Redefining Transactions by Using Conversational AI for Payments

Even though the payment industry has managed to keep pace with the growing pressure to adopt digitalization, in terms of adopting the latest technology, it remains at a nascent stage.

After reaching an era where we can make contactless payments using NFC technology or through a simple barcode scan, the best is still yet to come when we put the industry under the microscope of innovation.

In this article, we are going to unravel one such innovation that uses the capabilities of artificial intelligence to elevate customer experience and smoothen the payment journey for merchants and banks. Conversational payments.

Imagine a situation where you are interacting with your internet service provider through chat support to inquire about the bill details, and you get an in-chat option to make a bill payment. Think of how convenient it would be to not go through your banking or any other fintech app for this.

Now, while we are already on the imaginary route, imagine asking your Alexa device to book movie tickets without ever having to type in any authentication number. The fintech space is only a few applications behind in making these situations real and mainstream with the help of conversational AI for payments. And we will speed up the journey by covering the concept in detail today.

Voice and Text: The Two Foundational Blocks

In the current digital scenario, there are two ways for customers to interact with businesses with less human intervention – text and voice. Conversational AI in the payments industry targets both segments in a way that shortens the payment cycle and makes the customer experience more seamless and convenient.

The industry is moving towards exploring and adopting conversational AI use cases in payments instead of traditional payment mechanisms because the platform acts a lot more than a payment module. It can be built to become a financial advisor (Read our case study on building an AI-powered budget management app), a mode to check account balances, get banking offers, and more.

To understand the entire ecosystem of conversational AI applications in payments, it is important to look into both the forms of new-gen payment systems separately.

Conversational Payments through Voice

A Juniper report estimates that the voice commerce domain will reach $80 billion by 2023. And the transactions made through smart home devices are expected to hit $164 billion by 2025.

The way voice payments work is very similar to making payments through wallets or any other source of digital payment. The only difference is that the users will prompt their device to initiate payment through a voice-built application, and the following journey will start through the use of conversational AI in payments –

• The user will be greeted with an app screen prompting transaction confirmation, which they must authorize through a fingerprint scan or password. Following this, the payment will be made
• Conversely, the receiver will get a confirmation message through text, email, or in-app notification of the amount they have received.

The voice payment functionality directly extends the voice assistant revolution that Siri, Google, and Alexa started. After asking the devices questions about the weather, making reservations, and playing songs, the voice-powered user base is slowly moving towards the capability to make transactions on the go.

While several banks and fintechs have been exploring the benefits of conversational AI in payments, it is only now that they have finally started adopting their virtual voice. For example,

• KAI, a Kasisto conversational AI platform, is being used by Mastercard, JP Morgan, Wells Fargo, and others.
• 2017 Barclays, the Royal Bank of Canada, and Santander introduced voice recognition payments through Siri.
• Ally Bank has been talking to its customers via Ally AssistSM, while continuously improving the platform to identify speech and offer accurate answers.

Challenges for a smooth adoption

Amid a promise of adoption in areas like eCommerce payments, peer-to-peer transfers, and utility payments, the fact that even these voice-based examples of conversational AI in payments is not yet mainstream puts a question mark on its true capabilities.

At Appinventiv, we have made a few observations about the probable reasons behind this occurrence to run hypothesis tests and draw industry-wide solutions. Here’s what we found.

Security concerns – One of the biggest reasons behind the lower adoption of voice-based artificial intelligence in digital payments is the lack of security. Since the users tell the application to make payments instead of going through the usual route of entering biometric data twice and then adding OTP, there is a perceived risk of artificial intelligence payment fraud.

Lack of accent recognition – Another factor keeping the conversational AI impact on payments from being visible is the lack of understanding of accents and voice techniques. AI is still developing to understand context differences in speaking techniques like a slow drawl or raspy squawk.

IoT integration – The typical use case of voice-powered devices lies in multi-platform access. Users interact with many devices – phones, wearable devices, and smart home devices- to perform transactions. Adding these integrations while ensuring breach-proof security becomes a challenge.

Text-based Conversational AI for Payments

Before we look into the details of text-powered artificial intelligence in payments, it is important to look into a similar (and often confused with) already prevalent concept – traditional chatbots.

The traditional chatbots are built to be based on rules with a limited understanding of the conversation and a selected set of responses. Comparatively, conversational AI in the payments industry uses advanced-grade machine learning, natural language processing, and contextual understanding to offer more personalized, human-like interactions.

So, while the benefits of chatbots lie in their quick response time, simplicity, and fewer development efforts, conversational payments enhance customer experience by answering complex queries, providing scalability, continuous learning, and easy integration with other systems.

In many ways, they are here to solve the customer experience issues built upon legacy chatbots that run on untrained and unstructured data.

Here Are the Ways in Which Conversational AI Can Be Used in Payments

Proactive support: Using artificial intelligence in payments helps anticipate needs faster and better. They provide real-time, custom recommendations and solutions based on your users’ browse, purchase history, and preferences, leading to higher loyalty and satisfaction.

