Data Risk Management: Scope, Assessment & Best Practices

Understanding the Scope of Data Risk Management

Data is the one unavoidable constant in every modern business, so it’s no surprise that managing data risk has become a concern for organizations worldwide. Data risk management involves identifying, assessing, and mitigating potential risks to sensitive data, ensuring its confidentiality, integrity, and availability. With the proliferation of data breaches and cyber threats, understanding and implementing effective data risk management strategies is crucial to safeguarding valuable information assets.

What is Data Risk Management?

Data risk management is a combination of processes, policies, and technologies used to protect sensitive data from unauthorized access, disclosure, alteration, or destruction. You use it to assess the potential threats to the security of your data and implement measures to mitigate these risks.

Sensitive information doesn’t just belong to consumers; it could also be employee data. Data risk management practices helps you keep both customer and employee information safe from unauthorized exposure.

Why is Data Risk Management Important?

Managing data risks is very important. Without proper data governance, your business faces a higher risk of poor data, human error, and potential vulnerabilities leading to breaches.

Data breaches can result in significant financial losses, reputational damage, and legal repercussions for organizations. According to IBM’s Cost of a Data Breach Report 2021, the average cost of a data breach globally was $4.24 million. Beyond financial losses, breaches erode customer trust and confidence, leading to long-term implications for business viability.

With holistic data risk management practices, you can anticipate and mitigate these with appropriate policies and procedures. This helps you keep your business data safe and your business compliant with privacy regulations.

Common Data Risk Challenges

Data risk looks different across organizations and industries, but broadly boil down to:

• Lack of Awareness: Many organizations underestimate the importance of data risk management or fail to recognize the full extent of their data exposure.
• Complexity of Data Ecosystems: With the proliferation of data sources and technologies, organizations struggle to effectively manage and secure their data across diverse platforms and environments.
• Insider Threats: Malicious or negligent actions by employees pose a significant risk to your data and, as such, require robust access controls and monitoring mechanisms.
• Evolving Threat Landscape: Constantly evolving cyber threats, making it challenging for organizations to keep pace with emerging risks and exposures.

Types of Data Security Risks & Threats

Organizations face a myriad of threats that can have significant and far-reaching impacts on their operations, reputation, and bottom line. Some of the most impactful threats include:

1. External Threats: Cyberattacks such as malware, ransomware, phishing, and DDoS attacks launched by external malicious actors.
2. Insider Threats: Threats originating from within the organization, including employees, contractors, or business partners, who intentionally or unintentionally compromise data and network security.
3. Third-party Risks: Risks associated with outsourcing data processing or storage to third-party vendors or cloud service providers, which may introduce weak points into the organization’s data ecosystem.

Any of these can pose a threat to data, leading to data corruption and data leakage. These lead to loss of customer trust as well as financial implications for your business.

Laws and Frameworks for Data Protection

• General Data Protection Regulation (GDPR): Enforced by the European Union, GDPR mandates strict requirements for the protection of personal data and imposes severe penalties for non-compliance.
• California Consumer Privacy Act (CCPA): Similar to GDPR, CCPA grants California residents rights over their personal information and imposes obligations on businesses handling such data.
• ISO/IEC 27001: A widely recognized international standard for information security management systems (ISMS), providing a framework for establishing, implementing, maintaining, and continually improving information security practices

Data Risk Management Best Practices

• Assess Security of Data: Regularly assess your organization’s security posture to identify gaps in existing controls with penetration testing, vulnerability scanning, and security audits.
• Implement Access Controls: Enforce the principle of least privilege to restrict access to sensitive data only to authorized individuals. Use authentication mechanisms such as multi-factor authentication (MFA) to enhance access security.
• Encrypt Sensitive Data: Implement encryption techniques to protect data both at rest and in transit. Encryption helps safeguard data from unauthorized access even if perimeter defenses are breached.
• Deploy Data Loss Prevention (DLP) Solutions: Use DLP solutions to monitor and prevent the unauthorized transmission of sensitive data outside your organization’s network perimeter.
• Educate Employees: Train employees on best practices for securing data and your business network, such as recognizing phishing attempts, safeguarding passwords, and securely handling sensitive information.

