InsurTech4Good Weekly Newsletter – #17, 2025
Hello to everyone and regards from sunny London!
This week, we dive into the fundamentals of the Financial Data Access (FiDA) proposal, insurers' readiness for scaling Generative AI, regulatory approaches to AI innovation, the growing importance of synthetic supervisory data, and a fresh initiative from Hong Kong to foster GenAI in finance.
Hope you enjoy the read!
— Andres
Financial Data Access (FiDA) – Back to Basics
Last week, I tried something new and wrote several short posts about FiDA.
I started with an overview of FiDA, covered its scope, potential use cases, and finally explored how wider access to data can help overcome complexity in insurance.
Insurance and Gen AI
Are insurers really ready to scale Gen AI?
Deloitte's latest survey shows there are still big gaps.
But with the right focus on resources, responsibilities, and returns, insurers can move faster from pilot projects to real-world use.
Read more here.
Finance Meets AI: Considerations for Public Authorities
CGAP proposes in its recent blog post three key considerations that could enable regulatory authorities to proactively support the responsible use of AI in finance:
- increased coordination across broader policy domains
- iterative engagement with multiple stakeholders
- enhanced adaptive regulation.
This comprehensive approach could help mitigate AI risks and unleash its potential for financial inclusion.
Read more here.
Synthetic supervisory data
In the processes of analysis and decision-making related to financial products, data-driven statistical and machine learning models are being used with increasing frequency. One of the main challenges in the development and training of such models remains the same - the issue of data quality and quantity.
As part of the research into this issue, the National Bank of Georgia, through the involvement of its Financial and Supervisory Technology Development Department, is actively generating synthetic data using machine learning models and generative algorithms (Generative Adversarial Networks). The generated data has been successfully used for various tasks involving the hackathons.
Synthetic data is one of the most widely used methods in Privacy Enhancing Technologies, which allows for data sharing without the risk of disclosing real information or breaching confidentiality. This data only retains the statistical characteristics of real data, which is particularly important and valuable for statistical and machine learning models during their training and development stages.
In order to promote the development of financial technologies, support innovative ideas, and encourage competition in this field, the National Bank of Georgia is ready to cooperate with interested parties and, upon justified request, provide access to synthetic data.
Within the framework of this initiative, both regulated and non-regulated entities will have the opportunity to use synthetic data-generated based on real data sources-for the purpose of testing their ideas, including the training and development of various statistical and machine learning models.
Read more here.
The Hong Kong Monetary Authority (HKMA) launched second cohort of GenA.I. Sandbox
The Hong Kong Monetary Authority (HKMA), in collaboration with the Hong Kong Cyberport Management Company Limited (Cyberport), announced today (28 April) the launch of the second cohort of the Generative Artificial Intelligence (GenA.I.) Sandbox initiative.
The GenA.I. Sandbox aims to provide a risk-controlled environment to develop and test innovative solutions using artificial intelligence (A.I.), further advancing the adoption of A.I. technology in the financial sector.
Following the positive responses received in the inaugural cohort started in January this year, the second cohort will continue to focus on use cases that further enhance risk management, anti-fraud measures and customer experience.
Read more here.
Thanks for reading!
If you're navigating InsurTech regulation, policy, or innovation—and think I can help—don’t hesitate to get in touch.
📬 Subscribe to my newsletter here
📌See how I can help you here
🔗 Follow me on LinkedIn
📧 andres@insurtech4good.com
Member discussion