Enhancing Detection of Fraud & Money Laundering Using AI

Overview

Financial crimes like fraud and money laundering have evolved rapidly in complexity and sophistication. The cost of compliance has also risen sharply with more stringent regulatory controls. Hefty fines, erosion to reputation and trust are prompting financial institutions to turned to data analytics for more effective measures to detect suspicious activities from a wider variety of data sources, structured and unstructured. However, the high false positive rates bring no respite to the workload and continue to strain resources.

Today, artificial intelligence (AI) and machine learning (ML) can be used to complement data analytics. AI/ML can be incorporated into the financial crime compliance (FCC) model reviews to reduce the number of false positives by enabling smarter analytics, so that investigations can focus on genuine money laundering cases.

This one-day workshop looks at how to design an operational framework, incorporating the latest MAS paper on Guidance for Effective AML/CFT Transaction Monitoring Controls.

Next Course Starts On26 Feb 2019 (Tue) See Full Schedule
Fee SGD856.00* (as low as SGD96.80* after maximum funding) Learn more
Duration

1 day 

Level
Basic
Venue

Singapore Management University

Learning Objectives
  • Understand how artificial intelligence & machine learning work
  • Know how AL/ML can be used to detect financial crime
  • Learn to combine data analytics with AL/ML via smarter behavioural analytics to reduce false positives
  • Contextualize the event to improve outcome
  • Design an operational framework to improve effectiveness

Topics/Structure

  • Introduction to artificial intelligence (AI) and machine learning (ML)
  • Application of AL/ML in financial crime detection
  • Enhancement of analytics using AL/ML
  • Contextualizing the event 
  • Designing an operational framework to improve effectiveness 

Who Should Attend

  • Professionals in compliance, audit, risk management
  • Business function managers responsible for operational risk management
  • IT professionals and data scientists

Assessment

Upon meeting the attendance requirement and passing the assessment, participants will receive a Certificate of Completion.

Fees and Funding

Full Fee: S$856 per pax (incl GST)

Nett Fee payable after SkillsFuture Singapore (SSG) Funding:

  • S$256.80 (incl GST) for Singapore Citizens and Singapore Permanent Residents
  • S$96.80 (incl GST) for Singapore Citizens aged 40 years and above
  • S$96.80 (incl GST) for Singapore Citizens and Singapore Permanent Residents on Enhanced Training Support for SMEs (ETSS)
  • S$56.80 (incl GST) for Singaporeans on Workfare Training Support (WTS)

 

All self-sponsored Singaporeans aged 25 and above can use their $500 SkillsFuture Credit to pay for the programme. Visit the SkillsFuture Credit website (www.skillsfuture.sg/credit) to select the programme.

Mid-Career Enhanced Subsidy - Singaporeans aged 40 and above may enjoy subsidies up to 90% of the programme fee

Workfare Training Support (WTS) - Singaporeans aged 35 and above (13 years and above for persons With disabilities) and earn not more than S$2,000 per month, may enjoy subsidies up to 95% of the programme fee.

Enhanced Training Support for SMEs (ETSS) - SME-sponsored employees (Singaporean Citizens and PRs) may enjoy subsidies up to 90% of the programme fee. For more information, visit www.ssg.gov.sg/programmes-and-initiatives/training/enhanced-training-support-for-smes.html.

Eligible organisations (excluding government entities) may apply for the absentee payroll funding via SkillsConnect at www.skillsconnect.gov.sg for Singaporean/permanent resident participants attending the programme during working hours. The absentee payroll funding is computed at 80% of hourly basic salary capped at $4.50 per hour or $7.50 per hour for SME or 95% of hourly basic salary for WTS. For more information, visit https://www.skillsconnect.gov.sg/sop/portal/e-Services/For%20Employers/AbsenteePayroll.jsp

Schedule

Start Date(s)
Intake Information

26 Feb 2019 (Tue)

Program is held from  9am - 5pm

Speaker/Trainer Bio

Dr Khoo Guan Seng has over 28 years’ of experience in the design and implementation of enterprise wide risk management models, systems and processes. He gained deep practical insights from a career spanning across financial institutions in the US, Canada, UK and Singapore, including Man Group, American Bourses Corporation, ATOS Origin, RHB Capital, Singapore Exchange, Standard Chartered Bank, Temasek Holdings and Alberta Investment Management Corporation.

Dr Koh holds a PhD in Physics (Material Science) from the National University of Singapore. Prior to joining the private sector in 2000, Dr Khoo held academic positions with the Nanyang Technological University (NTU) where he co-developed the first post-graduate financial engineering programme and taught risk management for the NTU MBA programme. He speaks regularly at international banking conferences and published articles relating to enterprise risk management and sovereign investing. 

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