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.
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 20101. The benefits of integration include:
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:
To explore further how TaskUs can help FinTech companies in their data labeling needs, download our AI Services FinTech two-pager.