How Does Natural Language Processing Monitor Compliance?
NLP is a subset of generative artificial intelligence that interprets human communication and, crucially, can convert that communication into data sets. NLP powers both the technology behind customer-facing tools such as chatbots and, more relevant to compliance, can quickly analyze a large amount of written or recorded communication.
For financial institutions, consider NLP an antidote to the plague of unstructured data. All those internal and client emails, employee social media posts, voicemail messages and call transcripts create mountains of unstructured data that needs to be formulated and organized to prove compliance.
Thankfully, NLP can do that and more.
Analyzing Internal Communications
All communication — whether with the public or inside the financial institution itself — is subject to analysis from regulators. Think about the number of emails or direct messages you receive in a given day, multiply that by the size of your staff, and you’ll get a sense of what’s being asked of compliance offices.
NLP can ingest all of that data far more quickly than a human could and identify any questionable behavior. NLP can even pick up on anomalous communication patterns, including the intentionally confusing language a fraudster may rely on to avoid detection. NLP can flag that communication and alert a human to dig a little deeper.
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Automating Review of Regulatory Documents and Contracts
A good editor is an invaluable resource, and allowing an NLP tool to look at the documents you produce before releasing them can accelerate and accentuate the work compliance checkers do.
Training the NLP tool, as with any type of generative AI, is an ongoing process; human backup is essential to catch things the tool may have missed and to spearhead that continued training. As the NLP does its work, adding in new words, phrases or other questionable communication that should be flagged allows it to continue learning and grow smarter.
Monitoring Client Interactions
External client contacts must also be monitored, and many of the same insights about internal communication apply here as well. Beyond language, NLP can also monitor for tone and more holistically look at the overall sentiment of an entire history of client conversations.
NLP can also help distinguish between information that should be shared with the client and that which needs to stay private. Transparency is an important aspect of compliance as well, and NLP can make sure employees are sharing what needs to be shared — and nothing more.
Tracking Public Sentiment and Market Commentary
Compliance for financial institutions extends beyond a company’s walls, virtual or otherwise. Social media behavior can raise red flags for compliance teams to further investigate, and tracking it can curb behavior that may be unknowingly creating regulatory or reputational risk for the company.
At the same time, NLP can also offer real-time feedback on market behaviors and customer feedback that could represent a business opportunity.
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