Transforming a Global Bank’s Customer Contact Centre Operations Through Maveric Systems’ AI-Powered Solution
By Kishan Sundar, Senior Vice President, Chief Technology Officer – Key Accounts, Maveric Systems Limited
In the competitive banking landscape, customer service quality is a crucial differentiator. Poor customer service is the primary reason customers switch banks. Over 72% of customers expect immediate service and customer service agents to have the full context of their situation. However, traditional bank customer contact centres often fail to meet these expectations, resulting in lengthy resolution times and frustrated customers.
The Problem
A leading global bank faced significant challenges in its customer contact centres, such as
lack of understanding of customer sentiments
inefficient lead management
ineffective complaint resolution
cumbersome feedback systems
The primary concern was prolonged wait times for customer connections, leading to frustration and undervalued customer experiences. Moreover, agents lacked comprehensive knowledge of the financial products customers enquired about, intensifying service inconsistencies across channels.
To address the bank’s specific challenges, Maveric Systems harnessed advanced AI technology and successfully enhanced the overall customer experience while optimizing operations, solidifying the bank’s position as a frontrunner in digital transformation. Central to this achievement was Maveric Systems’ development of an innovative AI-driven Agent Assist solution and an Intelligent Knowledge Management platform.
These solutions leveraged cutting-edge large language models (LLMs) enhanced by RAG (Retrieval Augmented Generation), utilizing sophisticated NLP engines to analyze and interpret customer queries across various channels and interactions. This proactive approach enabled the system to discern customer intent, context, and sentiment effectively while retrieving pertinent information from the bank’s extensive knowledge base.
The Approach
Maveric Systems’ AI-driven Agent Assist redefined the customer contact centre process through a sophisticated AI approach.
The solution identified customer context by analysing customer interactions, including past call logs and understood conversations, and then classified intents and sentiments using advanced large language models (LLM) like the RAG (Retrieval Augmented Generation) based GPT framework. It also assists agents by retrieving relevant information from the bank’s knowledge base and guiding them to the correct workflow. Automating actions based on predefined workflows ensured swift and efficient resolution management, minimising the need for manual intervention. AI has been introduced here with complete human control, where it identifies action, but execution is controlled entirely by the agent. At the end of the interaction, the entire log and feedback from the customer and agent for future analysis are captured.
Here’s an example of how this solution helped.
Let’s say a customer contacted the bank regarding a credit card overcharge on late payment fees. The AI-driven Agent Assist would transcribe the conversation in real-time, draw up the customer’s credit card details along with payment history, retrieve late payment fee details for that credit card, and provide immediate insights into the transaction’s possible workflow for a fee waiver. This proactive approach reduced resolution times and enhanced customer satisfaction.
Challenges Overcome
Implementing the Agent Assist solution presented significant challenges. Acquiring a suitable LLM-based Gen AI model and all the associated technology stack for the banking industry was complex and resource-intensive. Additionally, the banking sector’s stringent privacy and security requirements necessitated extensive compliance measures. Using AI models in a secure environment was critical to the solution. Specialised training for the AI models to accurately understand and respond to banking queries was also crucial, requiring a significant investment of time and resources.
Impact
Maveric’s AI-driven Agent Assist solution offered several advantages:
Reduced Wait Times: Improved customer experience through quicker resolutions.
Enhanced Customer Engagement: Integration of customer transcripts with RAG techniques improved interactions.
Empowered Agents: The dual-focus approach assisted agents in seamless communication and access to relevant knowledge.
Implementing Maveric System’s AI-driven solution significantly improved the bank’s customer contact centre operations, reporting –
40% reduction in average resolution time
5% increase in customer satisfaction scores
30% boost in agent productivity
30% increase in first-time resolution
60% improvement in agent work satisfaction
Increase in call deflection rate through self-service.
Maveric System’s AI-powered solution transformed the global bank’s customer contact centre operations, setting a new standard for customer service in the banking industry.