Case
Our client is one of the thirty largest banks in Indonesia.
The bank has been operating since 1990. The head office of the bank is located in Jakarta, but the branches are opened around the country. It is in the TOP-10 of the largest banks and the TOP-20 most reliable credit institutions of Indonesia.
This bank regularly processes a large amount of low-conversion traffic such as loan applications which were made through the form on the bank’s website. Potential clients make around 17500 such applications per a week.
Problem
Previously, the bank delegated the application processing to an outsourced call center. The call center operator spent about 15 minutes calling potential clients. It took a lot of time to reveal clients who are really interested in the bank's services - and are interesting for the bank as well.
Lately the interest on loans has increased so the number of applications is constantly growing. The bank had to hire more operators to keep the processing speed at the same level. So the cost for each application was increasing as well.
Many potential borrowers often send requests to several banks at once to get a loan for sure. They also may forget about their application. So the bank needs to remind clients about itself to save the promising applications.
Task
Analyzing the incoming traffic and verify applications through the bank minimum requirements to reveal targeted clients. The process should be fast and cost less than call center services.
Solution
Effebot team offered to automate the processing of applications which are received from the bank’s site.
Experts developed a script which would take into account possible objections from a potential client. For this purpose, experts set up voice recognition in the script: if a client asked who’s calling, the robot automatically notified him that it was this bank. After the confirmation from a client the robot continued the dialogue.
The voice recognition is also used for verification. The potential client had to answer 4 questions to confirm he was solvent.
After an interview was over, verified clients were transferred directly to a call center operator. It has become possible thanks to the integration between the bank information system, the Effebot service and the call center telephony during the collaboration.
What was automatized?
Processing of applications which comes from the bank’s website
Verification of potential clients in compliance with the bank requirements
Transferring verified clients to the bank’s operator
Result
17 500
calls were made in a week
67%
potential clients answered the questions
9%
potential clients met the bank’s requirements
2-3 min
one call lasted
The robot significantly reduced cheap traffic processing time: one conversation lasted around 2-3 minutes or less instead of 15 minutes before. The robot was able to make 25 more calls per hour than the call center operator.
Such optimization of pre-sale processes had a positive effect on the interest of potential customers and increased the loyalty of the actual ones.
Effebot team proved that the processing of incoming applications or other monotypic tasks can be easily automated by a robot. Now operators receive only profitable applications from real borrowers who will be able to fulfill their obligations to the bank.
The robot reduced cheap traffic processing time by 5-7 times and saved the budget of our employer.
Our client’s feedback
“Thanks to proactive thinking and flexibility in solving tasks that needed to be implemented in a short time, the Effebot team showed its high competence and efficiency. They followed the market trends and offered us the best solutions. Thanks to it, we can process our customers' requests faster and better. I think that voice robots are a great tool to reduce costs and improve your performance. Best of luck to Effebot!“
NETVANA TELESMS PRIVATE LIMITED
4th Floor, Flat No. 28/A, FO-02,
80 Feet Road, Michael Palya,
Bengaluru, India
