Why do insurance companies need synthetic data?
Insurance companies have always been among the most data-savvy innovators. No wonder, since the ability to calculate risk accurately makes or breaks an insurance provider. Looking ahead, companies need to adopt sophisticated AI and analytics across their operations while staying compliant with regulations and protecting their customers data.
How can synthetic data help insurance companies?
Synthetic data is a game-changer in all things data-driven. Synthetic data can improve the performance of your pricing and fraud detection models, improve accuracy and fairness is AI models and unlock data assets hidden by privacy regulations. Realistic synthetic test data can help you serve customers, brokers and advisors with great applications, tested to perfection with synthetic user stories identical to those in production.
SYNTHETIC DATA Use cases IN INSURANCE
Improve AI model performance by 2-15%
Your fraud detection models only perform their best when they are trained on the right data. Synthetic data helps to create balanced versions of your production data that provide more granularity and depth and that make it easier for fraud detection algorithms to pick up patterns.
Improve the ROI of your insurance products
Software solutions only come to life when running on great data. Many external vendors rely on your data to deliver their services. Provide vendors ready-to-share, privacy-compliant synthetic data sandboxes to test different vendor solutions in a privacy-safe way.
Realistic test data at your fingertips
Create highly realistic synthetic test data to mirror your production data for safe, smart and cost-effective test data provisioning. Great applications begin with great data and dummy data generators will never provide you with the rich insights synthetic test data will.