Conversational AI in banking, or “conversational banking” marks a shift from impersonal, robotic interactions to personable bank-bots that juggle multiple requests with a human touch. The key to banking success remains stellar customer experience.
What Is Conversational AI?
Conversational AI refers to systems and technologies powered by intelligence that are created to engage in natural language dialogues with people.
These systems can comprehend human language inputs, analyze them for meaning and generate responses using language.
Conversational AI typically involves a range of techniques and technologies such as natural language processing (NLP) machine learning, deep learning and sometimes elements of speech recognition.
These technologies empower AI systems to understand and reply to spoken or written language in a manner that mimics interaction.
Conversational AI finds application in areas, including assistants, chatbots, voice activated interfaces and automated customer service systems.
In the finance and banking sector conversational AI plays a role, in offering customer assistance personalizing services automating tasks and enhancing user experiences.
How Conversational AI Is Being Used in Banking & Finance?
Conversational AI is transforming the finance and banking industry in the realm of fintech software development. Here’s a glimpse, into how top fintech software development companies are making the most of it;
Customer Support and Assistance
Fintech firms are integrating AI into their customer support systems to help users. Chatbots equipped with natural language processing (NLP) capabilities can comprehend user queries, provide information, aid in transactions and resolve issues.
Companies like Chime and Revolut, in the fintech sector utilize chatbots on their apps and websites to help customers with questions regarding transactions account balances and card related matters. These chatbots leverage AI technology to interpret user queries and offer real time support.
Tailored Recommendations
Through the analysis of user data and transaction histories conversational AI platforms can present personalized suggestions. These recommendations may encompass investment opportunities saving strategies or banking products that align with customer requirements and objectives.
Wealthfront, an automated investment platform harnesses AI to propose tailored investment suggestions to users based on their aspirations, risk appetite and investment inclinations. The platforms chat interface engages users in dialogues to gather details and customize investment plans accordingly.
Financial Planning and Advisory:
Fintech firms are employing conversational AI to offer automated financial planning and advisory services. Through chat interfaces, users can interact with virtual financial advisors to set financial goals, create budgets, and receive ongoing guidance on managing their finances effectively.
Betterment, a popular online investment platform, integrates conversational AI into its service to provide automated financial planning and advisory to users. Through the platform’s chat feature, users can set financial goals, receive personalized recommendations on asset allocation, and track their progress over time.
Risk Assessment and Fraud Detection
Conversational AI technology can examine how customers interact and their transaction behaviors in time to spot fraud or suspicious actions. By pinpointing irregularities and marking them for examination these systems assist financial technology companies in boosting security and safeguarding users’ financial resources.
Players such as Feedzai utilize AI technology to scrutinize customer interactions and transaction details for detecting behaviors instantaneously. Through observing trends and irregularities Feedzais AI driven platform aids fintech enterprises, in recognizing and addressing threats ensuring the protection of users’ financial resources.
Streamlined Onboarding Processes:
Fintech platforms are using conversational AI to streamline the onboarding process for new customers. Chatbots can collect necessary information, verify identities, and guide users through account setup procedures, reducing the time and effort required to open a new account or access financial services.
N26, a digital bank, employs conversational AI in its onboarding process to guide new customers through account setup procedures. Through the bank’s mobile app, users interact with a chatbot that collects necessary information, verifies identities, and completes account opening tasks swiftly and efficiently.
Voice-Activated Banking:
With the rising popularity of voice assistants like Amazon Alexa and Google Assistant, fintech companies are exploring voice-activated banking services. Users can perform banking tasks, such as checking account balances, transferring funds, or paying bills, using voice commands, making the banking experience more convenient and accessible.
Capital, one offers voice-activated banking services through Amazon Alexa, enabling users to perform various banking tasks using voice commands. Customers can check account balances, pay bills, and transfer funds simply by interacting with Alexa, providing a seamless and convenient banking experience.
Financial Education and Literacy:
Conversational AI is also being used to enhance financial education and literacy among users. Chatbots can deliver bite-sized financial tips, answer questions about basic financial concepts, and provide educational content to help users make informed financial decisions.
Bank of America’s virtual assistant, Erica, delivers financial education and literacy through conversational AI. Erica engages users in conversations about budgeting, saving, and investing, providing personalized tips and insights to help users improve their financial well-being.
Five Essential Components for Conversational AI
Natural Language Understanding (NLU):
This is like the AI’s ability to understand what you’re saying, just like how you understand your friend talking to you. It helps the AI figure out the meaning behind your words, so it can respond appropriately.
Dialog Management:
Think of this like a flowchart for conversations. It helps the AI keep track of what you’re talking about and what it needs to say next. It’s like a roadmap that guides the conversation in a smooth and logical way.
Language Generation:
This is how the AI formulates its responses to you. It’s like when you’re writing a text message or an email, but instead of a person typing, it’s the AI generating the words based on what it understands from you.
Context Management:
This is about remembering what was said earlier in the conversation. Just like you remember what you and your friend were talking about a few minutes ago, the AI needs to remember previous parts of the conversation to keep things coherent.
Integration with External Systems:
Sometimes the AI needs to fetch information from other places, like a database or a website, to answer your questions or perform tasks for you. This component allows the AI to connect with those external systems and retrieve the information it needs.
Conclusion
Implementing conversational AI in banking and finance is crucial for various reasons. It enhances the customer experience by providing personalized and convenient services, leading to higher satisfaction and loyalty.
Also, it improves operational efficiency and reduces costs by automating routine tasks and customer interactions.
The 24/7 availability of conversational AI ensures that customers can access banking services and get their queries resolved instantly, regardless of the time.
Conversational AI aids in risk management and fraud detection by analyzing data in real-time, thereby protecting customers and the organization’s assets.
Adopting conversational AI provides a competitive advantage, attracting new customers and retaining existing ones.
Not only this but conversational AI offers scalability and adaptability to meet evolving customer needs and preferences, ensuring long-term success in the dynamic banking and finance industry.
All in all, embracing conversational AI is not just beneficial but increasingly necessary to stay competitive, enhance customer experiences, improve efficiency, and manage risks effectively in today’s digital era not only in FinTech but across industries like healthcare, retail, EdTech and telecom.