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Fraud Digital Transformation

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Fraud digital transformation (FDX) is crucial to fraud prevention programs. With tech accelerating progress, processes, controls, AI/ML, must be assessed and updated  frequently

FDX

What is FDX?

Fraud digital transformation is a holistic strategic change of the Fraud Program, to update its processes, technology infrastructure, data architecture, prevention controls, and detection-models technology with accordance to technology, AI and ML progress. 

Why FDX is crucial?

Fraud digital transformation is more important than ever:

  • Steep progress in AI/ML modeling capabilities and accessibility can reduce fraud

  • New data-architecture, storing and streaming increases detection models' performance 

  • FDX brings efficiencies to existing processes with quicker response to emerging threats   

  • FDX reduces risk by manual processes automation, improved reporting and monitoring

  • Build a holistic technology framework that reduces fraud operation costs 

Strategic FDX

The steps

Building a strategy for fraud digital transformation should include:

  • Alignment of Fraud Program requirements to the technology transformation

  • New technologies fit to specific fraud organization needs especially AI, cloud ,SaaS.

  • An internal gap analysis and a clear Fraud Program future state

  • Joint strategy with the Financial Crime Unit (FCU) and CX teams

  • Design an FDX implementation roadmap and rollout plan 

What should you do?

To increase the success and future effectiveness of your fraud digital transformation, you should:

  • Hold a fraud program assessment to map existing state and identify gaps

  • Have a fraud risk assessment to identify gaps in controls and process

  • Assess AI and data processes in detection and prevention cycles

  • Build a comprehensive technology roadmap to address all assessments

  • Work with stakeholders from Risk, Customer success, AML/Compliance     

Going beyond 

To be a head of the curve, you should go beyond standard FDX processes:

  • Invest the time in assessing and research (bring in experts)

  • Build an FDX framework that is flexible for changes and upgrades 

  • Design an AI modeling environment which is open and controlled by you

  • Leverage existing proven technologies but also incorporate emerging ones

Want to discuss FDX and hear how we can help? Lets talk!

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