Financial chatbots have many advantages, including
Benefits-conversational-banking
Conversational banking, and reduced costs
Studies agree that making a digital banking transaction is cheaper than by phone. The cost of a transaction through a mobile device has an average cost according to the specialized magazine Chatbots Magazine.
Financial procedures
The constant learning of chatbots for banks through artificial intelligence allows us to better understand the needs of customers and provide them with a personalized experience on platforms that consumers prefer, such as WhatsApp, this makes the process more agile and less dependent on human interventions. That is, go for complete cases.
Currently, customers demand an active and immediate service and this is one of the great the benefits that conversational banking offers: chatbots for banks are available all the time.
Securing transactions with financial chatbots :
Artificial intelligence reduces the risk of fraudulent transactions because financial chatbots are capable of detecting anomalies or fraud.
Bot and banking: types of chatbots in the financial industry
The banking industry has revolutionized with the arrival of banking bots dedicated to solving different requests and procedures from mobile devices. Chatbots for banks on WhatsApp or Messenger are intelligent and capable of solving anything from simple questions to allowing customers to save.
Customer service chatbot
From branches to banking bots, customers now find quick answers and 24/7 online support. It becomes less necessary to visit a bank branch to answer a question.
Banking Services Chatbot
Bank chatbots are trained to carry out the entire process.
Chatbots for Banks: Tips for Building a Financial Chatbot
To build a banking chatbot, many elements must be taken into account, but the main thing is to provide a user-friendly experience. Do not fall for spam and guarantee all security conditions. Besides:
Remember that your customers are interacting with your company on a social platform where they expect a bot with natural language, personality, and even a touch of humor.
Direct shortcuts, do not give your customers long flows or difficult options to get to what they want.
Examples of chatbots for banks
At ATOM we help different financial institutions and banks in the region to make them conversational and intelligent banks, capable of solving their clients’ efforts in an easy and agile way. Here are some use cases of successful chatbots:
Perhaps by now, it is clear to you that there are indeed different types of chatbots. In this sense, AI conversational chatbots differ from keyword chatbots, which are simpler in the way they interact with the user, partly because their design complexity is lower.
In the specific case of keyword- or rule-based chatbots, these are designed to provide pre-programmed responses to specific customer input. These inputs can be scheduled or pulled as needed, but the basic function of a keyword chatbot is to provide a timely response to timely customer input.
What are conversational commerce chatbots?
As the very name suggests, conversational commerce chatbots are automated chat programs that use NLP/PLN and AI to communicate with customers conversationally, i.e. simulating a person-to-person conversation.
Likewise, these types of chatbots are designed with the intention of helping customers with a variety of tasks ranging from answering questions about products, recommending items of interest, processing and tracking orders, and providing usage information, creating shopping experiences. personalized throughout your shopping journey.
One of the advantages of this type of conversational chatbot -versus those of keywords- is its ability to provide a real conversational experience instead of just providing a generic multiple-choice menu. Additionally, through a conversational chatbot, it is possible to provide support 24 hours a day, 7 days a week, and manage thousands of simultaneous interactions.
These types of chatbots can be integrated into messaging platforms (such as WhatsApp, Messenger, Telegram, and Viber), as well as company websites. The result? Comprehensively improved customer experiences and, as a consequence, greater user satisfaction and loyalty.
As we have already said, AI conversational chatbots are designed to have natural conversations with customers. However, it is important to understand that this type of chatbot requires timely training where -in the middle of its design- the most frequent questions from users are inserted and timely answers to them. In addition, over time, and as AI chatbots interact with more and more people, they progressively gain their knowledge and adapt to respond better each time. From these interactions, chatbots learn to recognize patterns in customer behavior to improve their responses’ accuracy and relevance.
When designing a chatbot to unleash your conversational commerce strategies, it is essential to follow some steps:
Understand your audience: Before creating your chatbot, you must first and foremost understand your target audience thoroughly. What needs and difficulties would you be solving through a bot? On which channels do you like to communicate? Taking these and other factors into account, you will be able to design a chatbot that can interact with your customers in a natural way.
Define your goal and scope: decide what your chatbot can and cannot do. conversational AI chatbot solely for customer service? Will your bot provide recommendations or offer personalized promotions? Having a clear idea of the purpose and scope of your chatbot will help you design a more effective conversational flow.
