparty AML and Anti-Fraud Screening & Detection Process
  KOH-CHIA-LING-rounded

KOH CHIA LING
Managing Director
Osborne Clarke
Osborne Clarke

11:45 Fireside Chat: Case studies of RegTech Deployment
 
  • How to Utilize Natural Language Processing (NLP) to Help Law and Tax Professionals to Research in Seconds
  • How AI Automates Its Legal Services to Assist Victims of Domestic Violence by Providing Legal Advice and Automate Risk Assessments and Documents
  • Discover How Ailira Could Replace Tax Agents in Future by Answering Your Complex Tax Questions on Superannuation, Capital Gain Tax and Other Tax Issues
  Matt-Pollins_CMS-roundedMATT POLLINS
Partner
CMS Singapore
CMS Singapore

  Networking Luncheon
 
13:30 AI Meets Anti-Money Laundering: How MAS And Singapore Financial Sectors’ Joint KYC Can Improve Money Laundering Detection
 
  • How to Build a Robust KYC Processes to Harness Organization’s Front Line of Defenses
  • Converting past Unstructured Data Collectively to Detect Laundering Patterns That Are Innocuous
 
14:15 Paypal AI Case Study: How Paypal is Boosting its Security with AI
 
  • How PayPal Is Using AI to Keep up with Threats and Reduce Its Fraud Rate to 24% Lower than Average Merchants
  • Leveraging AI’s Ability to Detect and Address Threats Before They Hit PayPal’s Site Operations
  • Real-Time Analysis of Customers’ Transactions to Detect and Mitigate Fraud and Theft
  • What Potential Capacity PayPal See in AI Security Application
 
  Afternoon Refreshments & Networking Session
 
15:20 AI Case Study Roundtable:
 
  • Sharing on Different Industries’ AI Deployment on Boosting Their Risk Management and Fraud Prevention Function
  • Achievements and Benefits That Are Derived from AI Deployment
  • Challenges and Implications
 
16:15 CTO Panel: How to Assemble the Right Infrastructure, Systems and People You Need to Build Your Next Generation Risk and Fraud Management System
 
  • What Infrastructure You Need
  • Challenges of Forming the Team: How to Attract Talent
  • Synergy or Conflict in the Team
  • Mixing the Old and New
 
17:00 Closing Remarks by Conference Chairman