---
title: "Shanxi Securities Chief Information Officer Sun Jiafeng: The development of bond trading robots has achieved certain results"
type: "News"
locale: "en"
url: "https://longbridge.com/en/news/258626765.md"
description: "Shanxi Securities Chief Information Officer Sun Jiafeng stated at the \"2025 China Securities Industry Digital Practice Summit Forum\" that the bond trading robot developed by Shanxi Securities has achieved results, reducing the inquiry/quotation response time from 30 seconds to 3 seconds, significantly improving efficiency. It is expected to increase revenue by 5 million this year and an anticipated increase of 8 million to 9 million next year"
datetime: "2025-09-24T04:25:21.000Z"
locales:
  - [zh-CN](https://longbridge.com/zh-CN/news/258626765.md)
  - [en](https://longbridge.com/en/news/258626765.md)
  - [zh-HK](https://longbridge.com/zh-HK/news/258626765.md)
---

> Supported Languages: [简体中文](https://longbridge.com/zh-CN/news/258626765.md) | [繁體中文](https://longbridge.com/zh-HK/news/258626765.md)


# Shanxi Securities Chief Information Officer Sun Jiafeng: The development of bond trading robots has achieved certain results

On September 24th, the "2025 China Securities Industry Digital Practice Summit Forum" hosted by the Securities Times was grandly held in Beijing. Sun Jiafeng, Chief Information Officer of Shanxi Securities, stated at the roundtable forum on "The Implementation of Financial Large Models in Securities Business: Challenges and Path Exploration" that Shanxi Securities' fixed income business ranks among the top in the industry. A very important scenario in the fixed income business is that bond traders from various institutions quote/inquire off-market with each other, and a considerable amount of trading still relies on fax, landlines, and communication software, relying on voice and text interactions between people. Last year, Shanxi Securities began to layout the intent recognition of large models in the entire off-market inquiry scenario, developing a bond trading robot embedded in the entire inquiry/quotation process. Significant results have been achieved, reducing the response time for inquiries/quotations from 30 seconds to under 3 seconds, greatly improving inquiry/quotation efficiency. If we simply estimate revenue, it is expected to increase revenue by about five million this year, and by eight to nine million next year

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