What is conversational AI banking – Benefits and Examples

Irina Kolesnikova
February 10th, 2022

Person having conversation with AI

Juniper Research predicts the total number of people using digital will reach 3.6 billion by the year 2024. But for a traditional financial institution, it could be challenging to compete with fintech.

Automated conversational banking could be the pain-reliever. Here is a simple example: based on our experience, every customer service call contact costs about 3.2 EUR (in Estonia), but a huge part of this (50% and more) could be automated either with conversational IVR or chatbots.

In this article, you will learn about:

What is Conversational banking

dialogue with a chatbot

Conversational banking is a digital banking technology recreating a personalization level of human connection on digital channels.

It takes on many forms: text messages, visual and voice communication tools and ways to communicate, such as mobile apps, websites, messaging apps, etc. The best part of it—you can automate repetitive inquiries using artificial intelligence (AI) that enables customers to interact with banks through voice-activated or text-based chat interfaces.

AI software allows customers to engage with banking systems for routine financial services and transactions through convenient smartphones, tablets, PCs, smartwatches, television remotes, and other digital technologies.

Conversational ai banking uses

There are many ways in which conversational banking AI solutions can be useful for customers and their financial institutions. Some of the most common applications in the banking industry include:

  • Checking account balances
  • Reviewing transaction histories and budgeting recommendations
  • Transferring money between accounts
  • Paying bills
  • Applying for loans or credit cards
  • Changing passwords
  • Receiving fraud, repeat charges and suspicious activity notifications
  • Reporting upcoming travel
  • Reporting lost or stolen cards
  • Activating new cards
  • Checking rewards and points balances
  • Blocking cards

Conversational Banking Technology

Conversational banking – benefits for clients

Conversational banking – benefits for banks

 

Reduction of operational costs

Conversational AI also helps banks reduce their operational costs. Multiple conversational banking use cases identify significant cost savings derived from a reduced need for extensive training of human customer care representatives for capabilities in handling more complex transactions.

For instance, TitanCS has automated about 40% of all the incoming contacts, and 60% of written ones.

customer loyalty

Enhance customer loyalty and satisfaction

By providing a more personalized user experience, conversational banking solutions also help organizations enhance a customer journey and thereby loyalty and satisfaction levels.

In a study conducted by Juniper Research, approximately 50% of customers would likely switch their bank if they felt that the institution did not care about them as individuals.

Recorded response

Talking with the customer personally

Conversational banking leverages technology that helps to provide flexible and personalized service as a more human-like interaction tailored to the customer’s specific needs and behaviors.

You can quickly provide information on specific products and financial services—or more detailed explanations about specific banking procedures. Text and voice communications are also easily personalized based on various factors, including location, time of day, and the digital device.

channel support

Support
existing channels

Conversational banking solutions must also support customers who still prefer engaging with the bank’s more traditional websites and mobile apps.

Therefore, the AI-enhanced interface should be capable of working seamlessly alongside these other types of human and digital channels—rather than completely replacing them. After all, banks rarely want to alienate their long-term customers by forcing them to learn a new and sometimes intimidating technology.

Calls automated with conversational AI can work here: looking like good-old-fashioned phone conversations, it brings faster answers and a better experience (because it is always polite and not influenced by the mood or bad days).

data leaks

Reduce risks
of data leaks

Another benefit of conversational AI for banking is that it dramatically reduces the risk of data leaks.

In recent years, social engineering attacks are rising. People could lose their money because of too emotional human support: a criminal tells a pitiful story and asks for access to another person’s bank account.

Conversational AI systems are infinitely more secure because they no longer require customers to enter personal information into data fields (like login credentials, addresses, and credit card numbers)—and will never fall for a sob story.

different institutions

Benefits for institutions
of all sizes

One of the great advantages of conversational banking solutions is that organizations of all sizes will experience tremendous advantages. Even small banks will benefit from this technology—especially if they want to beat their local competition!

In contrast, the development of mobile banking apps can be prohibitively expensive for smaller banks. Meanwhile, conversational AI does not require additional IT infrastructures, such as servers and databases. So, smaller financial institutions can implement these AI solutions for a relatively low cost.

gain insights

Gain insights into
a customer’s behavior 

This is possible thanks to Big Data analytics, which can help the bank gain insights into customers’ decision-making processes and preferences.

Financial institutions can provide relevant promotional offers and recommendations through conversational AI solutions in real-time without human intervention by a customer service representative.

Conversational banking strategies:
3 main use cases 

Conversational AI banking allows customers to resolve simple questions or requests in real-time. The customer interacts with the software using natural language—which is then translated into a format that the bank’s internal systems can recognize. 

3 primary areas banks are exploring conversational AI chatbots and IVR:

  1. Personal Finance Management (PFM) – With more people looking to manage their money online or on the go from their smartphones, PFM tools have been growing increasingly more popular over the last 20 years. PFM benefits customers wanting access to personal finance management tools that help them stay on top of their spending habits by sending automated spending alerts while also managing their cash.
  2. Customer service – One of the primary areas of practical use for conversational AI is in customer service. In many cases, AI-enhanced technologies can successfully prioritize requests and route them to the right human agent. Customer issues could be automatically resolved either through a chatbot or phone call with conversational IVR—instead of waiting a long waiting time until they are connected to a customer service representative. By automating responses to customer questions, you can handle a higher volume of customer interactions without requiring additional staff or frustrating your customers.
    Example of routing a query with conversational banking technology
  3. Small business services – Banks are also starting to explore how conversational AI provides better services for small businesses. These conversational banking use cases often involve providing automated support for repetitive administrative tasks, such as invoicing, tracking expenses, and applying for loans. On some occasions, AI-enhanced chatbots even offer real-time financial advice to small business owners on topics that include how to manage their cash flow or grow their business.

Conversational banking experience:
4 best industry examples

  • Self-learning AI chatbot that numerous larger banking institutions find particularly useful. This proactive virtual assistant begins by interacting with the customer, determining the specific problem, then it either provides a client with a solution or directs the conversation to the appropriate support agents. It can also provide multilingual interactions, geographic directions, and other location-based services.
  • Conversational IVR that automatically resolves customer issues and even prioritizes urgent cases. On average, customers wait on the phone for more than 2.4 minutes before connecting with a human customer service agent. Only after waiting for such an extended period can customers even begin to describe their issues. MindTitan’s Conversational IVR utilizes only the most advanced speech recognition software and machine learning technologies to empower customers to ask queries in their own words and get a solution automatically without any human agent assistance.
  • During the past year of using a chatbot, BRI, one of the largest banks in Indonesia reported that monthly active users increased 89% month-on-month on average, after implementing a smart virtual assistant. The assistant has managed to streamline customer service operations and increase productivity by up to 97%. The assistant has succeeded in refining banking operations to attract and retain customers, especially micro customers.
  • IndusInd Bank’s launched the IndusAssist voice assistant in 2018. Their clients can conduct banking transactions on the go, not even looking at their devices’ screens, which is convenient nowadays.

Conclusion

conversational ai

The trend is clear: to compete with fintech, the legacy banking industry needs to implement Conversational Banking solutions in successful customer service to provide clients with a better experience. Using AI-powered Conversational IVR and chatbot reduces costs, radically boosts client satisfaction and loyalty, and eliminates human mistakes caused by an emotional state of mind. Setting up the process could be challenging, so it is crucial to choose the right technology partner.

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