TWIN processes more than 100 dialogues per day in messengers with bank customers

TWIN case

Problem

Arvand Bank, one of the largest banks in Tajikistan, offers a wide range of financial services for individuals and legal entities, including lending and deposits. Due to the large number of incoming calls, live operators could not effectively process calls.

What TWIN offered

  • TWIN developed several chatbot scripts in two languages (Russian and Tajik) and connected it to the bank's channels in Telegram and WhatsApp.
  • The main goal was to consult customers on frequent questions about the bank's services: loan processing, deposits, opening hours of the bank's branches, etc.

The scenario provides that if the bot doesn’t recognize the question, the dialog is switched to the operator. It’s also possible to transfer the dialog to the operator at the client's request, which improves the quality of processing requests.

Outcome

Currently the bot processes more than 100 dialogs per day, reducing the workload of operators. 

Кейс Arvand Bank  912px.png
Case
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