Data Transformation

Transform your data to capitalize on innovations like AI, Machine Learning, New Product Development, or Data Monetization.

Unlock Your Data's Potential

There are valuable insights within data, but the sensitive nature of your data makes it difficult to ‘monetize’ data with confidence. Facteus has helped over 1,000 financial institutions safely transform their sensitive data, extract key insights, and drive new product and revenue opportunities, while complying with strict data privacy regulations.

Synthetic Data is the Key

Insights available within your data can deliver a distinct competitive advantage. However, how can you effectively extract actionable insights, while ensuring that sensitive personal information is protected, not shared, or put as risk? With synthetic data you have the right fuel to safely drive your innovation engine.

Safe, High-Quality Data to Drive Innovation

Synthetic data is the future of financial technology innovation and safe for organizations to use now. Facteus’ Mimic synthetic data application transforms raw, sensitive data into safe, privacy-compliant synthetic data for deeper insights or product innovation. This transformed, synthetic data is compliant with all regulatory and privacy laws (i.e. GDPR, CCPA, GLBA) and safe to share with trusted third-parties.

What is Synthetic Data?

Synthetic data is an artificial data set that mimics the original data; however, it removes the personal or other sensitive information contained in that data. Raw data is run through special algorithms and generators to create new data sets that cannot be traced back to the original consumer or transaction. Every data field in the synthetic data is changed in ways substantial enough to ensure that reverse engineering is impossible, but in ways subtle enough that the synthetic data is reliable and statistically-viable for planning, analysis and reporting purposes.

Synthetic data is used today in many different industries to drive greater insights into research, prototyping, testing, and optimization while protecting the identities and personal information of consumers.

Technology

Google used synthetic data to remove or infer motion blur and dynamics in photos. Self-driving care companies use synthetic data generation to train driving algorithms over larger driving distances.

Science

Volcanologists used synthetic data to drop false positives of predicted eruptions from 60% to 20%. A wind turbine company used synthetic data to better predict wind speed for renewable energy projects.

Healthcare

During COVID-19, synthetic data was used to help predict infections and hospitalizations. HealthTech Companies use synthetic data to model cancer research without revealing patients’ identities.

Synthetic Data for Financial Services

For financial services companies looking for ways to unlock the power and value of their sensitive data, Facteus’ Mimic™ Synthetic Data Engine provides a way to turn raw data into valuable insights. Unlike other data technologies, Mimic moves beyond the process of simply trying to anonymize or “clean” the data. Instead, it creates synthetic data that maintains the statistical value of the transactional data, while removing relevant personally identifiable information (PII) that could be traced back to the original raw data.

Key Use Cases and Benefits of Synthetic Data

Privacy Data Protection and Security

Organizations can help safeguard the authentic personal data they maintain and meet their privacy and data security regulation obligations (i.e. GLBA, CCPA, GDPR). When synthetic data is used, authentic data doesn’t need to be shared internally or disclosed externally. This reduces the potential for a data security incident and minimizes the need for authentic data. With Facteus’ Mimic, raw data never leaves your firewall, ensuring that personal information is protected.

Read our White Paper - Data Monetization and Compliance can Co-Exist >

Product Innovation

Financial data assets are difficult to access and, even if you can, the data is too raw to effectively derive key insights or drive analytics. High quantity and quality of data is required to enable data-driven innovation. Synthetic data makes it possible to expand usage of your data and Facteus’ enrichment services provide an opportunity to clean, enrich, and enhance your data to unlock its full potential.

Learn More About Data Enrichment >

Capitalize on Cloud Technology

Synthetic data enables organizations to be comfortable migrating their data to the cloud to capitalize on the computing power and the latest technologies available in this environment. Access to machine learning, artificial intelligence, and analytics tools streamline time-to-market and create a competitive advantage. Using synthetic data, innovation labs and product groups can share financial data and collaborate on new innovations and segmentation strategies in a public or hybrid cloud environment using statistically-relevant insights.

Learn More About Cloud Migration >

Data Monetization

For companies looking for new revenue streams, synthetic data provides a safe and secure way to monetize financial data assets without putting privacy at risk. Synthetic data provides a safe way to unlock the “Truth” of data insights without compromising data privacy regulations. Facteus parters with over 1,000 organizations today to monetetize sensitive data and open up new revenue streams.

Learn More About Transaction Data Insights >

Aite Group Impact Brief: Facteus - Changing the Game With Synthetic Data

This Impact Brief from Aite Group highlights Facteus’ Mimic and Data Platform products and the value potential for financial insitutions, payment companies, and fintechs in leveraging synthetic data for internal analytics, competitive benchmarking, and data monetization. It is based on conversations with Facteus and a selected U.S. client, supported by third-party research.

Synthetic Data and the Cloud - Data Monetization and Compliance can Co-Exist

Financial services organizations over the years have made considerable investments to leverage data science in a way that improves business processes and optimizes go-to-market strategies. However, there is significant risk in using raw data for these and other purposes. An opportunity has emerged for companies to safely expand how they leverage their data and maximize the potential to create new revenue sources by adopting synthetic data for both data transformation and data monetization initiatives.








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