# Moxiang Technology

Hangzhou Moxiang Big Data Technology is a Zhejiang University-linked AI company. Founder Dr. Gao Peng studied under academician Pan Yunhe. Described as China’s only technology company focused on banking-specific financial LLMs and large-scale pretrained AI employees. Jointly developed the Zhihai Jinpan financial model with Zhejiang University to serve China’s 2000+ banks. AI staff support voice services, human-machine collaboration, direct branch operations, remote banking, employee consultation, training, assistance and app avatars. Embedded MaaS and conversational agents assist marketing, customer service and recommendations.
Zhihai Jinpan includes a deep-neural-network training/inference platform and pretrained algorithms and knowledge bases for 150 banking business categories. Its foundation supports hierarchical dialogue recognition, general and industry data/knowledge annotation and human-machine collaboration. Specialized product/scenario tools manage knowledge acquisition, retrieval and reasoning.
Trained on a 1 billion-scale banking dataset, its AI employees include:
1. Direct-marketing assistant: capabilities comparable to a relationship manager with 1-3 years of experience, covering 150 businesses such as asset growth, credit cards and loans. Average conversion reportedly reaches 5%, or 2 times conventional slot-filling/search-based voice platforms. Integrates into CRM and work-tablet workflows for human-like telemarketing.
2. AIGC relationship-manager assistant: trained on selling points of hundreds of products for different audiences, analyzes customer situations and generates personalized marketing, wealth plans, benefits and scripts.
2.1. Knowledge questions: understands bank products, manuals and regulations to answer staff questions.
2.2. Personalized selling points: analyzes customers, suggests asset allocation and suitable products.
2.3. Script guidance: extracts strong personalized approaches from successful outbound conversations.
3. AIGC customer-service assistant: supports context summaries, issue classification, agent guidance, conversation summaries, ticket drafting and outbound strategies.
Deployed at 100+ banks, with 8000 AI staff training and working at the six major banks, leading joint-stock banks, city commercial banks and rural commercial banks. Handles marketing, verification, reactivation, asset growth, installments and consumer-finance communications, improving staff efficiency and results.
Holds 31 technology patents and over 200 software copyrights, plus national high-tech, provincial R&D-center and specialized innovative SME recognition. Established a joint financial-AI laboratory with Zhejiang University and owns core financial AI intellectual property. Included in EqualOcean’s 2020 top 100 potential AI commercialization companies, Hangzhou potential unicorns and the Kunpeng program.
Jinpan, jointly released with Zhejiang University, has 7B and 13B models with further scaling possible. Retail-finance training sources include books, papers, knowledge graphs and dialogue texts. Targets efficient, intelligent and reliable financial questions and answers, text generation and knowledge reasoning.
Core features address general models’ weak quantitative business problem-solving through retail-finance fine-tuning, specialist knowledge injection and external knowledge collaboration. Supports explainable provenance linking outputs to parameters, training data and external knowledge. Combines general model capabilities and financial generalization in moderate-sized models deployable privately with limited enterprise computing. Integrates local data and search components to strengthen output while meeting security and compliance requirements.

Hangzhou Moxiang Big Data Technology is a Zhejiang University-linked AI company. Founder Dr. Gao Peng studied under academician Pan Yunhe. Described as China’s only technology company focused on banking-specific financial LLMs and large-scale pretrained AI employees. Jointly developed the Zhihai Jinpan financial model with Zhejiang University to serve China’s 2000+ banks. AI staff support voice services, human-machine collaboration, direct branch operations, remote banking, employee consultation, training, assistance and app avatars. Embedded MaaS and conversational agents assist marketing, customer service and recommendations.
Zhihai Jinpan includes a deep-neural-network training/inference platform and pretrained algorithms and knowledge bases for 150 banking business categories. Its foundation supports hierarchical dialogue recognition, general and industry data/knowledge annotation and human-machine collaboration. Specialized product/scenario tools manage knowledge acquisition, retrieval and reasoning.
Trained on a 1 billion-scale banking dataset, its AI employees include:
1. Direct-marketing assistant: capabilities comparable to a relationship manager with 1-3 years of experience, covering 150 businesses such as asset growth, credit cards and loans. Average conversion reportedly reaches 5%, or 2 times conventional slot-filling/search-based voice platforms. Integrates into CRM and work-tablet workflows for human-like telemarketing.
2. AIGC relationship-manager assistant: trained on selling points of hundreds of products for different audiences, analyzes customer situations and generates personalized marketing, wealth plans, benefits and scripts.
2.1. Knowledge questions: understands bank products, manuals and regulations to answer staff questions.
2.2. Personalized selling points: analyzes customers, suggests asset allocation and suitable products.
2.3. Script guidance: extracts strong personalized approaches from successful outbound conversations.
3. AIGC customer-service assistant: supports context summaries, issue classification, agent guidance, conversation summaries, ticket drafting and outbound strategies.
Deployed at 100+ banks, with 8000 AI staff training and working at the six major banks, leading joint-stock banks, city commercial banks and rural commercial banks. Handles marketing, verification, reactivation, asset growth, installments and consumer-finance communications, improving staff efficiency and results.
Holds 31 technology patents and over 200 software copyrights, plus national high-tech, provincial R&D-center and specialized innovative SME recognition. Established a joint financial-AI laboratory with Zhejiang University and owns core financial AI intellectual property. Included in EqualOcean’s 2020 top 100 potential AI commercialization companies, Hangzhou potential unicorns and the Kunpeng program.
Jinpan, jointly released with Zhejiang University, has 7B and 13B models with further scaling possible. Retail-finance training sources include books, papers, knowledge graphs and dialogue texts. Targets efficient, intelligent and reliable financial questions and answers, text generation and knowledge reasoning.
Core features address general models’ weak quantitative business problem-solving through retail-finance fine-tuning, specialist knowledge injection and external knowledge collaboration. Supports explainable provenance linking outputs to parameters, training data and external knowledge. Combines general model capabilities and financial generalization in moderate-sized models deployable privately with limited enterprise computing. Integrates local data and search components to strengthen output while meeting security and compliance requirements.

Canonical: https://uniquebase.ai/products/moxiangkeji
Stable identifier: UB-D822
Snapshot captured: 2026-10-15T14:23:27.067Z
English updated: 2026-10-16T01:35:59.528Z

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