Network Analytics: How to Uncover Financial Crime Risk

When:

On-Demand

Where:

Online

Network Analytics: How to Uncover Financial Crime Risk

Watch this webinar on the importance of network analytics with financial crime and compliance organisations, and best practices for deploying this technology.

  • How can firms enhance their financial crime detection and investigative capabilities?
  • What can banks do to gain a comprehensive understanding of the application of network analytics in the context of financial crime and compliance?
  • How can data visualisation techniques be leveraged for better understanding of complex financial networks?
  • Can network analytics be integrated into financial institutions’ current risk management and compliance frameworks?

Money laundering, fraud, and regulatory compliance are increasing challenges for institutions in the financial services industry. However, new developments in technology and data science are presenting unique solutions. Monitoring, detection, investigation, and reporting of these risks are of paramount importance to any organisation across financial services, but these processes have historically not been the most efficient.

While Know Your Customer (KYC) regulations have been implemented, and suspicious activity can be reported by filing a Suspicious Activity Report (SAR) to FinCEN in the US, network analytics needs to be leveraged to uncover hidden risk. Inefficient mitigation of financial crime can result in uncertainty, fines, and in turn, reputational harm, so network analytics – the process where network data is collected and analysed to improve the performance, reliability, visibility, or security of the network – can be hugely advantageous.

By applying network analytics, financial institutions can identify patterns, reveal hidden connections, and uncover suspicious behaviour. Further to this, network visualisation can bring clarity to complex relationships and provide more efficient ways to trace the flow of funds. Transparency across workflows and audit trails can also help improve controls, but inefficiencies around data persist. Incorporating machine learning tools into a network can further help teams predict traffic flows, generate smarter analytics, monitor network health, and tighten security measures.

Sign up for this Finextra webinar, hosted in association with NICE Actimize, to join our panel of industry experts who will discuss how to enhance financial crime detection and investigative capabilities.

 

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