BNP Paribas Cardif automates 66% of inbound calls using callbot

Channels

Call centre

Industry

Insurance / Banking

BNP Paribas Cardif is the banking insurance leader in 35 countries with 100 million customers worldwide

Background

The company's hotline constantly buzzes, so one would assume that only a human agent could work with clients from all over the world. Yet, the company chose to automate calls with the help of conversational AI due to the prevalence of standard inquiries.

Cardif's call centre used to operate 14 hours a day, while the work of the hotline agents was deemed inefficient.

Not all customers were able to wait in the long queue for advice on critical/vital issues. Typically, agents spend half of their shift answering common questions such as “where can I find your office?” or “how do I get a payout?”.

Goals

The main goal was to help the clients of Cardif to get information faster and to reduce the burden on call centre agents

Respond to customers in loss events swiftly

Increase percentage of requests solved at the first call

Automate the process of handling common questions

Solution

1The Cardif team analysed dialogues with its customers to identify the 50 best conversation topics
2They then came up with 15-20 key phrases for each topic, having added the assistant's answers and a few friendly phrases
3For a month and a half, Cardif was discussing whether its voice assistant should be a cartoon character or a real employee with a profile pic

Cardi bot sends key takeaways via email or text messages, while in complicated cases it transfers the call to the agent

We taught the callbot to answer common questions about the company, insurance payouts, working hours, and website navigation.

Alex Lartey

Co-founder of Tovie AI

How can Cardi help?

The Cardi bot had to be in line with the brand philosophy, be polite and friendly like a real insurance specialist

Respond to customers in loss events swiftly

Increase percentage of requests solved at the first call

Automate the process of handling common questions

Results

52%

Call containment

70%

Reduction in call waiting time

$9m+

Saving in operational costs over two years

Today, the FCR is estimated at

83%

As a result of the automation, the call center agents can now focus on higher-value tasks.

Cardif uses the FCR (First Call Resolution as a percentage of requests solved at the first call) metric to estimate the robot’s efficiency. If the customer does not call back within 24 hours after talking to Cardi, then the conversation may be considered successful.

Performance evaluation

83%

of NPS surney participants gave the highest rating to the company and its automated services

Cardif regularly conducts NPS surveys to estimate an index of customer brand loyalty

A recent survey showed that 52% of customers are willing to recommend the company to their friends and acquaintances. Moreover, 83% gave the highest rating to the company and its automated services.

Before Cardi, the NPS survey was conducted by two employees. Following the success of Cardi's robot, Cardif decided to do a similar project for outgoing calls. Now, another robot assistant, Cardi's colleague, conducts the surveys.

The assistant communicates with 400-500 customers each month and approximately 40% of them agree to take part in the survey

The effectiveness of the survey was lower when the calls were handled by company staff. Cardif plans to teach Cardi to answer questions on contract management and amendment.

The effectiveness
of the survey was
lower

when the calls were handled by hotline agents

The head office of BNP Paribas Cardif in Paris was also pleased with the results of Cardi's work.

Soon, Cardif plans to scale the adoption of conversational AI technology to all of its offices with Tovie AI

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