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Synthetic data for insurance

Optimize market selection, underwriting, pricing, claims management, AI performance and increase the lifetime value of your customers with synthetic data!
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Improvement in AI performance
Shorter time to data
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.

Related Content to Synthetic Data for Insurance

Reuters Report: The future of insurance

The insurance industry is experiencing a renaissance in Europe thanks to emerging opportunities and innovations. The insurtech market sees an amazing boom fueled by data innovations like synthetic data. The potential of data is huge, enabling data-driven product development and a complete AI transformation.

Download the report if you want to find out how insurers, reinsurers, regulators, and innovators are ushering in a new era of data-driven insurance. Topics covered in the report include:

  • Reckoning with emerging climate change risks 
  • Preventing credit card fraud with AI
  • Stress tests at the Bank of England and data quality
  • Synthetic data for digital transformation
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Three opportunities for insurers to increase their profits

When insurers apply a deep understanding of consumers and policy holders to their operations, three opportunities to generate revenue emerge.

Most industries are competitive, but few are more so than insurance. With the bundling of products, education – informing consumers that premiums are merely one indicator of value – and catchy branding, today’s insurers have come a long way in creating brand awareness and loyalty.

Even so, the insurance market is marked by razor-thin margins, aggressive competitors and fickle consumers. Here are three ways insurers can increase their profits in such a challenging environment.

  • Create a new product: What can you offer to your existing customers that you aren’t already?  What new products and plans fulfill an existing need and provide policy holders with added value?  Alternatively, how can you reach new customers, in new demographic segments and geographies? 
  • Optimize product pricing to balance risk and profitability: When engaging price-sensitive consumers, pricing new products too high can quickly diminish demand, while setting them too low immediately increases risk. Sound, strategic, data-generated pricing strategies reflect the optimum balance, one where risk and demand are calibrated in unison. But how do you identify that price point? 
  • Increase customer satisfaction and lower churn with better apps: Insurers have made tremendous gains to strengthen the user experience, but what app will make your customers’ and prospects’ lives even easier at every point in the process – from selecting the right product or plan, to making a payment or filing a claim?  How can you create customer-facing applications that make a real difference?

The answers to all of these questions can be found in the data customers and prospective customers create in their interactions every day; however, this information is often out of reach, expensive to gather, or too difficult to work with because of privacy and legal concerns. Fortunately, with synthetic data, insurers can overcome all of these issues with ease.

Synthetic data: the key to profitability for insurance companies

AI-generated synthetic data is a must-have tool for insurance companies, ready to be leveraged across a wide variety of insurance-specific use cases. Find out how to improve improve pricing and risk predictions, create meaningful and safe test data and be fully compliant with the strictest data privacy laws, like GDPR.

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Synthetic data: the key to profitability for insurance companies

Insurance providers are at the forefront of AI adoption. But as industry leaders know, data quality can determine the success of any project. They also need to consider compliance and data protection concerns.
AI-generated synthetic data negates these concerns while offering a far more effective alternative.

Learn how AI-generated synthetic data:

  • radically improves pricing,
  • provides test data for software development,
  • improves risk prediction,
  • eliminates compliance issues associated with traditional data sets and sources.

Download the guide In a time of razor-thin margins synthetic data can be the key to profitability to learn more!

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Improving home insurance pricing with synthetic geolocation data

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!
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What's your use case? Find out how synthetic data can empower your organization!

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