Legacy Contact Center Upgrade with Amazon Connect

Modernizing legacy contact center platform using Amazon Connect

5 min Lesen

Overview

A leading UK-based specialist bank serving SMEs, entrepreneurs and commercial banking customers was operating on a legacy contact center platform that relied heavily on manual customer authentication processes. Agents were required to ask multiple security questions before servicing customers, resulting in longer call durations, increased operational costs and a fragmented customer experience.

The Challenge

The existing platform relied heavily on manual customer authentication, requiring agents to verify customers’ identities with multiple security questions before processing requests. This process increased call duration, customer effort and operational costs while limiting the bank's ability to deliver a seamless digital banking experience.

The contact center environment lacked modern capabilities such as voice biometrics, intelligent self-service, AI-powered agent assistance, advanced analytics and cloud scalability. As customer expectations evolved toward frictionless digital interactions, the existing solution became a barrier to improving both customer satisfaction and operational efficiency.

Manual customer authentication through multiple security questions increased Average Handle Time (AHT)
Legacy contact center platform limited scalability and modernization initiatives
Customer verification process created friction and negatively impacted customer experience
Lack of voice biometrics and automation increased operational effort for agents
Inability to leverage AI-enabled self-service and intelligent routing capabilities
Limited visibility into contact center performance, customer interactions and operational analytics
Existing environment restricted the organization's ability to compete in an increasingly digital-first banking market
Failure to address these challenges would have resulted in continued operational inefficiencies, increased contact center costs, inconsistent customer experiences and reduced adoption of modern customer engagement capabilities

The Objective

The primary objective was to modernize the legacy contact center platform by implementing a cloud native contact center solution capable of improving customer authentication, enhancing security, reducing operational costs and delivering a superior customer experience.

Modernize the existing contact center platform using Amazon Connect
Reduce customer verification time through Voice Biometrics
Improve customer experience by eliminating repetitive security questioning
Reduce Average Handle Time (AHT) and improve agent productivity
Enhance security through biometric-based authentication
Enable intelligent routing, automation and AI-driven customer interactions
Improve reporting, analytics and operational visibility
Build a scalable, cloud native contact center platform capable of supporting future business growth

The Solution

HCLTech designed and implemented a cloud native Contact Center Transformation solution leveraging Amazon Connect and Auraya EVA Voice Biometrics to automate customer authentication and improve customer engagement. The solution integrated customer voice biometrics with Amazon Connect to enable real-time identity verification, eliminating the need for manual authentication while significantly enhancing customer experience and operational efficiency.

The solution was further enhanced with a custom Contact Trace Record (CTR) analytics pipeline from Amazon Connect to Amazon S3, enabling structured post-call analytics using AWS Glue Data Catalog, Amazon Athena and Amazon QuickSight. SAML 2.0-based Single Sign-On (SSO) integration with Azure Active Directory (Microsoft Entra ID) was also implemented to support centralized authentication, enterprise identity governance and controlled access for agents and administrators.

Assessment

Conducted a comprehensive assessment of the existing contact center environment, customer interaction journeys and authentication processes
Identified operational bottlenecks associated with manual customer verification and long call handling times
Evaluated current security controls, customer experience challenges, scalability limitations and integration requirements
Assessed opportunities to implement voice biometrics, intelligent routing, advanced analytics and AI-powered capabilities
Defined a cloud transformation roadmap aligned to the bank's customer experience modernization strategy

Build

Implemented Amazon Connect as the enterprise cloud contact center platform
Designed and developed intelligent IVR experiences and customer contact flows
Configured skill-based routing and intelligent customer call distribution
Enabled Amazon Connect Call Streaming to stream live customer conversations for real-time authentication processing
Integrated Amazon Connect with Auraya EVA Voice Biometrics to provide secure voice-based customer authentication
Leveraged historical customer recordings to create unique customer voiceprints for future authentication
Implemented real-time voice biometric verification to automatically validate customer identities during live interactions
Developed AWS Lambda integrations to orchestrate business logic and API connectivity between Amazon Connect, Auraya EVA and backend banking applications
Implemented SAML 2.0-based SSO integration between Amazon Connect and Azure Active Directory (Microsoft Entra ID) for secure agent and administrator access
Aligned Amazon Connect access with enterprise identity controls, role-based permissions and centralized user lifecycle management
Integrated contact center workflows with core banking platforms and customer information systems
Configured Amazon S3 for storage of call recordings, Contact Trace Records (CTR), reporting datasets and operational data
Built a custom CTR pipeline to capture and centralize Amazon Connect Contact Trace Records in Amazon S3 for analytics and governance
Cataloged CTR datasets using AWS Glue Data Catalog and queried interaction data through Amazon Athena for operational reporting, audit review and KPI analysis
Extended Amazon QuickSight dashboards with CTR-driven insights covering authentication outcomes, queue performance, routing behavior and customer service trends
Implemented Contact Lens for Amazon Connect to provide conversational analytics, sentiment analysis and agent performance insights
Deployed Amazon Q capabilities to improve agent productivity through AI-assisted guidance and contextual information
Developed operational dashboards and reporting solutions using Amazon QuickSight to monitor contact center performance and customer experience metrics

Operate

Established ongoing monitoring and management of the Amazon Connect environment
Utilized Amazon QuickSight dashboards to track authentication success rates, agent productivity, call volumes and customer service metrics
Used Athena-based CTR analytics to monitor interaction patterns, authentication outcomes, queue trends, routing performance and operational KPIs
Maintained SSO governance through Azure AD identity policies, access reviews and controlled provisioning for Amazon Connect users
Continuously reviewed customer interaction analytics and Contact Lens insights to identify improvement opportunities
Optimized customer journeys and contact flows based on operational performance data
Maintained voice biometric authentication processes and integration health monitoring
Enabled continuous improvement initiatives focused on customer experience, operational efficiency and service quality

The Impact

The Amazon Connect-based transformation enabled Cynergy Bank to modernize customer authentication and significantly improve customer service efficiency while providing a scalable foundation for future innovation.

Reduced Average Handle Time (AHT) through automated voice biometric authentication
Significantly decreased customer verification time by replacing manual security questions with real-time voice verification
Improved customer experience through faster and frictionless authentication
Enhanced security through biometric-based identity verification
Increased agent productivity by reducing manual verification activities
Established a scalable cloud native contact center platform supporting future AI and automation initiatives
Improved operational visibility through real-time reporting, analytics and performance dashboards
Improved data-driven decision-making through a custom CTR analytics pipeline using Amazon S3, AWS Glue Data Catalog, Amazon Athena and Amazon QuickSight
Strengthened access security and operational control through Azure AD-integrated SSO for Amazon Connect
Enabled adoption of advanced capabilities such as Contact Lens analytics, Amazon Q agent assistance, intelligent routing and voice biometrics
Key Business Outcomes
KPI 1: Average Handle Time (AHT)
Baseline: Manual authentication through multiple security questions
Outcome: Reduced Average Handle Time through automated real-time voice biometric verification
KPI 2: Customer Authentication Time
Baseline: Time-consuming customer verification process
Outcome: Significantly reduced authentication time, delivering a faster and more seamless customer experience