Financial Services

Fraud Detection and Content Management Efficiencies with AI

fraud detection

My last blog looked at call center optimization and how artificial intelligence (AI) provides an in-depth look into financial advice. In this blog, I analyze fraud detection and content management methods, with the assistance of AI.

Fraud Detection

In the online and digital world of financial services, fraud has increased and become harder to detect. However, the efficiencies available through ML enables hundreds of thousands of accounts to be monitored for fraudulent activity. There are many changes to an account that can appear to be normal activity, but when it’s combined with other activity, it can indicate fraud.

Financial Services - It's Time to Focus on Post-Digital Transformation in Banking
It's Time to Focus on Post-Digital Transformation in Banking

Digital transformation challenges in banking have been well understood and the strategies to address them simple and clear. However, it is becoming increasingly apparent that the industry is reaching a tipping point in the digital transformation journey.

Get the Guide

Examples of suspicious activity could include:

  • Changing the way a client interacts with their account (e.g., a client who always speaks to a representative starts to conduct all their business through a mobile app)
  • A change of address followed very quickly by a distribution request
  • Money going into the account while money is being paid out

While all of these may be completely innocent, ML can be used to identify potential fraudulent activity and alert the service provider to investigate.

Content Management Efficiencies

While most industries have moved to a near-paper-free environment, financial services – and more specifically retirement services – have continued to be plagued by the need to receive and process paper-based transactions in very large volumes. Machine learning can be employed in many ways to facilitate and expedite the processing of paper-based interactions.

  • Transactions received on paper can automatically be scanned and – using ML and rules-based engines – checked for completeness
  • If any data is incomplete, incorrect, or missing, the transaction can either be rejected with an automatic notification being generated for the client or routed to a specialist who can follow up and ensure the form meets standards
  • Resources in a call center can be identified as being a specialist in transactions to ensure resolutions are efficient and processed timely
  • Forms received in a completed format can be transformed into digital transactions and automatically queued to be run
  • Forms can be validated for suspicious flags, and even though there may be nothing missing or incorrect on the form, these transactions can be forwarded to specialists to review before allowing the transaction to process

To learn more about the opportunities to transform retirement services with artificial intelligence, you can click here, or download the guide below.

About the Author

Retirement Services Lead, Financial Services, Perficient Andrew Bihl, retirement services lead in Perficient’s financial services practice, joined the company in 2013 via the acquisition of ForwardThink Group. His areas of focus include program management offices, business process redesigns, and operational design. Andrew has over 20 years of experience in corporate and consulting roles. He has successfully delivered projects in the retirement services practice for diverse clients, such as Fidelity, Prudential, and TIAA.

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