kairon

When it comes to banking and financial services, the back office is where the real work gets done. This is the area of the business where all of the behind-the-scenes processes take place, from processing transactions and maintaining customer records to preparing financial reports. In the past, much of this work has been done manually, with bank employees completing repetitive tasks using specialized software. However, thanks to the latest advancements in conversational AI, this is starting to change.

Digital Assistants are now being used to automate many of the back-office tasks that used to be done manually. This can, for example, include tasks such as customer service, order processing, and data entry. The advantage of using Digital Assistants for these tasks is that they can not only speed up the process but also improve accuracy. They can also help to reduce costs, as Digital Assistants are often much cheaper to deploy and maintain than traditional software.

Customer Self-Service & Guidance
The use of AI in conversation is predicted to provide customer self-service and guidance. This is practically true of contextual banking which allows customers to receive personalized financial guidance based on their specific situation. Currently, most banks rely on phone banks and various digital channels to provide customer support. However, conversational AI enables customers to interact with Digital Assistants in a natural way, making it easy for them to get the information or help that they need. For banks, this means that they can provide an improved customer experience as well as reduced costs.

Fraud Prevention
Another important use of conversational AI in banking is fraud prevention. By analyzing customer interactions with Digital Assistants, banks can detect patterns that may indicate fraudulent behavior. This can be done in real-time, allowing banks to take proactive measures to prevent fraud from happening. In addition, Digital Assistants can be used to ask customers certain questions in order to verify their identities. This helps to reduce the chances of fraud and keep customers’ information safe.

Contextual Banking
Contextual banking is a form of banking that provides personalized service and advice to customers. This type of banking requires real-time access to customer data in order to offer relevant products and services. AI technology is a key driver of this trend, enabling banks to create actionable and scalable analytics. Over the next five years, banks are expected to move from traditional product-centric relationships to more contextual conversations with their customers. This is made possible by advances in conversational AI technology.

Personalized Financial Advice
Personalized financial advice is a method banks can use to enhance the customer experience. It uses conversational AI to give customers real-time personalized information regarding their financial situation. The personalized financial advice you receive is available in two different ways:

1. Customer service: The initial and most obvious method for customized financial advice is to assist customers with their daily banking requirements. This can include checking balances, moving money, paying bills, or paying off loans.
   2. Customer experience: Personalized financial advice can increase your interaction with your bank via any channel (online or on mobile). For instance, if you’re seeking student loans, your bank may notify you via email or text message to inform you of new programs that could benefit you, depending on your age and location.

A web-based microservices-driven package called kAIron makes it easy to build and scale out contextual AI assistants. By providing a no-coding online interface for adapting, training, testing, and maintaining such assistants, it is intended to make the lives of individuals who deal with AI-assistants simple.

The RASA framework is currently used to build kAIron. RASA focuses on the technology of Digital Assistants, whereas kAIron focuses on the technology involved in pre-processing the data required by this framework. These include the creation of knowledge graphs that can be used to automatically produce questions, answers, and intents, as well as question augmentation.

So it’s no surprise that banks are starting to make widespread use of conversational AI. According to a recent report by Juniper Research, the use of Digital Assistants in the banking sector is expected to grow by almost 300% over the next four years. This is good news for banks and their customers. With chatbots, banks can improve back-office productivity and customers enjoy a more seamless and efficient banking experience.