There is research by Juniper that in 2024 the number of people using digital will reach 3.6 billion. However, it might be difficult for a conventional financial institution to compete with fintech.
The solution might be automated conversational banking. Here is a straightforward illustration: according to our experience, each customer service call in Estonia costs about 3.2 EUR. However, a significant portion of this (at least 50%) could be automated using conversational IVR or chatbots.
But in order to understand AI banking, you will first have to have some basic idea about it. so, without delaying it anymore let me start with….
What is Conversational Banking?
If I can define conversational banking in a sentence then I’d better be using the sentence below.
“Basically it is a digital banking technology to personalize all of your transactions and human connections on digital channels”
It comes in a variety of shapes and sizes, including texts, websites, messaging apps, mobile apps, and other visual and verbal communication tools. The best part is that artificial intelligence
(AI) enables customers to communicate with banks through voice-activated or text-based chat interfaces while automating repetitive inquiries.
Customers can interact with banking systems via convenient smartphones, tablets, PCs, smartwatches, TV remotes, and other digital technologies thanks to AI software
for everyday financial services and transactions.
Conversational banking AI solutions
can benefit customers and their financial institutions in a variety of ways. In the banking sector, a few of the most popular applications are as follows:
Checking your account balance
Reviewing your transaction history
Transferring money between the accounts
Paying the bills
Loan applications/Credit Card Applications
Change your bank account password
Reporting your future travels
Reporting your lost bank things like cards and stuff
Activating new cards
Benefits Of Conversational Banking
1) Understand the language of the client
By enabling voice recognition, conversational AI for banking further customizes the customer experience.
Customers can speak commands to the software, and the software will translate their responses into input for AI, which will respond with an answer in a matter of seconds. Additionally, it is especially helpful for clients who have hearing or vision impairments and cannot use other digital customer service systems.
2) Zero waiting time
Quite self-explanatory, but to emphasize: this is what delights customers!
When compared to the typical 2.5-minute wait for customers to be connected to a customer service representative, this is especially advantageous. Waiting might be a frustrating experience because people are used to getting instant responses, much like when they search for something online.
3) Easily available
Customers should never hesitate to contact a financial institution if they have a question regarding their money.
The good news is that routine inquiries and financial services can be automated and offered whenever needed. It will only improve over time thanks to machine learning and artificial intelligence.
4) Smooth Flow
It's as easy as saying the client's request out loud or typing it in to get a prompt response.
More times the customer participates in the conversation, fostering loyalty and increasing openness to new opportunities (aka your commercial offers).
POV: Bank Side
1) Operation cost
Banks can lower their operating expenses with the aid of conversational AI. Numerous use cases for conversational banking point to significant cost savings because there is less of a need to extensively train human customer service representatives to be able to handle more complicated transactions.
For instance, TitanCS has automated 60% of written contacts and about 40% of all incoming contacts.
2) Customer’s behavior insights
Big Data analytics has made this possible by giving the bank insights into the preferences and decision-making processes of its customers.
Financial institutions can use conversational AI solutions to offer pertinent promotional offers and suggestions in real time without a human customer service representative's involvement.
Industrial example of conversational AI Banking
1) Self-Learning ChatBots
Several larger banking institutions find a self-learning AI chatbot to be especially helpful. When a customer interacts with this proactive virtual assistant, it first ascertains their specific issue and either offers a solution or refers them to the proper support personnel. Additionally, it can offer interactions in multiple languages, geographical directions, and other location-based services.
2) Conversational IVR
Conversational IVR prioritizes urgent cases and automatically resolves customer issues. Customers typically have to wait over 2.4 minutes on the phone before speaking to a live customer service representative.
Customers can only begin to describe their problems after waiting for such a long time. Customers can use MindTitan's Conversational IVR to ask questions in their own words and receive answers automatically without the help of a human agent by using only the most cutting-edge speech recognition software and machine learning technologies.
The trend is clear: in order to compete with fintech, the legacy banking sector
must incorporate Conversational Banking solutions in effective customer service to give customers a better experience. Costs are decreased, customer satisfaction and loyalty are dramatically increased, and human errors brought on by emotional states of mind are eliminated when using AI-powered Conversational IVR and chatbots. Making the process work could be difficult, so picking the right technology partner is essential.
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