Synthetic Data
in Finance
Discover the benefits of using synthetic data in finance
Finance industry
Banks
- 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
Insurance
- 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
FinTech
- 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
77%
of financial institutions afraid of losing competition without leveraging Big Data
$4.88m
is the average cost of a data breach in 2024, the highest on record
9.5%
Improvement of utilization of resources is estimated due to a data ecosystem
60%
is unable to use more than 40% of their data
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.
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
Ensures compliance with data privacy regulations by minimizing the use of real personal data, without hindering developers due to synthetic data.
Proud winners of the Global
SAS Hackathon
We are proud to announce that Syntho won in the healthcare and life sciences category after months of hard work on unlocking privacy-sensitive healthcare data with synthetic data as part of cancer research for a leading hospital.
Case studies
Explore real-world success stories from our clients.
Do you have any questions?
Talk to one of our experts
Why Syntho?
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
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data guide now
What is synthetic data?
How does it work?
Why do organizations use it?
How to start?
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