Unified Data Risk Management: The Key to Reducing Breach Costs and Legal Exposure A recent Exterro Executive Playbook for Data Risk Management highlights the growing financial and operational risks of fragmented data governance, where privacy, cybersecurity, eDiscovery, and compliance teams operate in silos leading to duplicated efforts, inconsistent responses, and escalating costs. The playbook warns that cyberattacks and insider threats are accelerating, with organizations facing an average of $10.2 million per data breach in 2025. When incidents occur, companies must demonstrate timely, defensible investigative practices under regulatory scrutiny. Poorly managed data exacerbates the problem, particularly during litigation, where rushed forensic work and emergency collections can inflate eDiscovery expenses by 50% to 70%. A proactive, unified approach centered on a continuously updated data catalog can mitigate these risks. By maintaining accurate classification, shared workflows, and automated legal holds, organizations streamline incident response, reduce redundant data, and ensure compliance. The playbook also flags shadow IT as a critical vulnerability, with 71% of employees admitting to using unauthorized AI tools a factor in 20% of 2025 data breaches, per IBM. To establish defensible governance, the report advocates for cross-functional visibility, standardized processes, and real-time data mapping. Integrating breach detection with legal-preservation systems, for example, allows automatic tagging and retention of incident data, while privacy teams can use classification tools to assess regulatory exposure. The result: faster decision-making, lower breach costs, and stronger resilience under scrutiny. The core takeaway? Fragmentation in data risk management increases costs, slows response times, and weakens legal defensibility. A unified model combining technology, clear ownership, and automated workflows transforms reactive chaos into proactive control, enabling organizations to act with precision when it matters most.