Method for generating exhaustion report

By using a digital human interaction module and intelligent agent collaboration, the due diligence process has been automated and made intelligent, solving the problems of low efficiency, large information bias, and long report generation cycle in traditional due diligence, and improving the execution efficiency and accuracy of due diligence tasks.

CN122114446APending Publication Date: 2026-05-29CLP JINXIN SOFTWARE (SHANGHAI CO LTD
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Patent Information

Application Number
CN202610055674.4
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-01-15
Publication Date
2026-05-29

AI Technical Summary

Technical Problem

In due diligence in the banking and insurance industries, existing technologies rely on manual operation, resulting in low efficiency, large information transmission biases, long report generation cycles, and a lack of unified quantitative standards, making it difficult to support scientific decision-making.

Method used

The digital human interaction module obtains due diligence task instructions, schedules intelligent agents to plan task processes, executes sub-tasks by execution intelligent agents, and finally generates standardized due diligence reports by report generation intelligent agents, achieving full-process automation and intelligence.

Benefits of technology

It improves the efficiency and accuracy of due diligence tasks, reduces labor costs and operational error rates, enhances the convenience and flexibility of command interaction, and adapts to due diligence needs in different scenarios.

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Abstract

The invention provides an after-call report generation method, which comprises the following steps of: obtaining an after-call task instruction through a digital human interaction module, and analyzing the after-call task instruction to obtain key after-call parameters of an after-call task; task planning is carried out based on the key complete scheduling parameters through the scheduling agent, and a task execution process of the complete scheduling task is obtained; wherein the task execution process comprises a plurality of sub-task nodes; scheduling an execution agent matched with the subtask type indicated by each subtask node to execute a corresponding subtask execution strategy through a scheduling agent according to an execution sequence among the subtask nodes so as to obtain a target task execution result of the complete scheduling task; and generating an after-call report of the after-call task through the report generation agent according to the target task execution result. The technical problems of low manual docking efficiency, large instruction understanding deviation, lack of pertinence in task allocation and long report generation period in a traditional all-end dispatching processing flow can be effectively solved.
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