Siloed systems turned routine compliance checks into hours of manual work. Now, AI agents execute these workflows in seconds.
A securities firm managing complex operations across 15 core departments, including brokerage, investment banking, research, and compliance.
Fragmented legacy systems created severe data silos that restricted the firm's ability to match financial products with long-tail customers....
Jianghai Securities Co., Ltd. is a securities brokerage company offering investment services.
Jianghai Securities's Workflow automation is part of this use case:
Related implementations across industries and use cases
Manual coding and RFP analysis slowed teams. AI agents in Teams now generate the drafts, achieving 73% code accuracy.
Routine reviews delayed member support. Now, non-technical employees securely build custom AI agents to resolve complex cases in minutes.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Document-heavy compliance workflows bottlenecked scale. Now, AI processes routine case documents, routing exceptions to staff.
A 500-component architecture slowed developers. A unified data layer runs AI document checks, freeing human brokers for complex advising.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
QC simulations ran 15 hours and reset from scratch on every change. Digital twins cut that to 3.6 seconds.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
Siloed systems turned routine compliance checks into hours of manual work. Now, AI agents execute these workflows in seconds.
A securities firm managing complex operations across 15 core departments, including brokerage, investment banking, research, and compliance.
Fragmented legacy systems created severe data silos that restricted the firm's ability to match financial products with long-tail customers....
Jianghai Securities Co., Ltd. is a securities brokerage company offering investment services.
Jianghai Securities's Workflow automation is part of this use case:
Related implementations across industries and use cases
Manual coding and RFP analysis slowed teams. AI agents in Teams now generate the drafts, achieving 73% code accuracy.
Routine reviews delayed member support. Now, non-technical employees securely build custom AI agents to resolve complex cases in minutes.
Manual document summaries bottlenecked experienced staff. Now, AI drafts preliminary risk assessments, freeing teams for complex advisory.
Document-heavy compliance workflows bottlenecked scale. Now, AI processes routine case documents, routing exceptions to staff.
A 500-component architecture slowed developers. A unified data layer runs AI document checks, freeing human brokers for complex advising.
Analysts couldn't touch the data—every question funneled through engineers, taking hours or weeks. Now they get answers in seconds.
Finance spent six hours stitching four data sources into fully burdened cost models. Now, they use AI to generate them in minutes.
QC simulations ran 15 hours and reset from scratch on every change. Digital twins cut that to 3.6 seconds.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.