"People are increasingly excited about the transformative change potential that GenAI can bring to the entire industry," emphasized Chairman of Pieretti, General Director of Generative AI Solutions at Moody's, a US-based company specializing in credit ratings and financial information.
Financial services are one of the industries heavily affected by GenAI after OpenAI launched ChatGPT in November 2022. After initial confusion, companies have clearly understood what they can and cannot do with AI, after management agencies issued guidelines and expanded the use cases to take advantage of GenAI's capabilities to allow models to create a variety of content.
According to data from Statista Research Company, financial services firms have invested about $35 billion in AI, including GenAI, in 2023. They expect to spend $126.4 billion by 2028, which corresponds to a compound annual growth rate of 29%.
According to a January 2025 report by the World Economic Forum in collaboration with Accenture, financial services businesses, which are rich in data and language, have applied, invested and integrated AI faster than other fields.
While the current application of AI in financial services mainly focuses on promoting efficiency, business leaders have paid more attention to "revenue growth opportunities", from improving customer experience, making products and services more related to each other.
The real opportunity lies in automating the decision-making process. The most interesting thing is the ability to identify and act according to small signals in real time, allowing for smarter and faster decision making like portfolio management, said pieretti.
Moody has developed 35 AI-powered or digital colleagues that can generate comprehensive financial risk reports and other tasks faster than humans.
Moody's AI agents are provided with guidance, personality, and access to data and research. For example, one actor can analyze macroeconomic trends, while another actor assesses the specific risks of the company using exclusive financial data and a third actor assesses competitive position.
As a result, these 35 AI agents can draw different conclusions, especially for complex topics such as analyzing the financial situation of a seemingly healthy company but facing geopolitical risks, the company said.
