Success Story

US-Based Financial Services Firm Establishes GenAI COE to Transform CX and Operations

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Engagement Background

The company faced significant challenges in customer experience and operational efficiency, particularly in handling customer complaints, IVR dropout rates, call transcription, and dispute resolution. These issues were compounded by manual processes and data overload, making it difficult to provide exceptional customer service and optimize operations.

Apexon partnered with them to establish a Generative AI Center of Excellence (GenAI COE), powered by Azure OpenAI for development and deployment of custom GenAI solutions tailored to the customer’s needs. Key implementations included call summarization, voice transcription, customized dispute response letters, and a conversational AI assistant.

About the client

This tech-forward financial services company provides simple, personalized payment, lending, savings, and loyalty solutions to consumers and businesses. These include market-leading private label, co-branded, general purpose and business credit card programs, as well as digital payments.

This company with multi-billion annual revenues and 8000+ global associates offers tech-forward payment and lending solutions; and owns and operates loyalty and reward programs for global brands.

The Challenge
A Struggle with Efficiency and Customer Experience

Our customer, a prominent player in the BFSI sector, grappled with several challenges that impacted both customer experience and operational efficiency. Here’s a closer look at the key hurdles they faced:

High Volume of Customer Complaints

Customer struggled to keep up with the sheer volume of customer complaints. Manual processes for summarizing and analyzing these complaints made it difficult to identify trends and address issues promptly, potentially leading to frustrated customers.

IVR
Frustration

Their existing Interactive Voice Response (IVR) systems suffered from high dropout rates, hindering customer service delivery. Understanding the reasons behind these dropouts was crucial for optimizing the IVR experience and improving customer engagement.

Transcription
Woes

The significant increase in call volume created a bottleneck in call transcription and analysis. Manual transcription was not only time-consuming but also prone to errors, hindering company’s ability to extract valuable insights from customer interactions.

Dispute Resolution Roadblocks

The manual process of responding to customer disputes was labor-intensive and lacked consistency. This approach made it difficult to personalize responses and address customer concerns effectively.

These challenges stemmed from two key root causes:

01Operational
Inefficiencies

Manual RelianceClient relied heavily on manual processes for tasks like summarizing complaints, analyzing IVR dropouts, and crafting dispute responses. This approach was not only time-consuming and prone to errors, but also limited scalability as their business grew.

Resource Strain Increased call volumes stretched their resources thin, making it difficult to track and analyze customer concerns effectively. This in turn, hindered their ability to optimize service offerings.

High Costs Manual review and response letter generation for transaction disputes led to increased labor and resource costs.

Limited InsightsThe lack of efficient ways to analyze large volumes of unstructured data made it difficult for the customer to gather ad-hoc insights that could inform strategic decisions.

02Data Overload and
Complexity

Information Avalanche This organization struggled to process vast amounts of call transcripts in various audio formats. They needed a way to efficiently summarize and transcribe this data to unlock valuable insights.

Dispute Data Demands Transaction dispute data often required precise and context-sensitive response letters, making manual processing a challenge.

Small Business Metrics Maze Tracking complex metrics related to their small business index became cumbersome, hindering their ability to gain valuable insights.

These challenges created a significant barrier for this customer in providing exceptional customer service and optimizing their operations. However, as you’ll see in the next section, GenAI offered a powerful solution.

The Solution
Powering Innovation with a GenAI Center of Excellence (GenAI COE)

Apexon partnered with this Financial firm to establish a Generative AI Center of Excellence (GenAI COE). This in-house capability empowers the customer to:

Leverage cutting-edge Large Language Models (LLMs) powered by Azure OpenAI

Develop and deploy custom GenAI solutions tailored totheir specific needs

Automate repetitive tasks and streamline operational workflows

Unlock valuable insights from diverse data sources

Apexon implemented a suite of GenAI solutions for this financial firm, including:

Call Summarization
Call Summarization

Leveraging Azure OpenAI, Apexon implemented a solution capable of accurately summarizing high volumes of call transcripts on a daily basis. This solution is optimized for both cost efficiency and processing times.

Conversational Assistant
Conversational Assistant

Apexon developed a conversational AI assistant powered by Azure OpenAI LLM. This chatbot allows users to ask questions in plain language and receive conversational responses. The solution leverages Azure Web Apps and OpenAI for scalability and cost-effectiveness.

Customized Dispute Response Letters
Customized Dispute Response Letters

Apexon implemented a system that crafts dynamic, precise, and context-sensitive letters in response to customer transaction disputes, utilizing the power of Azure OpenAI.

Voice Transcription
Voice Transcription

Utilizing Azure OpenAI Whisper, Apexon enabled the client to produce high-fidelity voice transcriptions from a wide range of file formats and languages.

These solutions equipped the customer with the capability to unlock valuable insights, automate workflows, and enhance customer experience, driving significant business value.

GENAI SOLUTIONS IMPLEMENTED
GenAI implemented various LLM-powered solutions

Apexon partnered with this financial company to establish a Generative AI Center of Excellence (GenAI COE) to empower them with cutting-edge AI solutions. This COE allowed customer to:

Complaints Summary
Complaints Summary

Apexon’s LLMs automatically analyze complaints, identifying key themes, sentiment, and regulatory concerns. This data empowers the customer to prioritize issues, target improvements, and ensure compliance.

IVR Dropout Analysis
IVR Dropout Analysis

By analyzing transferred call transcripts using LLMs, the customer pinpoints reasons for IVR dropouts, enabling them to refine the system for better containment and customer experience.

Call Transcript Summarization (POC)
Call Transcript Summarization (POC)

This Proof of Concept demonstrates the ability of LLMs to process massive volumes of call transcripts efficiently, potentially saving the customer significant costs compared to manual summarization.

Voice Transcription (POC)
Voice Transcription (POC)

Leveraging Azure OpenAI Whisper API, LLMs transcribe call recordings with high fidelity, enhancing accessibility and searchability for analysis and knowledge sharing.

Special Letters (POC)
Special Letters (POC)

LLMs dynamically generate personalized responses for unique customer disputes, aiming to improve communication, reduce response times, and maintain accuracy.

Key Results
Streamlined Operations & Enhanced Service Levels
Streamlined Operations & Enhanced Service Levels

Reduced onboarding time for new data sources from 14 days to 3 days through LLM-powered automation for faster access to data enabling informed decision-making.

Automated complaint analysis reduced program implementation time and fostered rapid user adoption.

Achieved 91% accuracy in sentiment analysis, ensuring compliance and addressing customer concerns effectively.

Increased Customer Satisfaction
Increased Customer Satisfaction

70% reduction in dispute handling time using LLM.

12x faster Dispute Response Letters generation with GenAI, improving customer satisfaction through faster responses.

50% reduction in operational costs 99% data accuracy, ensuring reliable insights for improved service.

Improved Efficiency & Scalability
Improved Efficiency & Scalability

With smarter decision-making through LLM solutions.

2x faster ML model development by ingesting 60% of data on Azure with historical context and a semantic layer.

Achieved 92% cost reduction in letter generation, from $4.40 to ~$0.30 per letter, saving ~$92k annually.

Ready to unlock the power of GenAI for your business? Contact Apexon today to schedule a free consultation and discuss how we can help you streamline operations, enhance customer experience, and achieve significant cost savings.