Conversational AI & Multi-agent AI for 24/7 banking assistance
MAR 24, 2025
What if we told you that your bank could talk to your customers anytime and anywhere through any channel? Many banks and financial institutions like yours serve their customers through multiple channels. Thanks to internet and mobile banking, quick and secure digital transactions will become the norm for customers in 2025.
Surveying a total of 75k banking customers, it was found that a majority of them considered trust to be the main factor in choosing a bank, while 72% of them expected quick and on-the-spot service! Personalization was also one of the key factors that influenced some customers to opt for a specific bank. Once dominated by big players, the banking industry is now a levelled field for independent challengers like you.
If you also want to understand what these customers expect from you in terms of ease and simplicity, it might be the right time to integrate your banking operations with conversational and multi-agent AI systems. This is because one industry that has benefitted the most out of all the industries in the financial services sector is banking.
How did AI become more prevalent in the banking industry?
Artificial Intelligence in banking has magnificently transitioned from classic data-driven methodology to modern Generative AI for financial services and banking. Tracing back to the time when AI was used for simple work automation in banks, this technology has developed predictive capabilities to understand what your consumers want! According to a study by Grand View Research, the market size of AI in banking will grow at a CAGR of 31.8% from 2024 to 2030.
Would you believe it if we told you that 80% of banks have acknowledged the fact that AI has made a difference in the banking sector? The growth potential of AI is projected to climb a staggering $1 trillion, as per a report by McKinsey. Banks like yours are upgrading their tech by incorporating conversational AI with multi-agent systems to help customers plan their investments safely.
What is Conversational AI in banking?
Open-source projects developed by tech giants like Amazon and Google have made conversational AI a common household name. Domestically, conversational AI agents and voice assistants like Alexa and Google Home can understand and interpret your requests in over 1000 languages. But what is conversational AI in banking, and why does it matter to you?
Don’t confuse conversational AI in banking with basic chatbots fed with limited and irrelevant responses that can’t mimic what we can do. Unlike basic chatbots that work on rigid scripts and manage simple troubleshooting, conversational AI technology uses natural language processing to understand the motives of your customers and how to solve their issues.
Types of conversational AI agents in banking:
a) Chatbots: Clever banking assistants that answer FAQs and send alerts, notifications, and balance details.
b) Financial advisors: Personalized AI financial advisors that provide portfolio tips personalized to client’s spending patterns.
c) Voice assistants: Financial agents that generate voice commands and allow clients to access financial services.
How does a Conversational AI agent check all the CX factors?
Conversational AI agents in banking hit every CX factor you can think of, be it trust, speed, accessibility or personalization. Once you become a master of these CX factors, it won’t be long before you are counted amongst the most well-established banks in your region. Following are some of the diverse sets of technology incorporated in Conversational AI agents for banking:
1) Natural language processing
Conversational AI agents use Natural language processing to decrypt lesser-known bank-related jargon, understand customer motives, and come up with a satisfactory response that solves their problem.
2) Generative Artificial intelligence
Choose any of your trained banking representatives and make them compete against a conversational AI agent with generative AI capability. You will be stunned by how closely it will resonate with the bank’s tone of voice and generate answers to customer queries.
3) Deep learning and ML
The massive amount of unstructured data obtained from millions of customer interactions is converted into a structured format with deep learning and ML in banking operations. Apart from this, it also helps reduce downtime and alerts your customers about emerging system failures.
4) Automatic speech recognition
The automated audit of customer interactions is carried out with the help of an authentication technology like automatic speech recognition. Customers can communicate with conversational AI agents in banking through simple voice commands.
Why Multi-Agent Systems Are Essential for an AI-First Bank?
Similar to employees working at your bank, multi-agent AI systems for banking customer service are your virtual workers that are made up of many AI agents. As per an analysis by McKinsey, multiagent systems are human-like AI agents who can manage task creation, workflow management, and plan of action by themselves.
Like a beehive, a multi-agent system comprises numerous independent agents, each having their own capability to make decisions and set goals. Instead of working in isolation, multi-agent systems work together like a swarm of bees and interact with each other to draw strategic conclusions.
Let us give you a simple example: Suppose one of your customers is applying for a loan and doesn’t have all the necessary documents. In that case, multi-agent AI systems for banking customer service can step in and manage the loan application process without external help. Their assistance isn’t limited to customers. They can even help your bank employees secure their next sale!
Benefits of Conversational and Multi-agent AI in banking
Conversational AI agents give a convenient solution for customers to interact with banking officials. Your bank can improve its workflow by enhancing customer engagement and freeing up staff to handle complicated transactions. Let’s go through some of the best benefits of conversational and multi-agent AI in banking.
1) Builds team synergy
The conversational AI agents aren’t here to replace your customer service agents. They are here to make banking customer service a breeze. Your human workers can quickly complete customer-facing tasks like identification, verification, and managing customer relationships by working collaboratively with conversational AI agents. They also assist your team by providing the contextual meanings behind customer requests by understanding their queries.
2) Handles customer service
Your software, linked with generative AI for financial services and banking, can help reduce customer wait times, improve the quality of calls, and provide personalized support to your customers. The conversational AI agent talks to your customers like humans and has the autonomy and perception to independently resolve their queries. When it observes a case where your customer is dissatisfied with the service, it can re-route the call to a human agent to get the query resolved.
3) Stays compliant and reliable
Since your banking industry is highly regulated, the technology you implement in your banking systems must comply with the regulations set by your government regarding data privacy. By forming a one-to-one conversation with your users, a conversational AI agent maintains the security of personal data and wins their trust. While chatting with customers, the agent also records a transcript that can be stored and used for data analysis and compliance reporting.
