Artificial Intelligence in Insurance | Inaza.com

1. Multi-Use Policy Provide tailored policies for multi-use and multi-driver scenarios WEB: WEB: ADDRESS: Business Centre, NCI, IFSC, Dublin 1, Ireland sales@inaza.com

2. Market Demand Be ready for Vehicle-as-a-Service The next era of vehicle ownership will require smarter and more personalized insurance 10% $22B of new vehicle registrations for private and corporate customers to be subscription- based by 2025 in new annual auto financing which is up for grabs by new players Superior customer experience and a convenient digital journey are expected by today's mobility customers. D E L O I T T E[ 1 ] B2C to B2B Vehicle usage and ownership is changing - creating new opportunities Personalization Contextual policies unlocks the high level of personalization that customers want 80% New digital technology allows a direct, real-time connection between supply and demand for mobility. [...] offers more comprehensive, bundled packages and fosters new value propositions in the area of car-sharing and private rental cars of customers are craving personalized offers 77% are willing to trade their behavioral data in exchange for lower premiums and quicker settlements The connected car allows insurance companies to increase overall profits by offering value- added services R O L A N D B E R G E R[ 2 ] D A T A A R T[ 3 ] 1. 2. 3. Deloitte - Vehicle as a Service - https://www2.deloitte.com/de/de/pages/consumer-industrial-products/articles/vehicle-as-a-service.html Roland Berger - Rethinking motor fleet insurance - https://www.rolandberger.com/publications/publication_pdf/roland_berger_motor_fleet_insurance.pdf DataArt - How Insurance Companies Can Adopt Personalization in 2021 - https://www.dataart.com/en/blog/how-insurance-companies-can-adopt-personalization-in-2021 I N A Z A . C O M

3. Solution CONDITIONAL RENDERING Our app can alter the end user experience depending on the active policy EXAMPLE Shared Mobility We are working closely with car manufacurers on the future of mobility called "Vehicle-as-a-Service". This involves multiple UBI and temporary policies to create a multi-driver, all-in-one vehicle monthly subscription model. RISK DATA CAPTURE Capture behavior and environmental risk data to see hidden risks We make it easy to provide tailored insurance for vehicles used in multiple environments. DATA CAPTURE Manage claims, emergency callout, billing and more - all from the app TELEMATICS Automatically collect telematics data - all from a phone with minimal data and battery usage CONTEXTUAL POLICIES EXAMPLE Create different pricing structures depending on how the end user is using the vehicle, eg. UBI for multiple taxi drivers Usage-based insurance for a shared taxi Multiple polices can be tied to a single vehicle that price depending on what driver is using it. This leads to the safer drivers being rewarded and dangerous drivers being made aware of unsafe behaviors. EMBEDDED INSURANCE A usage-based pricing model can be applied so if a driver misses a days work, they do not have to pay insurance. We can embed our solution into existing taxi, delivery and mobility apps This directly links the users costs with revenue - improving the customer experience by giving them flexibility and transparency into billing I N A Z A . C O M

4. Platform & Pricing AI RISK COMPOSABLE PLATFORM If you see a new gap in the market, there is no more setup needed. You can create a new product in days, not months. Our AI environmental risk will shine a light on predicted likeliness and severity of collisions. DATA PLATFORM SUPPORT Our 3-layer data platform will encourage you to create the new data-centric products of the future. We provide continuous support and new features are constantly rolled-out. EASE OF INTEGRATION Get in touch with Sales sales@inaza.com We work with you on setup and on a rolling basis to integrate with your existing infrastructure. As the platform is composable, we can complete a phased rollout of features so no single integration point is a blocker for deployment. I N A Z A . C O M