How AI Can Spot Underground Banking Entities Lurking Under Traditional Banking
Featured Speakers :
Alex with over 12 years of experience in the financial crimes and analytics profession, Alex has gained an extensive knowledge of anti-fraud and anti-money laundering techniques and solutions. He has designed and led financial crimes projects and solution implementations across verticals including banking, insurance, and government. Alex currently works in the Financial Crimes and Cyber group in PwC Canada as a technology specialist, working with clients to find ways to leverage emerging technologies and analytics, including machine learning, to enhance their financial crimes programs.
With business development background, advanced analytic knowledge, and financial services experience in financial crimes, Kevin has supported engagements to rectify and enhance client’s financial crimes programs through systematic improvements. Kevin advises customers of the best practices to incorporate new analytics strategy and technology to align with the latest risk typologies to mitigate risk exposure. He has worked across functions of financial crimes program from financial crimes risk assessment, implementation of controls and technologies, to remediation. Before joining Deloitte, he has held multiple positions with IBM, SAS and BAE Systems focusing on applying AI and machine learning for financial crime.
Within IBM, Daniel builds industry specific solutions for the financial services
sector. A seasoned thought leader that aides in the demo, design, development and
delivery of offerings that apply next generation analytics and artificial intelligence
technologies used in evolving financial crime solutions for regulatory compliance and
fraud. As part of his mandate, Daniel monitors the financial crime industry and global
landscape while meeting with business and technology leaders from financial services
organizations across the globe to share best practices and help them identify how they
can apply analytics and artificial intelligence capabilities to drive new business value
while meeting compliance and revenue commitments.
Complimentary webinar, courtesy of IBM and ACFCS
The global pandemic wrought by COVID-19 has disrupted the status quo and modus operandi of major establishments. An unusual suspect – ‘underground banking’ – also finds itself at the receiving end of this health crisis.
Money service providers like the hawala, hub or fei ch’ien networks that facilitate remittance actions globally in the are forced to go digital as their practices are limited by enforcement of social distancing. They are starting to exploit the cracks in traditional banking’s age old AML controls hardened to prevent suspected acts of money laundering.
They are increasingly using mule accounts and other seemingly legit mechanisms in the traditional banking sector to continue offering services to their clientele. Artificial intelligence can help traditional banks identify behavioral markers of these underground bankers circumventing their AML controls and take effective actions.
Learning objectives :
- How underground banking responded to COVID-19 lockdown restrictions
- How operators of underground banking leverage seemingly legit mechanisms to thrive in digital environments
- Why traditional AML controls are not enough to deter money laundering
- How behavioral insights powered by AI technologies can uncover these crimes
This session is eligible for 1 CFCS credits.
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