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The Role of Large Language Models in Revolutionizing Banking Operations

EasyChair Preprint no. 13248

19 pagesDate: May 12, 2024


Large language models have emerged as powerful tools in revolutionizing banking operations. These sophisticated models, such as GPT-3 and GPT-4, can process and generate human-like language, enabling them to automate various tasks in the banking sector. This abstract explores the transformative role of large language models in banking operations.


Firstly, large language models have significantly automated customer service in banks. Chatbots and virtual assistants equipped with natural language processing capabilities efficiently handle customer inquiries, reducing response times and enhancing customer satisfaction. Routine customer requests, such as balance inquiries and transaction history, can be seamlessly addressed, freeing up human agents to focus on more complex issues.


Moreover, these models play a crucial role in risk assessment and fraud detection. By analyzing vast volumes of financial data, large language models can identify suspicious patterns and anomalies, enabling real-time monitoring and prevention of fraudulent activities. This enhances the security and integrity of banking operations, safeguarding both customers and financial institutions.

Keyphrases: Automation, Documentation, Natural Language Generation, Personalization, reports, structured data

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Ayuns Luz and Harold Jonathan},
  title = {The Role of Large Language Models in Revolutionizing Banking Operations},
  howpublished = {EasyChair Preprint no. 13248},

  year = {EasyChair, 2024}}
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