Machine learning and artificial intelligence (AI) have carved out a niche in regulatory compliance because their applications address common systematic issues and challenges that many businesses face on a daily basis. But, more importantly, it accomplishes this in the most effective and efficient manner possible.
AI-enabled enterprise solutions, such as SaaS insurance software, can significantly improve efficacy and efficiency. Some are even able to do so while adhering to industry regulations. While the sky is the limit with artificial intelligence and machine learning’s technological breakthroughs, many of their current applications in compliance systems have demonstrated three benefits: fewer false positives, fewer errors, and lower costs.
1. Reducing the number of false positives
Many financial service providers have been experiencing alarmingly high rates of false positives in their compliance systems. Regrettably, compliance alert systems based on current, standard technologies have been triggering thousands of false positives every day. Because each alarm must be carefully reviewed, it opens the door to more human error and inefficiency. Fortunately, thanks to machine learning and artificial intelligence, this is no longer the case.
Machine learning and artificial intelligence can capture, analyze, and filter large amounts of data, as well as deal with false positives that waste money and time for providers. For example, they can significantly improve workflow by automatically categorizing any compliance-related activity and ensuring that the appropriate people are notified of any important updates, activities, or events. In other words, they can make compliance alert systems more efficient.
2. Cost-cutting
Many modern financial service providers are being forced to make changes and adjustments in order to comply with regulatory compliance requirements centered on data analysis and management. As a result, RegTech developers have begun to employ artificial intelligence to boost efficiency while lowering compliance costs by automating processes that would otherwise necessitate time-consuming manual labor.
Artificial intelligence, when combined with machine learning, can automate the workflow. As a result, your compliance operations will require less human capital and time. When used in conjunction with the accuracy gains made possible by the integration of both technologies, you can save a significant amount of money in annual compliance costs.
3. Addresses the issue of human error
Human error can cost regulated industries a lot of money every year, whether it’s due to a lack of due diligence, ineffective processes, or outdated technology. Financial regulations enacted in the aftermath of the global financial crisis, for example, mandate the tracking, management, and analysis of detailed data on transactions, operational activities, and customers in financial institutions. The massive amount of information available can create numerous opportunities for costly human error.
ML and AI, similar to the use of calculators over manual computation, have the potential to shed light on areas that would otherwise go unnoticed. They can also spot patterns and trends to make it easier to communicate with their customer base.
Conclusion
No one can deny that regulatory compliance poses a number of difficulties. While there is no such thing as a one-size-fits-all solution, artificial intelligence and machine learning can go a long way toward improving compliance systems.
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