Automated Vehicle Registration Verification for a Leading Indian NBFC
Technology Category
- Application Infrastructure & Middleware - Event-Driven Application
- Robots - Autonomous Guided Vehicles (AGV)
Applicable Industries
- Automotive
- Telecommunications
Use Cases
- Leasing Finance Automation
- Vehicle Performance Monitoring
About The Customer
The client is an Indian Non-Banking Financial Company (NBFC) engaged in consumer finance businesses. Their services include two-wheeler loans, loyalty customer loans (top-up loans for existing customers), loans against property, and commercial lending. They serve millions of customers across the country who require vehicle loans. The client was seeking to improve their loan processing efficiency and accuracy by automating the process of collecting and validating vehicle data.
The Challenge
The client, an Indian Non-Banking Financial Company (NBFC), was facing challenges in processing vehicle loans for millions of customers across the country. Before disbursing the loan, the client had to hypothecate the vehicle, which required detailed information about the vehicle. This data had to be manually fetched from government websites and applications, a process that was not only time-consuming but also prone to errors. This manual process reduced the overall productivity of the employees and increased costs. The client was seeking a solution to automate the process of collecting data and registering vehicles to increase overall efficiency.
The Solution
Datamatics, a technology company, studied the entire process and implemented a first-of-its-kind mobile automation solution. They integrated their proprietary Robotic Process Automation (RPA) solution, TruBot, with the mobile application using the APM server. This cleared the existing backlog within a few days. The bot automatically captured the relevant vehicle data from the website and the application and validated the data against the customer's name before disbursing the loan. This automation significantly reduced the turnaround time and the risk of errors in the loan processing.
Operational Impact
Quantitative Benefit
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