Webinar

Tackling the new frontier of fraud with machine learning

Financial criminals have become increasingly sophisticated when it comes to exploiting vulnerable consumers.

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In the United States, fraudulent stimulus payments are spurring major banks to shut down legitimate bank accounts due to suspected unemployment fraud. Furthermore, bad actors are deploying tactics such as call centre scams, account takeovers and micro deposit fraud to extract funds from both crypto and traditional currencies.

Financial service providers are responsible for protecting customers from large-scale fraud attacks. Unfortunately, not all have demonstrated the ability to operate on the same level of sophistication as the agile fraudsters, ultimately putting their brand reputation and penalties on the line.

Banks are also competing with new players in financial services that are tech-forward, exhibit high growth potential and offer sophisticated, tailor-made products and services.

Therefore, traditional banks must keep pace, by leveraging advanced technology powered by machine learning, to accurately identify customer behavioural trends, preventing fraud or criminal activity at the outset.

Machine learning platforms have the advantage of being able to analyse tens of thousands of complex signals. Financial service providers can then utilise behavioural pattern recognition to effectively understand and enforce on malicious activity, rather than relying on antiquated threshold rules that bad actors eventually learn to circumvent.

The ability to instantly understand and learn from the behavioural dynamics of a customer base is of paramount importance and will ultimately distinguish the successful players in the saturated but lucrative financial services industry.

Sign up for this Finextra webinar, in association with Sift, to join the panel of industry experts as they discuss the following areas:

  • Fraud, financial crime, and the state of play in 2021
  • What type of institution is ultimately responsible for customer protection?
  • The agility and growth potential of neobanks and challenger banks
  • Personalisation of services and the prevention of criminal activity
  • Machine learning and behavioural pattern recognition

Speakers:

  • Scott Hamilton - Global Payments & Liquidity Expert, Contributing Editor [Moderator]
  • Jane Lee - Trust and Safety Architect, Sift
  • Prag Sharma - Global Head, Artificial Intelligence Centre of Excellence (AI CoE), Citi Group
  • Chris Merz - Vice President, Security and Decision Products, Mastercard

Speakers

  • Scott Hamilton

    Scott Hamilton

    Global Payments & Liquidity Expert,
    Contributing Editor
    [Moderator]

  • Jane Lee

    Jane Lee

    Trust and Safety Architect
    Sift

  • Prag Sharma

    Prag Sharma

    Global Head,
    Artificial Intelligence Centre of Excellence (AI CoE),
    Citi Group

  • Chris Merz

    Chris Merz

    Vice President
    Security and Decision Products
    Mastercard

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