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AI’s Applications in Digital Finance

Aug 28-2024   



 

At the 2024 Academic Conference on Digital Economy Development and Governance, Prof. Shen Yan of the NSD delivered a keynote speech on AI’s applications in digital finance. She is also Deputy Director of PKU Institute of Digital Finance.

 

Digital finance has been the most important innovation in the financial system over the last ten plus years, she said. Its development and changes can be understood from three dimensions: institutions and their activities, digital technologies, and business models. As for innovations in digital finance, AI plays a significant role in improving financial services through scenarios, data, algorithm, and computing power.

 

Four areas exemplify AI’s applications in digital finance, according to Prof. Shen. Smart customer services can solve multiple problems for financial institutions, such as mismatch between working hours and customer inquiries, poor customer experience, and high staff turnover rate. She cited the example of a financial group whose smart services handled 86% of its annual total of one billion times of inquiry and successfully tackled 92.3%. The newly generated conversational transcripts were then tapped to promote smart sale to potential customers, leading to close to 200 billion yuan in revenue in 2021.

 

Another area is digital credit, which enhances financial inclusiveness and particularly benefits micro-, small-, and medium-sized companies. AI can not only make it easier for banks to acquire customers by obtaining big data on platforms, but also develop new risk control models by combining big data with machine learning. In addition, platforms can obtain customers’ behavior and transaction information at low costs, which is conducive to improving loan management and preventing moral hazard.

 

The third area concerns quantitative investment. Prof. Shen drew attention to a study by the University of Chicago, which found that ChatGPT4 outperformed the majority of human stock analysts, offering higher Alpha and Sharpe Ratio. The fourth note-worthy sphere is smart investment advisory, which holds the promise of providing good wealth management services to the middle class and even the wider public. Some financial institutions have undertaken trials in this regard, though not without challenges.

 

For AI to be more productive in digital finance, Prof. Shen said that some crucial issues must be addressed, including the constraints of algorithm, the limitations of data, and computing security.

AI’s Applications in Digital Finance

Aug 28-2024   



 

At the 2024 Academic Conference on Digital Economy Development and Governance, Prof. Shen Yan of the NSD delivered a keynote speech on AI’s applications in digital finance. She is also Deputy Director of PKU Institute of Digital Finance.

 

Digital finance has been the most important innovation in the financial system over the last ten plus years, she said. Its development and changes can be understood from three dimensions: institutions and their activities, digital technologies, and business models. As for innovations in digital finance, AI plays a significant role in improving financial services through scenarios, data, algorithm, and computing power.

 

Four areas exemplify AI’s applications in digital finance, according to Prof. Shen. Smart customer services can solve multiple problems for financial institutions, such as mismatch between working hours and customer inquiries, poor customer experience, and high staff turnover rate. She cited the example of a financial group whose smart services handled 86% of its annual total of one billion times of inquiry and successfully tackled 92.3%. The newly generated conversational transcripts were then tapped to promote smart sale to potential customers, leading to close to 200 billion yuan in revenue in 2021.

 

Another area is digital credit, which enhances financial inclusiveness and particularly benefits micro-, small-, and medium-sized companies. AI can not only make it easier for banks to acquire customers by obtaining big data on platforms, but also develop new risk control models by combining big data with machine learning. In addition, platforms can obtain customers’ behavior and transaction information at low costs, which is conducive to improving loan management and preventing moral hazard.

 

The third area concerns quantitative investment. Prof. Shen drew attention to a study by the University of Chicago, which found that ChatGPT4 outperformed the majority of human stock analysts, offering higher Alpha and Sharpe Ratio. The fourth note-worthy sphere is smart investment advisory, which holds the promise of providing good wealth management services to the middle class and even the wider public. Some financial institutions have undertaken trials in this regard, though not without challenges.

 

For AI to be more productive in digital finance, Prof. Shen said that some crucial issues must be addressed, including the constraints of algorithm, the limitations of data, and computing security.