Rohan Malhotra, Founder & CEO of Roadzen – Interview Series

Rohan Malhotra is the CEO, founder and director of Roadzen, a global insurtech company advancing AI at the intersection of mobility and insurance.

Roadzen has pioneered computer vision research, generative AI and telematics including tools and products for road safety, underwriting and claims. Companies like Axa, Allianz, Tata, and Audi use Roadzen to provide a better auto insurance experience to every driver on the road. Previously, Mr. Malhotra served as the Chief Executive Officer of Avacara, an enterprise software and data analytics company that provided product development services to Fortune 500 companies. Mr. Malhotra holds a bachelor's degree in engineering from NSIT, Delhi University, India and a master's degree in electrical and computer Engineering from Carnegie Mellon University where he studied AI and robotics.

What initially attracted you to computer engineering and machine learning?

I was drawn to robotics at an early age, captivated by the idea of creating machines that could perform tasks autonomously. This fascination with robotics served as my gateway into the field of computer engineering. As I learnt more, I observed that hardware can be abstracted into software and developed an interest in building systems that scale and learn. Now, we apply these ideas at Roadzen to make cars more intelligent and the legacy world of insurance dynamic and real-time.

Could you share the Genesis story behind Roadzen?

Roadzen was born out of a frustrating experience in 2015, when a friend's accident led to dealing with long delays in getting roadside assistance, several phone calls to file a claim over four and a half hours. This challenging episode sparked the application of my AI expertise towards enhancing road safety and transforming the auto insurance industry.

How does Roadzen use computer vision to assess the value of a vehicle?

Roadzen uses computer vision through its vehicle inspection and assessment platform VIA to determine the value of a vehicle. VIA employs AI, machine learning, and high-definition imaging to conduct digital vehicle inspections, overcoming the challenges associated with manual inspections, such as human error, subjectivity, and processing delays.

The technology provides a comprehensive view of a vehicle's condition by integrating real-time data and historical records. The computer vision capabilities of VIA enable accurate damage recognition and underwriting, by leveraging millions of underwriting decisions. It also incorporates fraud detection through automated analysis of patterns and user behaviors. The platform ensures high transparency with customizable access control for insurers during the inspection and underwriting process.

VIA contributes to seamless, efficient, and transparent vehicle inspection and underwriting, expediting the process while delivering reliable evaluations through dynamic reports and real-time notifications.

The same technology is used after accidents, could you discuss the process for customers and on-ground inspectors?

Roadzen's claims management technology is capable of recognizing any car part and identifying ten types of damage in less than a second, this technology significantly expedites the claims process. It shifts the claims process from reactive to proactive, triggering the claim process when an accident occurs, allowing customers to process their claims at the accident site instead of waiting for weeks.

Roadzen's automated claims platform xClaim, seamlessly engages customers and insurance carriers in an efficient claims process. Customers can swiftly report incidents through an app, providing initial visual documentation through video and images taken by the customer, or remotely engaging inspectors for accurate damage recognition within minutes. The system also incorporates fraud detection, enhancing the integrity of the claims process. The platform delivers dynamic reports and real-time notifications which expedite claims processing, while dedicated customer support ensures transparency and assistance for all stakeholders. The platform's customizable access control enhances customer experience, while creating a digital record of information accessible for future reference.

Roadzen offers real-time driver safety data, can you discuss how the AI analyzes how safe a specific driver is? How is this information then used for accident prevention?

When we combine the predictive capabilities of AI with real-time data, it paves the way for truly dynamic and effective driver safety – where the level of risk an individual to at any given moment can be assessed and alerted against.

Roadzen's comprehensive telematics suite incorporates a computer vision system that identifies driver behavior patterns. This system utilizes real time vehicle data and applies computer vision for crucial decision-making such as time to collision, accident prevention, and obstruction detection.

One of Roadzen's key innovations is distraction monitoring. With advanced face detection technology installed in vehicles, the system can discern if drivers are drowsy, distracted by their phones, or not wearing seat belts. This proactive approach can significantly decrease accidents attributed to distracted driving.

Roadzen has successfully tackled road object detection, one of the most complex challenges in computer vision. The technology can accurately gauge the distance between vehicles, a critical safety measure in preventing collisions.

While a human driver typically needs 1.3 seconds to react before an accident, Roadzen's technology can alert the driver approximately 3 seconds prior, effectively tripling the reaction time. This could potentially eradicate 60% of accidents caused by human error or distraction, marking a significant breakthrough in the insurance sector.

Roadzen's technology stack uses telematics to compile this data, create a comprehensive driver profile, and provide a dynamic quote tailored to each driver. This individualized approach enhances risk assessment accuracy and ensures fair premium pricing based on personal driving habits and conditions.

What are some of the other AI and machine learning technologies that are used at Roadzen?

Roadzen is focused on advancing AI through fundamental and applied research, with a specialized focus at the intersection of mobility and insurance. The AI Research team at Roadzen (AIR) is committed to deepening our understanding in critical areas including computer vision, generative AI, and core machine learning.  Computer vision allows machines to interpret and act on visual data, a critical function in mobility and insurance due to the rich information visual inputs provide. Additionally, we put significant effort into Machine Learning Operations (MLOps), which streamlines how our teams train and deploy models accurately and swiftly. We also use synthetic or generative AI to accelerate model training.

What are some of the challenges that the integration of AI brings to the insurance sector?

Challenges include navigating complex data structures, dealing with legacy data, and managing quality data sets from the sheer volume of data being generated. It's important to address potential issues around data privacy, security, and algorithmic bias to build trust and ensure the equitable use of AI in insurance. Development of open and responsible AI is going to be crucial to ensuring fair practices, preventing bias in AI-driven decision making, and safeguarding customer data.

Could you share your vision for the future of insurance and AI?

As the landscape of mobility transforms where a majority of cars will be connected and autonomous, AI has the potential to create a more efficient, customer-centric insurance ecosystem for connected mobility.  Predictive modeling for risk assessment, will lead to more accurate pricing and better risk management. AI and advanced analytics, will enable insurers to anticipate customer needs, personalize offerings, and improve customer experience.

With advancements in computer vision and telematics, we'll see major strides in accident prevention and improved driving behavior. This will lead to fewer claims, reduced costs, and safer roads.

Automated damage assessments will streamline the claims process, making it quicker and more objective. AI will also transform underwriting by making it faster and fairer, by assessing risk more accurately and eliminate human bias. And we are working to ensure that this future is built on responsible AI principles.

Thank you for the great interview, readers who wish to learn more should visit Roadzen.