Intelligent Account and Counterparty Segmentation for FinServ

Why this matters Financial institutions routinely evaluate new and existing counterparties with incomplete or evolving information. Manual reviews and static rules slow onboarding, create inconsistencies, and increase downstream risk.

Rysun's Intelligent Account & Counterparty Segmentation for Financial Services provides an AWS-powered standardized, ML-driven way to group and qualify business entities early—supporting faster, more consistent decisions while maintaining transparency and governance.

What the solution delivers

• Account and counterparty segmentation into qualification tiers
• Confidence indicators to highlight low-certainty entities requiring review
• A repeatable framework that can be adapted to institutional policies and data

How it accelerates time to value Instead of building segmentation pipelines from the ground up, the solution provides:

• Pre-engineered account-level features
• A proven clustering and scoring framework
• AWS-native data and ML pipelines ready for adaptation
• Teams focus on policy tuning and integration, not core model plumbing

AWS services and why they matter AWS provides the scalability, security, and auditability required in financial services environments.

• Amazon SageMaker – governed model training and batch inference at scale
• Amazon S3 – secure, durable storage for account data and segmentation outputs
• AWS Glue – controlled feature preparation and data transformation
• Amazon CloudWatch – operational monitoring and observability

Business outcomes

• Faster onboarding and qualification decisions
• Reduced operational and downstream credit risk
• Consistent segmentation logic across teams
• Improved transparency and decision confidence