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Development of a Customer Driving Behavior Monitoring and Accident Reporting Platform
  1. case
  2. Development of a Customer Driving Behavior Monitoring and Accident Reporting Platform

Development of a Customer Driving Behavior Monitoring and Accident Reporting Platform

zaven.co
Insurance
Financial services
Automotive

Identifying Challenges in Monitoring Customer Driving Habits and Streamlining Accident Reporting

The client faces difficulties in accurately assessing customer driving behaviors, which impacts risk evaluation, customer engagement, and claims processing. Existing systems lack seamless integration of vehicle detection, trip data collection, and in-app guidance for accident documentation, leading to suboptimal user experience and inefficient data management.

About the Client

A mid-sized insurance provider seeking to enhance customer engagement and risk assessment through telematics and digital reporting tools.

Goals for Developing an Integrated Telematics and Accident Reporting System

  • Create a branded mobile application for iOS and Android to monitor customer driving behaviors and facilitate accident reporting.
  • Develop a web-based administration panel for customer service, data analysis, and reporting functionalities.
  • Implement seamless vehicle detection using beacon technology and trip data collection via GPS to automatically start trip recording.
  • Enable real-time quality assessment of user-captured images for accident verification, including glare and blur detection.
  • Design intuitive user flows that provide context-sensitive guidance, minimizing user effort and stress during trip recording and reporting.
  • Ensure the system supports brand customization to align with client branding standards.
  • Develop APIs to facilitate communication between mobile apps, web admin panel, and backend systems.

Core System Functionalities for Telemetry and Accident Documentation

  • Beacon integration for automatic activation of trip recording when a vehicle is detected.
  • Trip recording using GPS data, with background operation even when the app is minimized or closed.
  • Historical trip browsing with aggregated scores and visual feedback diagrams.
  • Guided photograph collection during accident reporting, with real-time image quality analysis for blur and glare.
  • Context-sensitive in-app instructions and hints during data collection and reporting processes.
  • Fully branded mobile and web interfaces customizable to client branding.
  • Admin panel features including customer data management, report export, ID verification, and document printing.

Preferred Technologies and Architectural Approach

Mobile development using native iOS and Android SDKs
RESTful API architecture for backend communication
Beacon technology for vehicle detection
GPS-based trip tracking
Real-time image analysis algorithms for quality detection
Responsive web design for admin panel

Essential System Integrations

  • Beacon devices for vehicle detection
  • GPS data sources for trip tracking
  • Backend data storage and analysis systems
  • Identity verification and document management systems

Non-Functional Performance and Security Requirements

  • High reliability with background trip recording capabilities operating seamlessly in the background
  • Scalable architecture supporting increasing user base and data volume
  • Low latency communications between mobile apps and backend APIs
  • Secure data transfer and storage compliant with data privacy standards
  • Ease of use with intuitive UI/UX for users in stressful situations

Expected Business Benefits and Project Impact

The platform is expected to improve customer engagement by providing an effortless and transparent driving experience, leading to increased user satisfaction. Enhanced driving behavior data will enable more accurate risk assessment, potentially reducing insurance premiums or claims costs. Efficient accident reporting and data analysis will streamline claims processing and improve operational efficiency, with measurable improvements in user onboarding time, data accuracy, and customer retention.

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