Five GPT-3 Use Cases for Banks and Fintechs

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If you’re not familiar with OpenAI’s newest technology, ChatGPT, now is the time to spend a few minutes to sign up and play with the chatbot that has captured the world’s attention. ChatGPT leverages Generative Pre-trained Transformer 3 (GPT-3), OpenAI’s language generation model, and it is poised to disrupt a lot more than the customer service.

While ChatGPT has a multitude of use cases in the fintech industry– from automating copywriting to crafting a job description– GPT-3 is even more powerful. Accessed through OpenAI’s API, it can be tailored to suit a range of natural language processing tasks and runs on 175 billion parameters. ChatGPT has only 20 billion parameters. More importantly, firms can use GPT-3 via an API in a compliant environment.

The applications for GPT-3 across fintech and banking are seemingly endless, but I’ve outlined a handful of ways banks and fintechs can use the technology without requiring additional resources to save costs and create a better user experience.

Automate customer service interactions

Banks and fintechs can integrate GPT-3 into a chatbot or virtual assistant to lessen the volume of phone inquiries into their customer service department. GPT-3 can handle common customer inquiries, such as account balance inquiries or loan application status updates.

Enhance fraud detection

Organizations can use historical transaction data to train GPT-3 to identify patterns and flag anomalies that may indicate fraudulent activity.

Streamline document processing

GPT-3 can prove useful to firms that process a large number of documents and need to extract specific information from the paperwork. The technology can automatically extract information from financial documents, such as invoices or loan applications, which ultimately saves time by reducing manual data entry.

Create more personalized financial advice

Advisors can use GPT-3 to generate financial advice, such as investment recommendations, for their clients. In order to tailor the advice to the individual, GPT-3 will take into account customer demographics, risk tolerance, and investment goals.

Create sentiment analysis

From a marketing perspective, GPT-3 can be used to determine brand awareness and overall sentiment toward a company or brand. By analyzing customer feedback and social media interactions, companies can gain insight on new product deployments and measure customer satisfaction over time.

While many of these tools and capabilities have been available in the fintech and banking industry for over a decade, they are now even more powerful. What’s more, using GPT-3 may be more cost effective in the long run because of the range of use cases the technology presents.


Photo by Miguel Á. Padriñán

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