Why NLP needs human-in-the-loop

Why NLP need human-in-the-loop

While natural language processing (NLP) solutions are helping financial services extract valuable insights from unstructured data, Aveni warns there is the need for human-in-the-loop (HITL).

The RegTech company stated that while the algorithms are advanced, they cannot match the intuition and creativity of the human brain.

To help explain the need of HITL, Aveni likened an NLP solution to a car driving on a long journey. While the car has advanced features to make the trip smoother, such as automatic navigation and cruise control, the human driver is needed to make critical decisions and react to unexpected situations. For example, the car might get lost, encounter obstacles or even crash.

It said, “In the same way, NLP solutions need human input to guide and adjust the automated processes, ensure accuracy, and prevent errors or biases.”

HITL will provide essential insights and expertise to ensure the NLP processes are successful and avoid mistakes.

It added that by integrating human expertise with NLP, financial services can improve the accuracy and relevance of their insights. This is because humans can interpret complex linguistic nuances that algorithms struggle with, as well as identify context and entities in the text that machines could miss, it said.

However, HITL doesn’t only improve the quality of the insights, but can also help NLP solutions evolve and learn from their mistakes. By working together, they can identify areas for improvement and how to adapt the technique to be better.

Aveni concluded, “In a nutshell, by integrating human-in-the-loop, financial services firms can achieve more accurate and relevant insights, and improve the NLP solution’s performance over time. Thanks to this continuous improvement, the earlier you implement, the better your solution will be compared to a competitor’s.”

Read the full story here.

Aveni recently launched the Aveni Detect service on the Genesys AppFoundry marketplace. Aveni Detect platform analyses all customer interactions and mitigates against a range of risks from conduct and complaints to customer vulnerability.

Keep up with all the latest FinTech news here.

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