In the wave of financial digital transformation, large models have moved from being "technically feasible" to "useful for business operations".
Although mainstream general-purpose large models have demonstrated potential in scenarios such as customer service and marketing, they still face challenges in the financial professional field:
- Lack of accuracy: General models often have illusions in scenarios such as financial quality inspection and risk control;
- Weak business understanding: They need to rely on a large amount of manual prompts and knowledge engineering to adapt to financial terms and processes;
- Low collaboration efficiency: The customer service, operation, and compliance links are disconnected, making it difficult for AI capabilities to be integrated into the entire process.
Cloopen Ai Large Model Application Scenario Solution: Designed for Finance
Cloopen Ai believes that what financial AI requires is a "professional brain" capable of understanding business processes, rather than a general conversational tool.
So, while the industry is still debating "who will be the Prompt engineers", Cloopen Ai has already launched a vertical financial domain, out-of-the-box, scenario-based solution for finance: enabling seamless integration of AI capabilities with business processes, driving a double leap in efficiency and accuracy.
This solution is centered around six vertical intelligent agent products, deeply integrating financial workflows, regulatory rules, and business knowledge bases to achieve a leapfrog upgrade from "single-point tools" to "intelligent collaboration throughout the entire process":
01 Quality Inspection Agent, more precise financial compliance monitoring
- Out-of-the-box ready: Includes financial quality inspection workflows and key scenario quality inspection items, such as large model quality inspection: accurately identifying 7 types of complex financial issues like customer responses being contradictory, unconfirmed content, and risk omissions, and small model rule quality inspection: 11 hard indicators like silence, sensitive words, and emotional fluctuations.
- Deep scenarios: Precisely identifying customer metaphors, unclarified content, and logical contradictions, far exceeding the performance of general tools in complex financial conversations.
02 Insight Agent, focused on in-depth customer demand exploration
- Business understanding: Includes financial scenario mining models, with strong thinking and financial business understanding capabilities, able to deeply understand customers' implicit needs, potential complaints, and potential business opportunities, etc., key business items.
- Precise leap: The accuracy of implicit demand identification is 30% higher than general models, achieving precise matching of demands and products.
03 Agent for Call Center, more intelligent service expert in finance
- Knowledge integration: Integrates massive financial regulatory documents, internal knowledge bases, and historical cases to build professional response capabilities.
- Embedded in business flow: Deeply understands various business processing logic of financial institutions, accurately grasping customer intentions in interaction, and recommending the optimal processing flow and key operation steps in real time.
04 Knowledge Assistant, the "instant response hub" for enterprise knowledge
- Scenario-based intelligence: Builds a financial scenario library and conversation script library, accurately parses multi-modal documents, achieving scenario-based responses for complex business issues.
- Business flow linkage: The conversation script library and business processes are linked, providing scenario-based response guidance for front-line personnel.
05 Agent for Call Center, the "real-time assistant" for gold agents
- Empowerment by gold experience: Extracts the call center's outstanding agent's order-making experience, dynamically optimizes the conversation script library and strategies, and recommends more precise and customer-friendly content.
- Dynamic process embedding: Provides real-time process navigation, gold conversation script recommendations, and intelligent form filling throughout the communication with customers.
06 Coach Agent, the "AI incubator" for talent capabilities
- Scenario-based question bank: Through the mining of massive real customer communication scenarios, learns the order-making conversion experience of outstanding agents, and generates a scenario-based question bank.
- Enterprise talent profile: Explores the ability profile of gold agents, systematically consolidates talent cultivation SOPs, and thereby better organizes AI capability training.
@Cloopen's advantages
01 Pre-set scenarios, agile implementation
- Built-in financial-specific workflow: covers 6 major business lines including marketing, risk control, and customer service, avoiding enterprises from building Prompt and rules from scratch.
- Plug-and-play architecture: supports API-level integration with existing bank systems (such as CRM, credit platform), and the scenario can be launched within two weeks.
02 Dual solutions for security and cost optimization
- Local deployment: meets financial data compliance requirements.
- Hierarchical computing power adaptation: supports flexible configuration from T4 graphics cards to Ascend clusters, reducing the investment threshold for small and medium-sized banks.
03 Continuous evolution ecosystem
- Dynamic knowledge base feedback mechanism: forms a "business feedback → model optimization → capability upgrade" closed loop.
- Financial scenario library: updated quarterly, synchronizing regulatory policies and market trends.