Problem / Objective:

Recently, ICICI Bank began to use software robotics in their banking operations to reduce the response time and to improve efficiency. However, a section of the bank's customers is still unconvinced about the automation tools, often leading them to reach out to the bank with numerous queries, especially when money is remitted from international locations. As a result of the high influx queries, the average time taken for responding to them increased to 12 hours, negatively affecting customer satisfaction. 

Solution / Approach:

To overcome this challenge, the ICICI Bank introduced an AI engine that was developed using machine learning, NLP, and cognitive computing tools. The engine process queries from customers using text analysis and semantic analysis. The use of cognitive tools helps the bank's system to understand the query, process the query, and solve the issue through the bank's interface and revert to customers with the right solutions. The use of machine learning allows the engine to self-learn the querying processing and to provide better results to its customers.

Impact / Implementation:

With the use of this AI engine, the bank is now able to optimize its remittance operations and can respond to queries in real-time. Also, the bank has started to use this AI engine in document scrutiny process using optical character recognition.