4) Works with all platforms
There is a lot of friction in the process of standard chatbots that can lead to the customer hanging up the call. But unlike standard chatbots, conversational and multi-agent AI technology isn’t restricted to a particular platform or service. Customers can interact with conversational AI agents via a method they prefer, as these AI agents can be deployed across various channels like WhatsApp or Messenger.
5) Tracks suspicious activities
Conversational and multi-agent AI for 24/7 banking assistance can recognize the patterns of fraud in a transaction or conversation by grasping the content, context, and sentiments of the interaction. In a case where a customer who usually makes small payments suddenly initiates a big transaction, the conversational AI agent for fraud prevention detects that activity and immediately sends an alert and warning message to your InfoSec team.
Use-cases of Conversational and Multi-agent AI in banking
Before a certain period of time, the use of Artificial intelligence in banking was restricted to front-office operations. By the end of 2022, Generative AI had taken over, and banks could now use AI to streamline their back-office operations as well. Let’s look at some of the important use-cases of conversational and multi-agent AI in banking:
1) Managing customer authentication
Conversational and multi-agent AI for 24/7 banking assistance can request IDs to check validity, provide a simple roadmap to your users for document submission, and share real-time updates on the status of account setup. Your customers can also approach the AI chatbot to learn about loyalty programs, cashback schemes, card usage bills, and many such FAQs.
2) Keeping track of bill payments
Apart from setting up the account, your customers can take care of their recurring bills and make payments through the conversational AI interface. The interface thoroughly verifies and confirms the transaction through an additional layer of security like OTP. They can also make contacts or carry wire transfers by interacting with the AI agents and managing their finances.
3) Personalizing financial advice
Based on the financial condition of your customers, such as their goals, spending history, and available funds, the conversational AI agent for financial customer support can generate optimal financial advice for them. Customers can also receive timely updates on their investment portfolio via their preferred channels, like SMS or emails.
4) Up-selling and cross-selling
Conversational & multi-agent AI for 24/7 banking assistance can introduce up-selling and cross-selling offerings and have a contextual understanding that helps them break down user intent. Once the customers are authenticated using their user authentication protocol, the AI chatbots for banking understand their intent and present the information as requested before them.
5) Collecting and sharing documents
Millions of personal documents uploaded each day can be analyzed and verified in real-time with the conversational AI agents. It reduces bureaucracy and time consumption by giving your customers quick assistance with filling out forms for loan requests, creating fresh accounts, and freezing lost cards.
6) Setting auto-payment notifications
You can program your AI agent to send timely payment reminders to your customers and keep them updated about pending fees or missed transactions. Customers can be notified about bill payments and due dates through text, e-mail, and even push notifications. The AI agent also enhances the payment experience by providing multiple methods to settle these payments.
7) Detecting fraudulent transactions
You can quickly identify fraud or any suspicious activity in real-time by monitoring transaction patterns with conversational AI agents powered by AI and machine learning. Whenever a transaction appears abnormal, the AI agents immediately act on that activity and send quick alerts to the customer and the bank to prevent fraudulent transactions.
Famous examples of banks incorporating conversational & multi-agent AI
Many banks have incorporated innovative ways to surpass customer expectations and reduce the workload on customer service agents. Here’s a roundup of some noteworthy banks using conversational AI agents and setting up new standards for the banking industry.
1) JPMorgan Chase
LLM Suite, the Generative AI for financial services and banking at JPMorgan Chase, is accessible to more than 60,000 of its employees, most of them being financial advisors. Similar to OpenAI’s ChatGPT platform, it is a conversational agent that can work as an experienced virtual research analyst and help employees write professional emails and create detailed reports.
2) HSBC
Warren Buckley, the Head of optimization and Contact Centres at HSBC, launched Conversational Builder to blend human empathy with intelligent automation. It is one of the best personalized voice assistants for banking services that has amazing contextual understanding and banking expertise. It lightens the pressure on HSBC’s customer service agents by automating repetitive tasks.
3) Bank of America
Erica is one of the best personalized AI financial advisors with predictive analytics and cognitive messaging abilities that can handle around 1.5 million client interactions daily. It helps users manage money and updates their credit scores. Apart from that, it keeps an eye on how much users are spending, reminds them of bill payments, and identifies potential money-saving opportunities.
Future of conversational and multi-agent AI in the banking industry
In the coming years, you will be able to offer more refined and smooth customer service with the help of conversational AI agents and personalized voice assistants for banking. Banks which adapt conversational AI earlier than their competitors will definitely get the upper hand in the following aspects:
1) Personalized communication
Generative AI models like OpenAI’s GPT will generate relevant human-like responses and make conversations more interactive and personalized with context awareness. In future, the interactions your customers have with conversational AI agents will be more intuitive, empathetic, and effective.
2) Customer journey analytics
You will be able to optimize and plan your offerings by understanding consumer behaviour across various touchpoints with the help of AI-powered customer journey analytics. It will swiftly conduct the processing of financial data from millions of conversations and online transactions to help you optimize your offerings accordingly.
3) Enhanced Fraud prevention
The conversational AI agent for fraud prevention will monitor user transactions instantaneously to detect fraudulent patterns or suspicious activities using predictive analytics and ML in banking operations. They will proactively alert customers about security and counter cyber threats with greater accuracy.
Personalize banking customer service with a Conversational AI agent
Without any second thoughts, the conversational and multi-agent AI for baking is going to make your customer journey smoother by providing an efficient way to manage finances. With the commitment of 24/7 banking assistance, it is set to make customer service more personalized and secure.
Our diligent team at Webelight Solutions Pvt. Ltd. has the expertise to develop AI chatbots for banking that provide intelligent responses simulating human conversations. The conversational AI agent for financial customer support would help you expand your financial services across aspects like customer service, marketing, and sales to enhance user retention and upsell products all through the customer journey.
