AI-Powered Collections System

Transforming Debt Recovery with Agentic AI

How the System Works: Customer Data Ingestion

    Customer Data Ingestion

    Collect and integrate customer data from various sources.

    Predictive Model

    Utilize machine learning algorithms to predict delinquency risk.

    Decision Logic

    Determine appropriate actions based on predicted risk scores.

    Action

    Implement decisions based on the determined actions.

    Learning Loop

    Continuously monitor and refine the model based on outcomes.

    How the System Works: Workflow Diagram

      Data Input

      Customer Data feeds into the Predictive Model.

      Prediction

      The Predictive Model analyzes data and generates risk scores.

      Decision Making

      Decision Logic uses risk scores to determine actions.

      Action Implementation

      Actions are implemented based on the decisions made.

      Continuous Improvement

      The Learning Loop refines the model based on action outcomes.

      Role of Agentic AI: Autonomy

        Data Processing

        Autonomous data processing and predictive modeling.

        Low-Risk Decisions

        Automated decision-making for low-risk customers.

        Model Monitoring

        Continuous model monitoring and refinement.

        AI Efficiency

        Agentic AI enhances efficiency in routine tasks.

        Scalability

        Enables scalable collections operations.

        Role of Agentic AI: Human Oversight

          High-Risk Review

          High-risk decision review and approval.

          Customer Support

          Direct customer communication and support.

          Model Validation

          Model retraining and validation by human experts.

          Complex Cases

          Handling complex customer situations requiring empathy.

          Ethical Considerations

          Ensuring ethical considerations in decision-making.

          Responsible AI Guardrails: Fairness

            Bias Auditing

            Regularly audit and test the model for bias.

            Fairness Across Demographics

            Ensure fairness across demographic groups.

            Mitigation Strategies

            Implement strategies to mitigate potential biases.

            Equal Opportunity

            Promote equal opportunity for all customers.

            Transparent Criteria

            Establish transparent and unbiased decision-making criteria.

            Responsible AI Guardrails: Explainability & Compliance

              Transparent Explanations

              Provide transparent and interpretable explanations of model decisions.

              Compliance with Regulations

              Ensure compliance with relevant regulations like FCRA and ECOA.

              Audit Trails

              Maintain detailed audit trails of all decisions and actions.

              Regulatory Updates

              Stay informed about and adapt to evolving regulations.

              Accountability

              Establish accountability for AI-driven decisions.

              Responsible AI Guardrails: Data Protection

                Robust Measures

                Implement robust data protection measures.

                Customer Information

                Safeguard customer information from unauthorized access.

                Privacy Protocols

                Adhere to strict privacy protocols and standards.

                Data Encryption

                Utilize data encryption and anonymization techniques.

                Secure Storage

                Ensure secure data storage and transmission.

                Expected Business Impact: Reduced Delinquency Rates

                  Decrease Delinquency

                  Decrease delinquency rates by 15% within the next 6 months.

                  Collections Costs

                  Reduce collections costs by 20% through automation.

                  Increased Efficiency

                  Improve collections efficiency by 30%.

                  KPI Tracking

                  Track and monitor key business performance indicators (KPIs).

                  Data Driven Optimization

                  Optimize collections strategies based on data analysis.

                  Expected Business Impact: Customer Outcomes

                    Better Experience

                    Provide personalized and proactive support to customers.

                    Increased Fairness

                    Ensure fairness and transparency in collections practices.

                    Scalability Impact

                    Enable Geldium to scale its operations.

                    Customer Satisfaction

                    Improving overall customer experience and satisfaction.

                    Bias Reduction

                    Reducing potential for bias and discrimination.