Pay attention to the design: the conversational flow is essential for the success of your chatbot implementation. Do you want your chatbot to be attractive, natural, and easy to talk to? In that case, apply conversational design principles such as using simple language, providing choice, and anticipating user needs to create a chatbot that people sit down with, instead of transacting.
Employ AI, NLP, and machine learning: Natural Language Processing (NLP/NLP) enables your chatbot to recognize, understand, and respond to users more effectively. Machine learning and AI will improve the performance of your chatbot by “learning” with each interaction to better understand the user, their patterns, and how to provide more accurate responses.
Test and refine your bot: As with any other design project, testing and refining is crucial. Collect analytics, feedback, and comments from your customers to identify areas for improvement for your chatbot. Did you detect that there are many abandonments in the same contact point? Maybe it’s good to take a closer look at this timely stage of the customer journey.
This step-by-step guide will help you build a chatbot that is truly capable of making more genuine connections with your customers.
The best channels to host your conversational commerce chatbot
In practice, choosing the ideal channel to integrate your conversational commerce chatbot depends on several factors, such as:
Engagement: Understand which channels are most engaged in terms of your target audience.
Use Cases: Determine which channels best suit each use case and what their business requirements are in terms of security, supported technologies, immediacy, etc.
Recurring inconveniences of users: detect which channel best addresses the most frequent problems of your clients, due to their very nature or particularities.
After having considered the previous three points, companies must understand which channels are best suited to all of them. It is likely that after careful analysis at least one of these channels will emerge as a good candidate:
Integrating a conversational AI chatbot into all of these channels can be a significant workload at first. Therefore, it is advisable to analyze the interactions with customers and then choose only two or three channels that you think will give you the best return in the first instance.
What are the main benefits of AI conversational chatbots?
Improvements in customer service
In addition, chatbots can also handle large volumes of simultaneous inquiries, which reduces wait time and improves ticket resolution time, positively impacting customer satisfaction.
improved experience
Chatbots deliver highly engaging, end-to-end experiences through ultra-personalized interactions that feel like a natural human-to-human conversation.
What factors should be considered in the implementation of an AI chatbot?
When it comes to implementing AI-powered conversational chatbots, companies need to consider several factors to ensure their strategy aligns with their organization’s business goals.
Pay attention to these items:
Objective: having a clear understanding of what objective your chatbot will fulfill is essential so that you can define consistent success metrics and thus be able to measure the real value of this tool within the experience of your customers.
Intuitive experience: how easy is it for your users to understand how the chatbot works? Is this intuitive enough?
Integration with existing technologies: Your bot should be able to integrate with your ERP, CRM, customer data platform, contact center, and other systems in order to extract data and personalize the customer experience.
Training: How simple will it be to make future changes to your chatbot’s question tree? How difficult or complex is it for your employees to create a new bot? How much training will be needed to be able to carry out the above?
Security and privacy: what certifications does the company responsible for your chatbot have? Does your chatbot comply with all local regulations? Does your bot have native data privacy and security systems?
Analytics and Metrics: What metrics, reports, and data dashboards does the platform offer? Is it possible to cross data directly in the system or is it necessary to export everything? Is the data displayed in real time or is there a delay in its display?
How is it possible to use AI chatbots within conversational commerce?
Throughout their evolution, artificial intelligence chatbots have played increasingly complex and relevant roles within companies.
Its main applications are the following:
Answering Frequently Asked Questions: While this was one of the first uses of bots, even today, this continues to be a very valuable application of this technology. After all, responding to FAQs quickly and accurately improves customer satisfaction and enables scalability that is difficult to achieve through human agents.
Shopping Assistant: AI-powered bots can understand users’ needs and make accurate recommendations based on their preferences. In addition, they can resolve doubts about the different models and guide the customer toward the most suitable product.
Payment: Bots can even facilitate payment within the same chats to complete different transactions there. Features like these are already enabled by Apple Business Messages and, gradually, by WhatsApp in different regions.
Order Tracking: The moments immediately after an order is purchased are very anxious for consumers. So it pays to provide an amazing experience by providing order delivery details and answering any questions that may arise at this time.
Post-sales support: any questions that a user may have regarding a product/service (its use, changes and returns, etc.) must be answered promptly.
Engagement and cross-selling: AI bots excel at recognizing behavior patterns and recommending products to attract and encourage repurchases.