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Development of a Machine Learning-Based Credit Risk Assessment Platform for Enhanced Debt Management Operations

scalosoft.com

Financial services

Legal

Operational Inefficiencies in Legal and Credit Risk Management Processes

The client faced challenges in manual legal process execution, high operational costs, and the need for GDPR-compliant automation. Legacy systems lacked scalability and integration capabilities, requiring modernization to maintain competitiveness and enable seamless collaboration with external technology partners.

About the Client

Multinational debt management organization operating across Central Europe with multiple member companies, specializing in financial solutions and compliance-driven legal processes.

Key Goals for System Modernization

Automate critical legal and credit risk assessment processes using machine learning
Ensure full compliance with GDPR and data security regulations
Enhance system scalability and interoperability through service-oriented architecture
Reduce manual intervention in KYC checks and operational workflows
Establish a foundation for future system extensions via API integrations

Core System Capabilities

Machine learning models for predictive credit risk analysis
Automated KYC verification workflows
GDPR-compliant data handling and audit trails
API-first integration with existing financial systems
Real-time process monitoring and reporting dashboard

Technology Stack Requirements

Angular

Gitlab

SQL

Xunit

Ninject

Kubernetes

Hangfire

Automapper

Dapper

SonarQube

.NET

System Integration Needs

Legacy financial systems via RESTful APIs
Third-party identity verification services
Existing compliance management tools
Customer relationship management (CRM) platforms

Performance and Compliance Standards

Enterprise-grade data encryption and access controls
Horizontal scalability via container orchestration
99.9% system uptime SLA
Real-time processing latency under 500ms
Automated compliance validation workflows

Expected Business Outcomes

The implementation will reduce manual processing time by 60-70%, decrease operational costs through automation, and ensure 100% GDPR compliance. Enhanced scalability will support 2x growth in customer volume while maintaining performance standards, with API integrations enabling future expansion into new markets and regulatory environments.