Paving System for India’s Core Banking
from decoding to delivering.
Airtel is a third-party software; we matched the list of messages with the SMS templates, filtered out the fraudulent messages, and let the right messages pass through our security system by adding a pre-registered ID per message. Our system identified the qualified messages that must reach the audience.
Know our Client
Airtel or say Bharti Airtel is one of the ruling global telecommunications companies. With over 403 million subscribers, 11 crore broadband connections, 99.45% active subscriber base, Airtel is undoubtedly among the top 3 telecom operators in India.
Note their Pain Points
The TRAI (Telecom Regulatory Authority of India), to detain fraudulent transactions took the initiative to pre-register all the promotional/ transactional SMS templates with a central portal and authorize only those transactions that matched the pre-registered template. The Core Banking Systems identified a need for a system that enables them to read the incoming transactions and qualify the message with the pre-registered ID.
Hear in their Solutions
A system that could identify incoming messages, compare them with a pre-fed list of templates, run a Natural Language Processing, qualifies a template that matches the existing cached list of templates, and provide an ID matching with the central portal registered with the regulatory.
Discover our Specifics
Our system could identify incoming messages, compare them with a pre-fed list of templates, run a Natural Language Processing, qualify a template that matches the existing cached list of templates, and provide an ID matching with the central portal registered with the regulatory.
We built and delivered a robust system that processes requests for more than 80 banks, identifying templates as well as processing more than 10 million requests each month with a success ratio of over 98%. Our solution had its share of unique challenges that needed us to deploy the same microservices architecture on an on-premise setup. We decided to opt for an active load balancing setup where the Core banking Systems were load-sharing income traffic of two nodes.