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AI Archiving

02 May 2024 3 mins read
By Jennie Clarke

How to benefit from an AI archive

Here are four of the potential applications for Artificial Intelligence archives:

  1. Communication surveillance
  2. Behavioral analytics
  3. Sales analytics
  4. Customer support triage

Communication Surveillance

The first application for an archive powered by generative AI is for communication surveillance. In financial organizations, such as broker dealers, regulation requires the monitoring of all messages. This includes the likes of whatsapps, facebook messages and more ‘official’ channels, to prevent the likes of insider trading, and identify non-compliance.

AI-powered archives can perform this role successfully, especially due to their machine learning capabilities. For example, Global Relay’s AI archive model relies on a mix of natural language processing, text and computational linguistics. This enables the algorithm to automatically decide whether sentiment within communications is positive, neutral or negative. Teams can get even more specific on this with a numerical scale, highlighting extreme versus moderate sentiments.

Behavioral analytics

AI archives are also beneficial in helping companies to spot threats before they occur in the United States and beyond. By consistently capturing, monitoring and storing comms, analytics programs have access to an abundance of data. This amalgamation makes it easy to define “normal”, and for the AI technology to identify anomalies. 

One concern in this area is false positives: an erroneous result. In this example, it would be the identification of an extreme threat, where there is none. To avoid false positives in its results, Global Relay’s AI algorithm leverages pre-approved communications. Your team can pre-approve already accepted language (the most common cause of false positives), and identify matches in the archiving. This technique effectively filters the results to reduce false classification.

Sales analytics

Digital archives are not only effective in internal communications, but can also influence sales messaging. For example, AI archives can be applied to analyze the market, especially when examining direct competitors. By doing this, the algorithm can automatically spot strengths and weaknesses in messaging, and help businesses to test and develop their perfect formula.

This is particularly useful for regulated businesses. By using an AI archive, teams can identify specific business objectives and double down on these features within their messaging. And with guardrails on AI models, meeting regulatory requirements has never been so easy.

Customer support triage

Finally, an archival AI system can be useful in growing customer engagement, and reducing the number of disgruntled consumers. In particular, capturing customer sentiment and applying an automated algorithm enables teams to spot a dissatisfied customer before they complain. From there, it’s about proactively getting in touch to make things right. 

One of Global Relay’s AI strengths is that the algorithm can successfully identify the predominant language within any text from over 100+ possibilities. In a customer service setting, this can be incredibly beneficial in contacting a local translator before getting in touch, and ensuring the interaction can be as smooth as possible. 

By applying an AI solution to a customer support function, teams can benefit from a better reputation. Get in touch with a dedicated member of the Global Relay team to find out more

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Published 02 May 2024

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