Caitong Securities is a universal Chinese brokerage that provides trading, investment-banking, asset-management and wealth-management services to six million investors. Headquartered in Hangzhou with more than one hundred branches nationwide, the firm has grown steadily since its establishment in 1993. To stay competitive in China’s digitising capital-markets, management set a strategic objective to migrate legacy offline workflows onto a data-driven, mobile-first operating model. The vision centred on unifying data, monetising rich user traffic inside the flagship “Caitong APP,” and transforming over 300 marketing scenarios into personalised, event-based journeys—powered by insightful, AI-driven analytics across all service lines.
“Digital transformation is not accomplished overnight—we have walked a long road, ensuring that every single step delivers solid, down-to-earth results.”
—— Director of Web Finance Department
Before engaging our BI solution, Caitong’s data lived in disconnected call-center, trading, CRM and marketing systems amassed over twenty years. These silos blocked a unified customer view, forcing analysts to merge spreadsheets manually and maintain contradictory tagging rules. Campaigns were broad and untargeted, content operations intuition-driven, and mobile traffic spikes overwhelmed reporting processes. Consequently conversion rates fell, regulatory reporting lagged, and management could not surface actionable insights fast enough to satisfy demanding investors and regulators during increasingly volatile market swings.
Working alongside Caitong’s data-governance office, our team first consolidated transaction, account, research and behavioural data into a cloud-native “data middle-platform” built on MaxCompute and Kafka streaming. Unified dimensional models standardised over 300 marketing scenarios, while Elasticsearch powered millisecond-level interactive drill-downs. Quick BI sat on top of this lakehouse architecture, providing drag-and-drop dashboards, fine-grained permissions and row-level security that met stringent financial-industry compliance requirements.
AI capabilities were embedded throughout: an Auto-Tagging engine used gradient-boosting algorithms to classify users by life-stage, risk tolerance and product affinity; natural-language query let relationship managers surface metrics without SQL; and real-time anomaly detection alerted operations teams to unusual flows or order-book imbalances. Implementation followed an agile, three-sprint plan—data ingestion, metric modelling and business rollout—with each sprint ending in hands-on training. Seamless APIs then fed identical metrics to the Caitong APP, WeChat mini-programs and outbound-call systems, ensuring insights reached every client touchpoint.
Within four months, Caitong Securities achieved a single source of truth for six million client profiles and 30 billion historical trade records. Marketing teams launched hyper-targeted push notifications that lifted click-through rates 42% and account activation 18%. Dashboard self-service cut ad-hoc report turnaround from five days to two hours, freeing analysts for alpha-generating research. Real-time risk alerts reduced settlement exceptions 65%, and the intelligent content factory doubled daily article output with no extra staff. Customer-experience scores inside the Caitong APP climbed from 76 to 88, underscoring the platform’s data-driven growth impact and strengthening brand loyalty among investors.
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