The world is constantly evolving; machines and AI are automating processes that humans did in the past, and the same is happening in the Insurance industry. Insurers are now under pressure to provide the best-personalized experience unmatched by machines to stay relevant. Here analytics comes into play to help you provide specific and custom services your clients need. 

  • Customer Experience

    Get a closer and fuller view of your customer by leveraging AI and Insurtech to create profitable and in-demand services that would satisfy your customers and increase your ROI.
    By using insurance analytics, you'll be able to:

    • Enhance your marketing communication and recommend products and services based on self-learning marketing algorithms.
    • Grasp the customers' contact and response history by analyzing data gathered from touchpoints.
    • Create a cohesive and engaging experience for your customers throughout their journey
    • Automate the customer experience decisions across different platforms
  • Insurance Fraud

    The best way to stop fraud is to predict when and where it could happen and fortify these areas to avoid fraudulent activity, which is done using AI and machine learning.
    By using insurance fraud analytics, you'll be able to:

    • Find fraud using FNOL and detect fraudulent attempts or actual fraud with real-time and batch data analysis utilizing AI and machine learning.
    • Detect and stop fraudsters from taking new policies at the point of policy inception
    • Empower your investigators with a tangible interface for managing the whole case process.
    • Do an intelligent data search and collection to help investigators have all the necessary data to carry out their investigation successfully.
    • Discover previously undetected fraud relationships using link analysis.
  • Insurance Risk Management

    Using intuitive insurance risk analytics and putting it in the hands of your CRO and risk professionals while abiding and adjusting short and long-term strategies and complying with regulations will help you forecast and manage high-risk situations with ease.
    By using insurance risk management analytics, you'll be able to:

    • Establish a flexible and robust risk management foundation that allows for scalability, analytics, reports, and workflows to be efficiently executed.
    • Have one platform for managing risk and finances with integrated IFRS 17/9, LDTI, and Solvency II while regularly complying with its regulation, Risk-Based Capital (e.g., ICS 2.0, C-ROSS, LAGIC), and Statutory Reporting (for US insurers).
    • Leverage AI and machine learning for building tariff models, IBNR calculations, automated reserving processes, and real-time pricing.
    • Monitor processes, sign-off on decisions, and receive real-time feedback on reserving analysis decisions.