Data Labeling for the FinTech Industry: Streamlining Fraud Detection & Compliance

Over the last few years, financial institutions turned to automation and Machine Learning to enhance customer experience and improve the efficiency of their fraud detection processes. However, as fintech companies grow their digital ecosystem, attacks and fraudulent activities are also growing more sophisticated.

Today, simply detecting and preventing fraud is not enough. A more holistic approach is needed to remove the lack of visibility across the financial crime life cycle. This approach involves the convergence of fraud detection and compliance. 

Typically, FinTech companies view fraud and money laundering as two separate cases involving different departments, but criminals do not see it the same way. They take advantage of this siloed approach, making it easier to manipulate financial accounts and commit more complex financial crimes.

Taking a holistic approach to suspicious customer behavior across all service lines results in a more effective investigation process and removes the loopholes bad actors could take advantage of. 

The Benefits of AI/ML Convergence in Fraud Detection and Compliance

According to a survey conducted by the Association of Certified Anti-Money Laundering Specialists and Ernst & Young,  52 percent of financial institutions had already integrated some aspects of fraud detection and compliance as early as 2010. (1). The benefits of integration include:

  • Increase in Investigation Speed and Efficiency
    The integration allows AI systems to immediately notify analysts, increasing the speed of the investigation process.
  • Improved Fraud Prevention and Detection Rates
    Enables the capture of low-value events that are not previously recorded as fraud.
  • Low Duplicate Alerts
    Prevents duplicate alerts that result in the investigation of common subjects. 
  • Improved Reporting
    Allows faster generation of reports, including risk exposures, filings, losses, and operational metrics.

How can TaskUs help?

Integrating compliance and fraud detection can be a daunting task for most financial institutions, especially if they do not have the proper set of training data. ​​TaskUs is your partner in building better-performing Machine Learning models.

With our deep expertise in the financial industry, we can help you structure historical data with meaningful labels to uncover trends in fraud detection. We also recruit, train, and manage remote evaluators to review alerts of potential misconduct.

Other key data labeling services include:

  • Document Analysis via Transcription / Text Annotation
  • Virtual Assistants and chatbots using Intent Detection / Text Collection

To explore further how TaskUs can help FinTech companies in their data labeling needs, download our AI Services FinTech two-pager.

Reference:

  1. Financial Crimes Convergence—The Case for Integrating Fraud and Anti-Money Laundering Processes

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