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How is Conversational AI and Bot Transforming the Banking and Financial Services Sector?

Nov 21, 2018 10:50 AM 3 min read
Editorial

Most decision makers in the Information Technology (IT) sector are of the opinion that the use of Artificial Intelligence (AI) in Banking, Financial Services and Insurance (BFSI) segment would lead to an increase in operational efficiency and bring about a transformation in the manner by which core financial processes are carried out.

 

In that respect, Conversational AI technology is the way to go as they facilitate two-way interaction between the banks and their customers, allowing banks to establish long term relationships with their customers by providing a seamless experience.

 

Over time, Conversational AI is likely to develop an automated response system to contextualize and personalize conversations with their customers on-demand and in real time.

 

Some major sub-segments to influence implementation of AI in BFSI sector are:

 

  1. Chatbots or Voicebots: This AI technology is programmed to converse with the customers round the clock. It is programmed to self-learn and conduct intelligent conversations with humans over chat or audio.
  2. Robo Advisors: This AI technology uses different platforms to offer investment advice to customers covering multiple issues, with zero human intervention.
  3. Emotion AI: It is a branch of AI which helps in enabling machines to detect human emotions using advanced facial and voice recognition technology. Subsequently, it makes use of this information to provide advice to the customers depending on their mood and state of mind.
  4. Data Analysis: AI systems which record multiple data points and use them to evaluate problems related to its own applications as well as to solve problems related to different areas of banking.
Conversational AI and Bot: Transforming Banking and Financial Services Sector
State of AI Deployment in Banks

 

One of the primary aspects associated with AI in banking is its ability to supercharge its customers using multiple touch points. The coming years will witness deployment of AI-oriented Chatbots and Voicebots which can interact with multiple customers using the most advanced conversation options. According to a survey of banks who are planning to deploy AI technology in the next one year, 52% have Voicebots as their top priority, followed by chatbots at 48%.

 

Some of the major Indian banks to implement these services include:

 

  • State Bank of India:  SBI’s INTouch chatbot is using AI technology powered by IBM Watson to address various customer queries. The chatbot provides information on various banking products and services like loans, term deposit and more.

 

  • HDFC Bank: The bank has introduced its own conversational banking chatbot called EVA exclusively for its customers. This AI-powered virtual assistant chatbot designed by Bangalore-based AI start-up Senseforth can answer millions of customer queries covering multiple channels.

 Conversational AI and Bot: Transforming Banking and Financial Services Sector

 

  • ICICI Bank: The bank’s in-house built iPal chatbot serves multiple customers to offer assignment on micro transactions like bill payment and fund transfer. Within a short span of time, the chatbot has handled more than 6 million queries on its portal and mobile app iMobile providing information on multiple aspects with close to 90% accuracy. The bank claims that it is the only AI-led Indian chatbot service available on the bank’s website as well as mobile application.

 

To Conclude

 

The main objective of most AI technology adopted by banks in India is to offer a enhanced, proactive and personal customer experience at a lower cost. As banks adapt themselves to these newly deployed AI systems, and frequently use them for back-end business processes, they can help reduce human error and improve turn-around-time wherever manual processes are required.

 

To know more, download our latest research paper titled Artificial Intelligence for Banking, Financial Services & Insurance Sector.

 

This article originally appeared in Nasscom Community.

 

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