Selling opportunities: Imagine an eCommerce chatbot where you ask for a suggestion to gift something to a 3-year-old kid, and the chatbot doesn’t just give you multiple product suggestions and asks about the kid’s preferences, activities, etc. Also, while sharing an in-chatbot payment link for you to make payment. All of this becomes possible with the use of conversational AI for payments.

Account management: The use of conversational AI in payments can also be seen in its tailored interactions. For example, if a user accidentally sends money to an incorrect account, the conversational payments platform can help them rectify the issue with a more human-like interaction.

Fraud detection: Conversational AI for payments uses multi-factor authentication and real-time monitoring for detecting potential fraud activities. With the inclusion of both NLP and Machine Learning, the technology can easily flag when the user is chatting in a different pattern than the chat history and report/block unusual transaction activity from the user’s profile.

For more information, read our in-depth article about Machine Learning in Finance: Leveraging the Technology for Financial Fraud Detection

Challanges for a smooth adoption

Now, even though the platform promises a series of truly revolutionizing benefits, especially in the customer experience sphere, the conversational AI impact on payments will have to face some roadblocks before it witnesses mass adoption.

• Reliance on company’s data – To offer human-like solutions and cross-sell offers, the tools using artificial intelligence in payments must tap into the company’s sensitive data as part of the continuous learning efforts. This, when left unmonitored, can become a very serious concern for the fintech industry, which holds millions of customer data and buying patterns.
• Compliance issues – The questions like how exactly is the user’s data is tracked, where it is stored, which exact information the conversational payments tools have access to, etc., can raise some serious issues on the compliance and regulations front, leading to a dent in the complete adoption of artificial intelligence in digital payments.

How do we Approach the Development of Conversational AI Applications in Payments?

The role of conversational AI for payments is on the path of becoming a must-have. With technologies like Machine Learning helping create more data-intensive artificial intelligence in payments and Natural Language Processing giving them the ability to empathize with your users, the future of conversational AI in payments is very promising. However, this promise comes with some challenges the industry must address by partnering with companies that deeply understand AI software development for payments.

If you approach us at Appinventiv to build your conversational AI platform for payments, here’s how we will manage the project.

First, we will gather an understanding of your end goals and the connection between your objectives and your user’s market requirements. After that, we will create a project roadmap. Next, our team of AI developers will work on creating a proof of concept based on the data your model will be based on and the conversational payments infrastructure. Lastly, we will test the tool in a closed market with real users to understand the platform’s efficacy. We will then deploy it in your current infrastructure or your new application software.

While this is on the development side, on the business end, we would give you suggestions on the features you should add, how to approach compliance, ensuring customer data security, and more.

Here are some of the features we would suggest our clients add when they are looking to build conversational AI use cases in payments.

• Generative AI in payments: The essence of conversational payments lies in empathy and a deep understanding of your users’ needs. This can be achieved perfectly by integrating a continuously learning technology designed to respond like a human, something we promise with our generative AI development services.
• Go beyond payments: While the end goal of any business is to get revenue, we would suggest you build a system that creates relationships by understanding users’ patterns and pain points. Only when you reach the stage where you empathize with the users, will your platform convert into a go-to advisory platform, and your business will become the best example of conversational AI in payments.
• Keep IoT in consideration: Digital payments are happening between various devices – parking points, gas stations, wearable phones, smart TVs, etc. For you to truly explore the benefits of conversational AI in payments, it is critical to make your platform scalable enough to connect between these devices seamlessly.

These are only a few tip-of-the-iceberg-level suggestions – a peek into what you can expect from our AI development company regarding brainstorming. When you partner with us to build your conversational AI for payments platform, you can rest assured that you will get end-to-end ideation and development support to guarantee your space in the list of disruptors.

Get in touch with us today to explore the possibilities.

FAQs

Q. What is conversational AI for payments?

A. Conversational AI in payments defines a technology that can perform human-like interactions with software users as they move from browsers to buyers. An example of this can be seen in an eCommerce chatbot suggesting a buyer gift ideas for a child based on the kid’s preferences, leading up to the chatbot sending them a payment link to make the purchase from within the chat window.

Q. How does Conversational AI for Payments work?

A. The conversational payments platform enables customers to make payments seamlessly within AI-powered conversation tools through chatbots, Intelligent Virtual Assistants/Agents (IVAs), and voicebots. The way it does that is by the integration of high-end technologies like NLP and Machine Learning.

Q. What are the benefits of using conversational AI for payments?

A. Some of the benefits that define the role of conversational AI in payments include – elevated customer satisfaction, better cross-sell and up-sell opportunities, instant fraud detection, deeper understanding of customers, and automation of tasks on the employees end.

Q. Where can we see the use of conversational AI in payments?

A. Conversational AI use cases in payments can be seen across every industry – P2P payment platforms, eCommerce, Media and entertainment, eLearning platforms, and more. Every sector can use the capabilities of the technology to build solid relationships with their customers and turn them into a loyal user base that is willing to pay for the experience.

THE AUTHOR

Sudeep Srivastava

Co-Founder and Director