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Writer's pictureConrad Wojtan

AI-Assisted Data Security and Protection Now

In 2015, a single data breach at one major health insurer affected 78.8 million Americans - nearly a quarter of the U.S. population. The compromised data included names, birth dates, Social Security numbers, and employment information.


If you’re not already working on it, you’re almost certainly planning to:  protecting your data. Regulators, shareholders, and members require insurance companies to protect sensitive data.  Threats are growing in magnitude and sophistication every day.  Standards for acceptable safeguards are growing as well.


At PremiumIQ, we’re working with our clients on this challenge, and I’d like share a few tips.   For starters, we recommend a holistic program of data protection and governance – not a piecemeal or episodic approach that allows our clients to address the challenges head-on and grow with confidence.


The Challenge

Insurers manage vast amounts of data across multiple platforms between cloud services and on-prem systems. Business users often do not know where sensitive data resides, let alone the risk it poses to the organization if not properly managed. PremiumIQ works side-by-side with your data leaders to create and implement a strategy to identify, classify, and protect sensitive information in even the most complex data landscapes.


The Benefits

It seems that most organizations these days are past the point of needing business cases for data protection, but that’s because the cost-benefit equation is compelling and self-evident.  A data protection program:

  • Reduces Compliance Risk: Automated classification and protection mechanisms help ensure consistent compliance with regulatory requirements

  • Enhances Security Posture: Comprehensive protection across the entire data lifecycle minimizes the risk of data breaches

  • Improves Efficiency: Centralized data management and automated protection reduce manual effort and improve productivity

  • Optimizes Cost: Risk-based prioritization ensures protection investments align with actual business risks

  • Future-Proofs Your Company: Flexible framework that can adapt to evolving regulatory requirements and security threats.

 

PremiumIQ’s Approach

We’ve done this a few times.  Our holistic approach to data protection focuses on three key pillars:

  1. AI-Assisted Data Discovery and Classification 

    • Implementing AI-based automated scanning capabilities across structured and unstructured data sources

    • Developing sensitivity labels that align with regulatory requirements and business need

    • Creating a unified data classification strategy that combines automated and manual classification methods

  2. Comprehensive Data Protection Mechanisms 

    • Deploying Data Loss Prevention

    • Implementing encryption and data masking

    • Establishing architectural protection through proper data segregation

    • Securing the entire data supply chain

  3. Risk-Based Data Governance 

    • Unlocking the business context of the data

    • Prioritizing protection measures based on data sensitivity and access patterns

    • Implementing continuous monitoring and reporting mechanisms


Key Success Factors

Based on our experience, successful implementation of such programs requires:

  • Clear understanding of regulatory requirements and business objectives

  • Strong stakeholder alignment across IT, Security, Privacy, and Business units

  • Identification and selection of appropriate tools and technologies that integrate with existing infrastructure

  • Comprehensive training and change management programs

  • Regular monitoring and adjustment of protection mechanisms


Is data protection top of mind for you? It should be. PremiumIQ brings expertise in P&C insurance data to help insurers build robust protection strategies. We partner with stakeholders across your organization to create a resilient foundation that safeguards your sensitive data while enabling business growth. Contact us today to schedule a data protection assessment.

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