Managing Risks to Cloud Data

With the increasing adoption of cloud computing, organizations are turning to cloud data risk management software solutions to secure their data assets in the cloud. These solutions offer features such as encryption, access controls, data loss prevention, and threat detection tailored for cloud environments.

Data Risk Assessments

Assessing your threats is a critical step in understanding and mitigating potential risks to sensitive and personal data within an organization. Here’s a structured approach you can follow:

1. Define Scope and Objectives:

• Clearly define the scope of the assessment, including the systems, processes, and data types to be evaluated.
• Establish clear objectives for the assessment, such as identifying threats and weaknesses, assessing the effectiveness of existing controls, and prioritizing risk mitigation efforts.

2. Identify Assets and Data Flows:

• Identify all assets within the organization that store, process, or transmit sensitive data, including your hardware, software, databases, and cloud services.
• Map the data flow across the organization and document how data moves between systems, departments, and external entities.

3. Identify Threats and Vulnerabilities:

• Identify potential threats to the security of your business information, including cyber threats (e.g., malware, phishing), insider threats, physical security risks, and compliance violations.
• Identify flaws and weaknesses in systems, applications, and processes that could be exploited by threat actors to compromise data integrity, confidentiality, or availability.

4. Assess Current Controls:

• Evaluate the effectiveness of existing security controls and safeguards in place to protect sensitive data, such as access controls, encryption, monitoring tools, and incident response procedures.
• Identify gaps or weaknesses in existing controls that may leave you vulnerable to data breaches or other security incidents.

5. Analyze Risks:

• Assess the likelihood and potential impact of identified threats exploiting vulnerabilities to compromise sensitive data.
• Use data analytics and assessment methodologies, such as qualitative or quantitative risk analysis, to prioritize risks based on their severity and likelihood.

6. Determine Risk Tolerance:

• Define the organization’s risk tolerance level based on its business objectives, regulatory requirements, and risk appetite.
• Determine acceptable levels of risk for different types of data and business processes, considering factors such as sensitivity, criticality, and legal obligations.

7. Develop Risk Treatment Plans:

• Develop risk treatment plans to address identified risks, including risk mitigation, risk transfer, risk avoidance, or risk acceptance strategies.
• Prioritize risk treatment efforts based on the severity and likelihood of risks, available resources, and organizational priorities.

8. Implement Controls and Monitoring:

• Implement recommended controls and mitigation measures to reduce the likelihood and impact of identified risks.
• Establish mechanisms for monitoring and evaluating the effectiveness of implemented controls over time, adjusting strategies as needed based on changing threats.

9. Document and Communicate Findings:

• Document the results of the risk assessment, including identified risks, recommended controls, and risk treatment plans.
• Communicate findings to relevant stakeholders, including senior management, IT teams, data owners, and regulatory authorities as required.

10. Review and Update Regularly:

• Regularly review and update the risk assessment process to reflect changes in the organization’s environment, technology landscape, and regulatory requirements.
• Conduct periodic reassessments to ensure ongoing effectiveness of controls and alignment with business objectives.

The Impact of AI on Data Risk Management

The rapid adoption of artificial intelligence (AI) has revolutionized data risk management by enabling organizations to enhance threat detection, automate security processes, and analyze vast amounts of data for anomalies and patterns indicative of potential risks. AI-powered solutions can augment human capabilities, providing real-time insights into emerging threats and helping organizations stay one step ahead of cyber adversaries.

Reducing and Mitigating Risks to Data with BigID

BigID is the industry leading platform for data privacy, security, compliance, and AI data management, leveraging advanced AI and machine learning to give businesses the visibility into their data they need.

With BigID you can:

• Know Your Data: Automatically classify, categorize, tag, and label sensitive data with unmatched accuracy, granularity, and scale.
• Improve Data Security Posture: Proactively prioritize and target risks, expedite SecOps, and automate DSPM.
• Reduce Your Attack Surface: Shrink the attack surface by proactively eliminating unnecessary, non-business-critical sensitive information.
• Remediate Data Your Way: Centrally manage data remediation – delegate to stakeholders, open tickets, or make API calls across your stack.
• Enable Zero Trust: Reduce overprivileged access & overexposed data, and streamline operations.

Be proactive with your data security approach— get a 1:1 demo with our experts today.