Accelerate Innovation and Safe Data Sharing with Partners

• 分析与建模 - 机器学习
• 平台即服务 (PaaS) - 数据管理平台

• 商业运营
• 产品研发

• 数据科学服务
• 系统集成

Preparing and sharing data sets with partner organisations has long been an operational hurdle for large multinational insurers. A staggering amount of manpower is required to make it happen, with hundreds of scientists spending months on just a handful of data sets. In this way, compounding the expense and delay of data processing in an already unwieldy compliance process. Key challenges include costly man-hour requirements, with an average of 5 to 7 people required to assist with data sharing and provisioning. Additionally, there is no consolidated environment for test and training data, leading to up to 48 hours spent on refreshing test datasets shared with a partner organisation. Limited data available for tests negatively impacts model accuracy and performance. Furthermore, the long and cumbersome compliance process takes between 2 and 4 months to go through compliance approvals and data sharing agreements (DSA).

The customer is a leading insurance company that employs more than a hundred data scientists and manages 3000 datasets. The company is focused on accelerating product development and innovation to remain competitive in the market. They sought a high-tech solution to enable them to share structured datasets externally while maintaining data security. The company faced significant challenges in data processing, which historically required extensive human capital. They needed a solution that could streamline their data operations, reduce manpower requirements, and ensure compliance with legal and security standards. The company aimed to unlock high-speed product development and innovation by leveraging advanced data management technologies.

Using the Synthesized DataOps platform, the customer was able to achieve scalability and huge time savings. Millions of Synthesized data records were automatically generated in just 10 minutes, allowing the company to share data with third-party vendors for product development. The platform understood diverse data types and formats, which facilitated seamless data sharing. The solution also led to a dramatic reduction in team size and the number of touchpoints, with only one person involved in the process of data generation instead of up to seven on average. The complexity of data storage access was eliminated, as numerous isolated data storages were condensed into one platform for browsing and storing test data. The data structuring processes were streamlined, and the legal and compliance risks were significantly reduced. The Synthesized platform ensured zero exposure to compliance failures and no risk of security breaches. Additionally, the quality of test data improved, with Synthesized offering data that was of higher quality than the original dataset provisioned using manual processes. The platform provided highly accurate insights that could be shared with partner organisations. Synthesized is an AI-powered DataOps platform that automates all stages of data provisioning and curation, enabling data-driven enterprises to create new, high-quality Synthesized data scenarios for test and development purposes.

• The company saved 200 man-hours per project, significantly reducing the time and effort required for data processing.
• The team size and number of touchpoints were dramatically reduced, with only one person involved in the data generation process instead of up to seven.
• The complexity of data storage access was eliminated, as numerous isolated data storages were condensed into one platform for browsing and storing test data.

• Saved 200 man-hours per project.
• Reduced team size from 5-7 people to just one person involved in data generation.
• Generated millions of Synthesized data records in just 10 minutes.