Synthetic data for insurance
Optimize market selection, underwriting, pricing, claims management, AI performance and increase the lifetime value of your customers with synthetic data!
Download the case study15%
Improvement in AI performance
60x
Shorter time to data
15,000
Synthetic home addresses
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 in 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.
"MOSTLY AI has demonstrated quickly how innovative approaches can benefit a group like Telefónica. This makes it all the more exciting that the start-up will help wayra to make the cooperation of other start-ups in our hub with Telefónica even smoother and more effective in the future."Florian BogenschützManaging Director of wayra
Related Content to Synthetic Data for Insurance
For insurance companies, synthetic data is the key to profitability. With synthetic data insurance providers can create new data-driven revenue streams and increase the lifetime value of their customers.
In this case study we showcase:
- how a MOSTLY AI customer established a synthetization framework
- how the framework was tailored to modeling based on privacy-risk classification and
- how synthetic data shortened the time-to-data from six months to three days!
