Transform Banking Ops with 4M+ AI Conversations

About the Client

The customer is the largest commercial bank in India with a vast network of branches, holding a significant market share of 23% in assets and 25% in deposits and loans. This bank caters to over 450 million customers worldwide.

₹5 Trillion

Market Capitalization

$51 Billion

Annual Revenue

250,000

Employees

22,000+

Branches Globally

Business Requirements

The client wanted to transform their customers’ daily banking operations over WhatsApp instead of spending time on bank Apps, ATMs, and direct visits.
The public sector bank urged to automate most of its banking services not limited to Account statements, loan queries, Interest rates, Debit Card blocks, Stop Cheque requests, etc.
Since most of its functional operations require direct synchronization of banks’ databases, the client wanted to customize the bots into API-driven in order to deliver a real-time and immediate resolution to user queries.
The client wanted to improve its overall sales and marketing results to drive better revenue across all its banking and financial services.
The virtual bot has to be scalable, multilingual, and easily accessible for registered and non-registered users.

Solution

The Twixor team built a custom AI and NLP-powered Virtual Assistant that can be accessed seamlessly by the users on WhatsApp. The team had a dedicated server to handle the authentication and authorization of users.
In order to make the virtual assistant more secure and compliance-free, the banking bot never asks for a User ID and Password from users. It’s as simple as a handshake with the banking bot and business application.
The team built 11 static and 8 API-driven use cases. The challenge was in tackling multiple accounts linked to the same user and our team efficiently handled this by integrating with third-party client db.
Twixor team augmented a campaign builder to drive potential leads. Built a scalable campaign module since it had to reach 800K+ users through WhatsApp in a single launch.
The journey built was accessible from 3 different languages and configured keyword-driven intent. And also implemented Adaptive rich cards to improve the user journey experience.