Our client is a leading Indian bank and has hundreds of branches nationwide. The bank serves private and corporate customers in tier 1 and tier 2 cities in India. They aim to extend their services to rural areas and to the self-employed and is consistently adding more branches to its portfolio.
Increasing customer base required to either add more bank resources in the market or to devise a system to enhance the productivity of existing resources thereby increasing the market share. The bank chose to optimize their existing resources and increase their efficiency to provide banking assistance to more and more customers across India.
An innovative idea to provide doorstep banking services to customers and increase market reach
The bank aims to provide easy financial assistance to their customers in a scalable manner. The possibility of improving its customer service and increasing market penetration opened up with the idea of ‘Doorstep Banking’ – an uber-like on-demand banking service to their customers right at their homes.
Their idea to provide doorstep banking services to customers required mobilizing an army of in-field financial consultants. The bank was previously relying on a manual allocation to manage their field operations. It led to a huge backlog of banking assistance to customers, missed service requests, inefficient use of the field agents, and sub-optimal customer service.
To overcome these operational challenges, they identified the need for a system to increase the agents’ productivity, automating their job scheduling and thereby freeing them up to cater to more customers in a day.
Developing an intelligent solution to optimize end-to-end field operations
The bank partnered with Persistent to develop a solution on Dista, the partner company’s own location intelligence platform to orchestrate the following:
- Customers raise service requests to book doorstep banking services through a web or mobile app
- Dista’s scheduling and routing engine assigns the requests to the closest available financial agent based on requested time for the service, skillset of the agent, type of request and other parameters
- The location intelligence platform assigns the request to the financial agent on their android devices
- Financial agents arrive at the customer location to execute the service request
As a Google Maps and Google Cloud Partner, Persistent designed the doorstep banking solution on the Google Cloud tech stack. The solution uses Google Maps APIs including Distance Matrix, Directions Service, Maps Javascript API V3, and GeoCoding API and Google Cloud products like – App Engine, Datastore, Firestore, Cloud Storage and BigQuery.
Cost-effective, quick-to-market development
The solution is built on a fully managed platform – App Engine, hence it requires minimal management. The bank saves costs with the reduced efforts that would have been required to develop and maintain the infrastructure.
Automatic scaling, high performance
Since Datastore is built for automatic scaling and high performance, it perfectly fits in with App Engine to serve as the database for the solution.
Seamless integration with current systems
The solution was integrated with their existing banking portal through a service framework with pluggable components. ‘Rest Based Services’ facilitate communication between the app and the system, and an ‘Enterprise Communication Middleware tool’ enables external service integration.
Real-time dashboarding and reporting
Their operations teams track, monitor, and react to the daily in-field operations and exceptional scenarios through real-time dashboarding on Firestore. The dashboards help in creating exhaustive reports for the services rendered.
Data Security
The bank’s customer data is extracted from the bank portal and is erased from the memory after use, and is not stored on Datastore or BigQuery.
For the next phase, the financial agents will be able to accept and serve intergrid jobs, against the current provision where an agent can serve only his assigned grid. The bank has been using the solution for more than three months and has reported increase in agents’ productivity, fall in operating costs and service delays.
