Insurers and insurtechs handle sensitive personal, financial, and health data daily. A breach can expose customers to identity theft, invite regulatory penalties, and erode trust. Compliance with global regulations like GDPR, HIPAA, and other regional laws requires robust security protocols. On top of this, cyber threats are growing, with ransomware, phishing, and data exfiltration becoming more sophisticated.
When choosing an insurtech company, you should check their ability to protect data, both to meet legal mandates and to reassure customers.
Here’s a closer look at what to look out for.
Data encryption
Encryption is the foundation of data security. Insurtechs must protect sensitive data both in transit and at rest. Using protocols like TLS, data is safeguarded from interception during transmission. Meanwhile, strong encryption algorithms ensure that stored data remains secure, even if access controls are compromised.
Access control
Proper access control ensures only authorised personnel can interact with sensitive information. Role-based access assigns permissions based on specific responsibilities, reducing the risk of misuse. Multi-factor authentication (MFA) adds another layer of security, protecting against unauthorised access even if login credentials are exposed.
Privacy by design
Privacy by design ensures data protection is integrated into every stage of development. By minimising the amount of data used and employing anonymisation techniques, insurtechs can safeguard customer information while maintaining efficiency. This reduces exposure and supports regulatory compliance.
Regulatory compliance
Compliance with laws like GDPR, CCPA, and HIPAA is non-negotiable. Insurtech platforms must demonstrate adherence to these regulations through audits and certifications. This reassures customers and regulatory bodies that data is handled responsibly.
Transparent and explainable
Regulators are increasingly demanding that AI-driven decisions be transparent and easily explainable. Insurtechs must provide clear documentation that explains how their AI processes data and reaches conclusions, particularly in automated claims or underwriting decisions.
Read more: How Sprout.ai uses AI, and what sets it apart from other AI tools
Data residency and ownership
Data residency ensures information is stored in secure centres within agreed jurisdictions, complying with local sovereignty laws. Customers should always retain ownership of their data, with clear terms on how it is used and stored. This transparency is essential for trust and accountability.
Security certifications
Security certifications like ISO 27001 indicate that an insurtech adheres to industry-recognised best practices. Regular third-party penetration testing validates the effectiveness of these measures, ensuring platforms stay resilient against evolving threats.
Proactive monitoring
Continuous threat monitoring is essential for detecting and mitigating risks in real time. Advanced detection tools can identify potential vulnerabilities or malicious activity before they cause significant harm, ensuring uninterrupted operations.
Synthetic data
Synthetic data offers a privacy-first solution for training AI models. By mimicking real-world patterns without using actual customer information, synthetic data minimises exposure. It allows AI models to learn effectively without compromising sensitive data, reducing the risk of breaches or misuse.
Large Language Models (LLMs)
LLMs play a key role in automating data preparation, such as cleaning, labelling, and generating synthetic examples. This reduces vulnerabilities associated with manual handling and accelerates secure AI training, ensuring both efficiency and safety.
Read more: 9 essential features to look for in AI claims processing platforms
Sprout.ai delivers on essential security features
Sprout.ai sets a high standard for security in insurtech, implementing all these crucial measures to protect customer data. Its multi-layered security approach protects customer data, builds trust, supports compliance, and drives innovation in the insurtech space.
Sprout.ai encrypts data in transit using TLS and secures stored data with advanced encryption algorithms.
Role-based access limits who can interact with sensitive data, while MFA ensures accounts remain protected from unauthorised access.
The platform embeds privacy into every process, minimising data use and anonymising claims data to safeguard sensitive information.
Sprout.ai adheres to GDPR, CCPA, and other regulations, with regular audits to maintain trust and transparency.
It ensures its AI models generate clear, explainable outputs. Documentation supports insurers in understanding and justifying automated decisions.
Customer data is stored within agreed jurisdictions in secure data centres. Customers retain full ownership and control over their data.
Adherence to ISO 27001 standards, along with regular third-party penetration testing, ensures a strong security posture.
Continuous monitoring and advanced detection tools protect against potential risks, keeping operations secure and uninterrupted.
Sprout.ai trains its AI models with synthetic data, reducing reliance on sensitive real-world data. LLMs automate data preparation, streamlining processes while maintaining high security standards.
With proactive monitoring processes, Sprout.ai ensures its AI systems remain aligned with regulatory requirements and ethical standards, adapting to changes as they arise.
