Fintech customers asking questions like those to AI-powered product explanation interfaces or chatbots before signing up for a product or service, and inquiring about safety, prices and licenses. AURALIS analyzes all answers to uncover corresponding trust gaps which might be keeping potential customers from becoming paying customers.
In AURALIS you can see the actual language that was generated by ChatGPT when it responded to a buyer's inquiry as to whether a specific bank is "safe" and also see the sources cited by ChatGPT and then alter the language as needed to best suit your purposes. As an example, the response generated by ChatGPT included information as to the bank's compliance, information regarding its deposit insurance and the positive or negative sentiment expressed by financial analysts regarding the bank. In order for a bank to win the business of a buyer, it typically receives the most favorable response to this inquiry from the buyer.
Daily prompt sweeps for Trust, Safety, Fees and Features related questions. Citation tracking of Trust badges found on websites of Government regulatory bodies, Analyst reports and Consumer review sites. Sentiment analysis of all found compliance text with weighting applied where necessary. Competitor analysis for all conversion critical questions.