Financial Crime World

Transforming Anti-Money Laundering (AML) Approaches with a Digital First Mindset

Banks can revolutionize their anti-money laundering (AML) and financial crime strategies by embracing a “digital first” approach. This involves leveraging technology to improve the customer experience, reduce backlogs in know-your-customer (KYC) and due diligence, and optimize value while mitigating risks.

Four Key Steps for Digital Transformation

1. Segment Customers More Finely

Developing a model that categorizes customers based on their risk profiles can help banks treat high-risk customers with the scrutiny they deserve, while providing a smoother experience for low-risk customers. This involves:

  • Creating a detailed customer segmentation model
  • Categorizing customers based on their risk profiles
  • Applying targeted due diligence and monitoring to high-risk customers

2. Deploy Self-Service Solutions

Self-service options can help reduce the burden of KYC and due diligence on less-risky customers, while automatically posing more questions to higher-risk customers. This involves:

  • Implementing digital self-service channels for low-risk customers
  • Using machine learning algorithms to identify high-risk customers
  • Providing tailored due diligence and monitoring for high-risk customers

3. Tailor and Track Remediation Efforts

This step involves tailoring remediation efforts at the individual customer level, providing a clear view of how remediation efforts are faring for operations, the board, and regulators. This includes:

  • Developing a comprehensive remediation plan
  • Tracking progress and outcomes
  • Adjusting strategies as needed to ensure effective remediation

4. Leverage Third-Party Data, External Providers, and Artificial Intelligence (AI)

Off-the-shelf solutions and data providers can help quickly stitch together an integrated solution, while AI can accelerate learnings from these outputs. This involves:

  • Integrating third-party data into your AML system
  • Using external providers for enhanced due diligence and monitoring
  • Leveraging AI to analyze large datasets and identify patterns

Enhancing Customer Segmentation with In-House Data

To develop a finer segmentation model, it’s essential to leverage in-house customer data supplemented with external data. For example:

  • Knowledge that a customer is a student can be used to understand “normal” wealth and banking activity for these customers
  • This information can enable banks to categorize students into a lower-risk category

Conclusion

By adopting a digital first approach and leveraging new technologies such as AI, self-service solutions, and third-party data, banks can transform their AML and financial crime strategies. By following the four key steps outlined above, banks can reduce backlogs in KYC and due diligence, improve the customer experience, and optimize value while mitigating risks.