Synthetic data in finance
Discover the benefits of using synthetic data in finance
Finance organizations and the role of data
Data takes a crucial role in the finance industry, driving informed decision-making, risk management, customer insights, and regulatory compliance, while enabling innovation and efficiency through data-driven strategies and solutions. Synthetic data usage offers financial organizations a privacy-preserving solution to enhance risk assessment, fraud detection, algorithm training and software development. By creating realistic yet synthetic datasets, financial institutions can optimize decision-making, improve regulatory compliance, and develop innovative strategies without compromising sensitive customer information.
Finance organizations and the use of synthetic data
- Improve fraud, anti-money-laundring and anomaly detection models
- Accelerate open banking and enterprise data-sharing with stakeholders
- Implement data-driven innovation
- Assure regulatory compliance with stringent data protection regulation
- Personalized customer insights based on high-quality synthetic data
- Test data for digital banking products
- Secure collaboration and data sharing
- Ease secondary uses of insurance data
- Accelerated product development with the use of synthetic data
- Reducing the time-to-market
- Regulatory compliance with data protection regulations
- Secure algorithm training by maximizing the data and minimizing the privacy
Case studies
Why do finance organizations consider synthetic data?
- Stay ahead of the competition. Solutions that allow financial organizations to utilize data smarter will enhance the competitive position.
- Reduce time-to-data. Synthetic data accelerates access to data by minimizing risk assessments, internal processes and bureaucracy related to data access requests.
- Ambition to innovate with data. The ambition to innovate with data is significant in the financial sector. Synthetic data will accelerate the realization of this ambition.
- Ensures compliance with data privacy regulations by minimizing the use of real personal data, without hindering developers due to synthetic data.
Why Syntho?
Syntho has extensive experience working with financial organizations
Experience working with financial organizations
Extensive project involvement with international banks, insurance companies, and fintech organizations
Time series data
The platform supports time series data (typically relevant for transaction data, market data, investment data, event data etc.)
Upsampling
Syntho supports upsampling, that allows users to generate more data in case of limited data, typically used in the field of fraud detection and anti-money-laundering
Do you have any questions?
Talk to one of our finance experts
Proud winners of the Global SAS Hackathon
Winner of Global SAS Hackathon in the Category Health Care & Life Sciences
We are proud to announced that Syntho won in the healthcare and life sciences category after months of hard working on unlocking privacy-sensitive healthcare data with synthetic data as part of cancer research for a leading hospital.
Data is synthetic, but our team is real!
Contact Syntho and one of our experts will get in touch with you at the speed of light to explore the value of synthetic data!