Forget ChatGPT—Here’s How Conversational AI Is Quietly Reinventing BFSI

With all the buzz around generative AI, it’s easy to overlook another class of AI that’s driving real impact right now: conversational AI. Unlike rule-based chatbots, conversational AI uses natural language processing (NLP) and machine learning (ML) to simulate human-like conversations across apps, calls, and digital channels.

And while consumer apps like Siri and Alexa are the prominent stars, some of the most powerful conversational AI examples are unfolding behind the scenes in banking and finance.

From instant fraud alerts to multilingual virtual agents, let’s dive into three real-world conversational AI examples in BFSI that are transforming customer service, compliance, and productivity.

Conversational AI examples for your bank or fintech

What Is an Example of Conversational AI?

In its simplest form, conversational AI refers to systems that enable machines to communicate with humans using natural language. It encompasses a variety of technologies, including chatbots, voice assistants, and messaging apps, all powered by artificial intelligence. 

Conversational AI simulates human interaction by processing and understanding human language. Technologies like Natural Language Processing (NLP), machine learning, and deep learning make this possible, allowing AI systems to respond intelligently to user input.

Examples of Conversational AI in Action

• Chatbots for customer service interactions on websites.
• Voice assistants like Siri and Alexa answer questions, control devices, and assist users.
• Virtual agents that handle complex queries and perform actions like booking appointments or troubleshooting technical issues.

Conversational AI helps businesses engage with customers at scale while reducing operational costs. It’s a crucial tool for delivering personalized and efficient customer experiences across various industries.

How Does Conversational AI Work?

Conversational AI combines Natural Language Processing (NLP) and Machine Learning (ML) to understand human language, detect intent, and deliver human-like responses. These systems get smarter over time by learning from past interactions.

Core Technologies:

• NLP: Breaks down human language into components for processing.
• NLU: Understands context, sentiment, and intent.
• ML: Continuously improves accuracy by learning from data.

Unlike rule-based chatbots, conversational AI can handle open-ended queries and multi-turn conversations, making interactions seamless and intuitive.

Conversational AI Assistants in Customer Service

AI assistants are transforming customer service by handling interactions across chat, email, and phone—resolving issues, answering FAQs, and performing tasks like password resets and order checks.

Benefits:

• Instant responses: No wait times for customers.
• Lower costs: Reduces reliance on large support teams.
• Personalized support: Uses customer data for tailored answers.

AI assistants are now common in call centers, available 24/7, enhancing satisfaction and agent productivity.

Conversational AI Automation in Support

Conversational AI automation boosts efficiency by handling high volumes of routine tasks without human involvement.

Common Use Cases:

• Ticket resolution through guided workflows
• Order status updates via automated responses
• Basic troubleshooting without agent intervention

This automation ensures fast, consistent support, reducing response times while improving overall service quality.

Conversational AI Examples in BFSI

Banks and financial institutions are using conversational AI to automate support, enhance security, and deliver faster, more personalized customer experiences.

1. Convin: Voice AI That Automates BFSI Call Center Conversations

While most conversational AI examples in BFSI focus on chat or app-based interactions, Convin stands out by bringing AI automation to voice-based customer calls — the most complex and high-volume support channel in banking.

• Automates 100% of inbound and outbound calls
• Handles EMI reminders, KYC updates, loan verifications, and more
• Improves lead qualification by 60% and reduces manpower needs by 90%
• Offers multilingual support for regional and international banking customers

With conversational AI trained specifically for banking workflows, Convin’s voicebot delivers natural, secure, and scalable conversations, helping BFSI contact centers lower costs and boost CSAT without compromising on compliance or personalization.

2. NatWest’s Cora: AI Fraud Assistant That Scales Trust

What is an example of conversational AI? Meet Cora — NatWest’s AI-powered virtual assistant. Initially designed for basic queries, Cora is now being enhanced with OpenAI’s large language models to handle complex fraud claims and sensitive support issues.

