Managing data risks, unlocking trust and innovation

Bytes, barriers, and breakthroughs

Effective data risk management requires identifying and prioritizing the sources and drivers of data risk across an organization. However, many companies encounter significant barriers that prevent them from developing a comprehensive and consistent view of data risk and its impact on their strategic objectives and operational performance. These challenges include a lack of accountability within the enterprise risk framework, unclear ownership of data risks, limited understanding of data risks within the first line of defense, and low visibility into the adverse impact of data risks across the enterprise, among others. Addressing these challenges is crucial for organizations to manage data risk successfully.

Financial services organizations are increasingly influenced by trends in data risk management due to evolving regulatory requirements and the adoption of data-driven decision-making and emerging technologies like artificial intelligence (AI) and machine learning (ML). Key trends include:

• Regulatory scrutiny: Regulators have become more knowledgeable about data, demanding better organized, granular, traceable, and frequently collected data. Noncompliance can lead to significant penalties.
• Increased confidence in data: Leadership and consumers expect high-quality, ready-to-use data. Organizations must identify and mitigate emerging data risks to maintain confidence in their data.
• Formalized data risk management: Due to regulatory requirements, diverse product offerings, and complex operations, financial services organizations must prioritize data risk within their enterprise risk framework. This shift is moving data risk management from sporadic efforts to a more structured approach.
• Board and management visibility: Enhanced reporting and visibility into data risks are crucial for accountability and better decision-making. This includes executive views for high-level insights, business views for specific insights and accountability, operational views for monitoring effectiveness, and custom views for tailored information analysis.

These trends highlight the growing importance of data risk management in ensuring regulatory compliance, maintaining data quality, and supporting informed decision-making in financial services.

Deloitte assets to accelerate DRM

Deloitte leverages its experience and assets to help clients prioritize and accelerate data risk management initiatives, whether establishing a new program or enhancing an existing one. Deloitte emphasizes the importance of establishing baseline DRM capabilities by understanding the current maturity level of the capabilities; updating and defining data risk standards (including data life cycle phases, risk inventory, and minimum expectations); prioritizing data risk types, operating units, domains, and use cases based on current maturity levels; and creating a DRM roadmap and implementation process to mature data risk management capabilities.

Deloitte offers extensive experience and various assets to help clients efficiently achieve their data risk objectives. These assets include the Data Risk Taxonomy, Data Risk Management Operating Model, Issue Management Framework, and Data Risk Metrics Library.

Are you ready to align your data protection efforts with overall business goals?

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