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AI-Driven Customer Retention and Process Automation Platform for Global Banking

appinventiv.com

Financial services

Challenges in Customer Retention and Operational Efficiency

The bank faces significant challenges in managing massive data volumes from daily transactions and loan applications, resulting in 6% annual churn in its home loan portfolio. It lacks insights into churn drivers and struggles to optimize ATM cash management, impacting customer satisfaction and operational efficiency.

About the Client

A leading bank in Europe operating across multiple national markets, providing multilingual banking services to a diverse customer base.

Objectives for AI Implementation

Develop AI-driven solutions to automate banking processes and reduce manual workload by 35%
Implement predictive analytics to identify at-risk customers and improve retention rates by 20%
Optimize ATM cash management to achieve 92% service levels through ML-driven forecasting
Deploy a multilingual conversational AI to handle 50% of customer service requests

Core System Functionalities

AI-driven customer churn prediction dashboard with risk scoring (1-10 scale)
Multilingual chatbot (7 languages) for real-time complaint resolution and fraud reporting
ML-based ATM cash demand forecasting using 10M+ transaction data points
API integration with CRM for actionable insights and personalized interventions

Technology Stack Requirements

Artificial Intelligence (AI) and Machine Learning (ML) frameworks

Natural Language Processing (NLP) for multilingual support

Cloud infrastructure (AWS/Azure)

Python-based data analytics tools

System Integration Needs

CRM platform (e.g., Salesforce/SAP)
Mobile/web banking applications
Transactional databases and payment gateways

Performance and Security Standards

Scalability to handle 10M+ daily transactions
99.9% system uptime for critical services
End-to-end encryption for financial data
Real-time processing with <200ms latency for chatbot responses

Expected Business Impact

The AI implementation is projected to reduce operational costs by 20%, increase customer retention by 20%, and improve ATM service levels to 92%. Automation will cut manual processes by 35% while enabling proactive customer interventions through predictive analytics.