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Development of AI-Powered Financial CRM for Debt Collection
  1. case
  2. Development of AI-Powered Financial CRM for Debt Collection

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Development of AI-Powered Financial CRM for Debt Collection

snotor pro
Financial services
Fintech

Inefficient and Manual Debt Management Processes

B2Kapital faced challenges in managing a large volume of debt cases, leading to inefficient workflows, difficulties in monitoring payments, and limitations in proactive debt recovery strategies. The existing processes relied heavily on manual data entry and lacked effective AI-driven insights for optimizing debt repayment.

About the Client

A debt collection agency providing financial services to banks and other financial institutions.

Enhance Debt Collection Efficiency and Effectiveness

  • Streamline debt case management processes.
  • Improve operator productivity and reduce manual effort.
  • Enhance payment monitoring and reporting capabilities.
  • Implement AI-powered recommendations for debt repayment strategies.
  • Provide a centralized platform for all debt-related information.

Core CRM and Debt Management Functionality

  • Case Import (Excel/XML)
  • CRM Module for Debtors
  • Synchronous Operator Work
  • Calendar & Notifications
  • Operator Work Tracking
  • Message Sending to Debtors
  • AI Recommendation System
  • Bank Statement Processing
  • Report Generation & Export

Modern Web Technologies and API-Driven Architecture

PHP Symphony 2
Ember
REST API
MySQL
Recombee
Bootstrap

External Reporting and National Authority Integration

  • National Authorities reporting systems

Scalability, Performance, and Security

  • Scalability to handle a growing number of cases and users.
  • High performance for quick data access and processing.
  • Robust security measures to protect sensitive debtor data.
  • Responsive design for optimal user experience across devices.

Improved Debt Recovery Rates and Operational Efficiency

The new system is expected to significantly improve debt recovery rates by providing operators with data-driven insights and efficient tools. It will also increase operational efficiency through automation, streamlined workflows, and reduced manual effort, leading to cost savings and improved customer satisfaction.

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