AI + Finance
Around the core flows of banks, brokers, insurers and trusts — multi-agent, federated learning and knowledge graphs braided into one rope. Risk, trading, marketing, audit and compliance collection — every step measurable, traceable and supervisable.
Evidence notice: cases, figures and inferred project metadata are unverified scenario illustrations, not established client outcomes, credentials or return promises. Signed contracts define scope, fees, baselines, acceptance and data responsibilities; client business data stays off-chain.
1. Key Capabilities
- Smart Risk & AML —— GNN graph mining plus multi-source fusion lifts suspicious-transaction recall and response time.
- Bond-Trading Agent —— Quote parsing, matching, pricing and compliance — fully automated, 10× trader productivity.
- Cross-Institution Federation —— Federated risk and anti-fraud models keep data in domain and meet financial regulations.
- Smart Audit & Collection —— Compliance rule engine plus LLM evidence collection cuts audit cycles and labor cost.
2. Representative Scenarios
Trust risk control · bond-trading agents · bank precision marketing · insurance smart underwriting · cross-institution AML modeling.
3. Quantified Outcomes
AML response +25%, 10× bond-trading productivity, 60% shorter audit cycles, 100% compliance on cross-institution modeling.
4. Specs & Fit
| Best for | Banks / brokers / insurers / trusts / payments |
| Core tech | GNN + FL + multi-agent |
| Deployment | Private / regulatory sandbox / consortium |
| Compliance | MLPS-3 / banking / personal-finance |
| SLA | 99.95% availability |
5. Case Digest
Top-trust smart risk control
GNN + federated joint modeling sharply lifts suspicious-path recall.
+25% AML response, +18pp suspicious detection.
Broker bond-trading agent
Quote parsing, pricing, matching and compliance — fully automated.
10× trader productivity.
Insurance smart underwriting
Multimodal fusion of underwriting docs lowers manual review.
-60% manual review rate.
Bank corporate-credit smart assistant
Financials, statements, news and industry research integrated; credit recommendations one-click.
9× credit-report throughput, 10× industry-research coverage.
Third-party payments anti-fraud
Transaction graphs + behavior sequences + device fingerprints jointly modeled.
+32pp fraud-block rate, -45% false-positive rate.
6. FAQ
Q. How is data compliance ensured?
A. Cross-institution federated modeling keeps data in domain — meets CBIRC and sandbox requirements.
Q. Time to launch?
A. Single scenario: 6–8 weeks; platform projects: 3–6 months.
Q. Is cost predictable?
A. Lightweight backbone + Skills reuse — average per-inference cost down 40%+.