Contact Center Modernization with AI

About the client

The client is one of North America’s largest banks, providing a wide range of financial services, including personal and retail banking. They serve over 20 million personal banking and branded card customers, along with 46 retail partner clients across their North American operations.

Business goals and objectives

The contact center modernization initiative focused on achieving three key strategic objectives:

• Enhancing customer satisfaction and experience: The primary goal was to elevate customer satisfaction (CSAT) and improve the Net Promoter Score (NPS) by delivering superior customer experiences. 
• Migrating to a modernized technology platform: Transitioning from traditional telephony systems and legacy platforms to a robust technology stack was pivotal. The target infrastructure enables lean service implementation and operational excellence through AI-driven operations management. Features such as agentic AI and self-service capabilities empower end-to-end management across channels, boosting efficiency and scalability.
• Optimizing operational costs and efficiency: The initiative aims to reduce operational (OPEX) and infrastructure costs significantly while maximizing the impact of human capital. Improved efficiency in business process management (BPM), zero call wait times, and reduced average call handling time (AHT) for agents are central to this objective.

Challenges

In the retail and personal banking space, the client faced a slew of challenges, ranging from high call drop rates to lengthy turnaround times. Some of the key challenges were:

• Inconsistent experiences - Gaps in agent performance and customer interactions led to misaligned CSAT and NPS scores.
• Call drop rates - 85% of calls were dropped or unreturned due to long wait times or poor first-call experiences.
• High Costs - Each call costs an average of $12, impacting operational efficiency.
• Skill gaps and retention issues - Skill-based call routing, agent training, retention, and roster management became a significant global challenge.
• Collaboration - Engage technology and business teams for robust governance across digital transformation initiatives.

LTM’s solution

The multi-year contact center modernization roadmap and implementation blueprint were created in conjunction with the client’s technology and business teams as part of the tech advisory and consulting team.

• Conversational AI integration - Deployed digital and voice-enabled Bots with ASR (Automatic Speech Recognition) and STS (Speech to Text) capabilities, serving 20+ million customers and 46 retail partners.
• 24/7 multilingual support - Ensures round-the-clock availability, assisting customers anytime in their preferred language.
• Advanced AI automation - Implements human-like voice agents to handle customer tasks and take actions seamlessly.
• Real-time query handling - Reduces wait times by managing routine queries instantly and utilizing Agentic Assistant RAG-based search to provide quick, accurate responses.
• Emotion detection and escalation - Identifies customer emotions and routes complex issues to human agents when required for better resolution.

Tech stack

LTM’s solution leveraged technologies such as:

• Conversational AI and Gen AI with STS (Speech-to-Text and Text to Speech) 
• Automatic Speech Recognition STS 
• RAG Search GPT 3.5 (Subsequently used Mistral and Vertex AI Gemini LLMs as per Organization alignment)
• Telephony system Integration with SIP (Session Initiation Protocol) trunk mapping
• Banking services and API integration in both cloud and on-prem services
• Integration with digital services and messaging platforms to enable Customer services, mobile app cloud platforms, and systems

Business outcomes

• 90% cost savings on the straight-through process: A reduction from US$12 to USD 0.7 per conversation.
• Achieved USD 6 million in annual OPEX savings: Out of this, USD 3 million was realized in the first year. 
• Zero call wait time: Connect anytime with a 90% confidence score for intent identification and cross-channel customer outreach.
• Improved and consistent CSAT and NPS
• Optimized KPI monitoring: Conversational AI dashboards integrated with data governance frameworks enable the monitoring of business and technology KPIs.