• Handles millions of chats per month
• Reduces handoffs to human agents by over 30%
• Cuts investigation time from days to minutes

Customers don’t need to repeat themselves or wait on hold. Cora understands context, extracts relevant data, and escalates only when necessary. That’s the power of conversational AI built for trust.

3. Qapital: App-First Banking with AI-Driven Self-Service

Qapital is a mobile-only fintech brand that automates over 50% of its customer interactions through conversational AI, enabling real-time support without bloated support teams.

• Users can freeze cards, track goals, or report issues via chat
• Contextual responses powered by NLP and customer history
• Agents focus only on complex or high-value tickets

This example shows how conversational AI isn’t just chatbots — it’s embedded into the core banking journey, helping fintechs stay lean and customer-centric.

4. AirAsia: Multi-Language AI That Cuts Wait Times by 98%

Although this use case is relevant to travel, it hits home for BFSI, especially for global banks with diverse customer bases.

AirAsia’s AI assistant supports 11 languages, handles booking and FAQs, and drastically reduced customer wait time from 45 minutes to under 1 minute.

Imagine the same multilingual intelligence helping your bank serve:

• Rural customers in local dialects
• Expats accessing cross-border banking
• High-volume loan inquiries at scale

Conversational AI makes this possible, without scaling call centers.

Bonus: Voice AI in Call Centers — Like a Smart Siri for Banking

Just like you ask Siri or Alexa to play music or set alarms, banks now use voice-powered AI bots to handle inbound calls.

Convin’s AI voicebot, for instance, can:

• Understand natural speech (even slang or accents)
• Automate balance checks, KYC updates, and EMI reminders
• Escalate with context already captured

This voice-driven experience feels more human than outdated IVRs and improves CSAT by up to 27%.

Explore how Convin powers BFSI voice automation.

Why Conversational AI Is the Future of Business Communication

The shift toward conversational AI is inevitable as companies look for ways to automate communication and improve operational efficiency. For many, the question is no longer "why conversational AI" but how quickly they can adopt it to stay competitive. This technology allows businesses to deliver real-time, personalized communication at scale, which traditional methods cannot achieve.

Key Benefits:

• Scalability: Businesses can handle thousands of customer queries simultaneously.
• Cost Reduction: Automating communication reduces labor costs and improves overall efficiency.
• Improved Customer Satisfaction: With faster response times and personalized interactions, customers are more likely to have positive experiences.

By integrating conversational AI, companies can offer a seamless experience across channels, making it easier for customers to interact with their brand through chat, email, or voice.

Among the leading conversational AI solutions, Convin’s AI-powered phone calls offer next-level automation for businesses, especially in call centers.

Lower your manpower requirements by 90% with Convin

Embracing Conversational AI: A Game-Changer for Modern Industries

Conversational AI is reshaping business communication across industries, offering automation and personalization on a scale previously unattainable. As seen in the examples of conversational AI, companies across banking, healthcare, retail, and telecom are leveraging this technology to improve customer experiences and streamline operations.

For call center managers and business leaders, adopting conversational AI solutions like Convin’s AI Phone Calls is no longer a choice but a necessity. With its ability to automate complex tasks and deliver personalized interactions at scale, conversational AI is poised to become a critical tool for businesses worldwide.

AI-powered phone calls can boost your csat scores by 27%

Frequently Asked Questions

1. What is a conversational AI?
Conversational AI is a type of artificial intelligence that enables machines to understand, process, and respond to human language in a natural, conversational way. It powers chatbots, voice assistants, and virtual agents using technologies like natural language processing (NLP) and machine learning.

2. Which is the best conversational AI?
There’s no single “best,” but top platforms include Convin (for voice automation in BFSI), ChatGPT, Google Dialogflow, and IBM Watson Assistant. The best choice depends on your use case—chat, voice, multilingual support, or industry-specific needs.

3. Is ChatGPT a conversational AI?
Yes, ChatGPT is a conversational AI developed by OpenAI. It uses advanced language models to engage in human-like conversations across a wide range of topics and tasks.