In today’s ever-evolving regulatory landscape, having your data at risk is probably the worst nightmare for any organization. With stringent regulations and data sprawling across on-premises and cloud services, data is constantly at risk.
Data is often called ‘digital gold’ and ‘an organization’s strategic asset.’ However, if data is at risk, it can quickly become a liability. Additionally, data security incidents, particularly data breaches and cyberattacks, have become all too common in recent years.
In the third quarter of 2024, 422.61 million data records were compromised in data breaches, affecting millions globally. IBM’s ‘Cost of a Data Breach Report 2024’ report indicates that each data breach costs businesses an average of $4.88 million worldwide, with 1 in 3 breaches involving shadow data. Perhaps the most concerning is that by 2026, cybercrime will cost the global economy more than $20 trillion.
These unsettling statistics demonstrate the crucial need for organizations to implement robust data risk management procedures to protect their data. According to Gartner Research, data risk assessment is core to robust data security governance. The research further indicates that security and risk management managers must conduct data risk assessments to identify and mitigate critical privacy and data risks.
This guide dives into the core of data risk, data risk management, the need to prioritize data risk management, best practices, and how Securiti helps.
What is Data Risk?
Data risk refers to the potential for businesses to encounter unintended data loss, mishandling of data, unauthorized access, data corruption, or data exposure that can jeopardize data quality throughout the data lifecycle and the organization’s business activities, reputation, regulatory compliance status, etc. Over the years, data risks have significantly evolved. Today, they can be categorized as:
- Internal negligence where data is at risk due to poor data governance, misconfiguration, or human error, and
- External threats where data is at risk due to the evolving nature of cyberattacks, the increasing number of data breaches, and rogue insiders who engage in leaking data.
A single unsecure data point can escalate data risk across the organization, rendering data vulnerable across the entire data lifecycle. It isn’t limited to third-party vendors, but also to malicious threat actors, internal personnel, and even automated systems that mishandle data.
What is Data Risk Management?
Gartner defines risk management as the management of granular business risks between the security governance and enterprise risk management layers.
Similarly, data risk management is the holistic approach of identifying, categorizing, and assessing data risk vectors, and implementing necessary controls to minimize data risk. Data risk occurs due to data exposure. Organizations must analyze the parameters when collecting, processing, and sharing data to understand where risk is present and proactively adopt security measures to minimize, contain, or eliminate data risk.
Why Should Businesses Prioritize Data Risk Management
When organizations fail to manage data risk actively, they risk exposing their data assets to a wide range of threats, including cyber attacks, reputational damage, and regulatory noncompliance penalties, making data risk management core to an organization’s cyber defence strategy and an imminent priority.
In such an event, organizations risk not only their data assets but also their business continuity, reputation, and financial resources. This is primarily because evolving data privacy laws are in place worldwide. With GDPR, CCPA/CPRA, and several others heavily regulating organizational practices, prioritizing data risk management is no longer a choice but a regulatory requirement.
Additionally, data silos containing unstructured data pose a serious threat to an organization’s data risk management posture. A study by Experian estimates that 40% of business-critical data resides in silos. Furthermore, ResearchGate study reports that roughly 70% of organizations have data silos in more than 50% of their business units.
This increasing number is a stark wake-up call for organizations to prioritize data risk management, enabling businesses to systematically identify, assess, and mitigate vulnerabilities across data ecosystems—whether on-premises, in transit, or in the cloud.
Causes of Data Risk
There are multiple reasons for data risks, including:
A. Evolving Threats
Cyberattacks and cybercriminals are evolving and improving their strategies targeting sensitive data.
B. Human Errors
Humans are the weakest link in the cybersecurity chain, with research showing human error is responsible for an overwhelming majority of successful cyberattacks.
C. Poor Data Governance
Inadequate or absence of governance controls and policies leads to irregularities and unreliability in organizational data security, privacy, accuracy and accessibility practices.
D. Data Mismanagement
Mishandling data across its lifecycle, particularly at rest and in transit, can expose data to vulnerabilities.
E. IoT Vulnerabilities
Connected devices often lack built-in privacy and security safeguards, leaving millions of smart internet-enabled devices vulnerable to attacks.
F. Inadequate Data Security
Lack of familiarity with state-of-the-art security measures, weak encryption, legacy models, and nonsecure access controls leaves data susceptible to attacks.
G. Bad Patch Management
Patches contain the upgrades required to fix vulnerabilities. Failure to auto-update to necessary updates exposes data to risk.
H. Continuous Diagnostics and Mitigation (CDM)
Non-automation leads to poor security posture, and inadequate monitoring can cause significant delays in threat detection and response times, increasing the risk of data breaches.
Best Practices for Managing Data Risks
Managing data risks is crucial. Here are some industry-wide best practices each organization should adopt:
A. Conduct Regular Data Risk Assessments
Data risk assessments help analyze the security posture of an organization’s practices. Conduct regular data risk assessments to identify vulnerabilities and patch data risk exposure.
B. Strong Data Governance
Establish strict data handling policies and ensure transparency of data assets by implementing a robust data governance framework of accountability, ensuring that a designated individual is responsible for actively managing data residing in silos, shadow data, dark data at rest and in transit.
C. Access Controls
Restrict data access to authorized personnel only using role-based access control (RBAC) and multi-factor authentication (MFA). Securiti enables dynamic access control through metadata-driven policies via Data Command Graph, enabling security teams to define precise access scopes across all data types.
D. Establish Clear Roles and Responsibilities
Each individual within the organization handling data should clearly understand their role and responsibilities in obtaining, processing, sharing, or retaining data.
E. Implement Data Monitoring
Establish real-time data monitoring controls and visible pipelines that indicate where data is, where it travels, and to whom it is transferred. This will enable you to detect threats promptly.
F. Anomaly Detection
To keep data secure at all times, examine certain data points and identify infrequent events that appear suspicious due to their deviation from the known pattern of activity.
Automate Data Risk Management with Securiti
Securiti Data Risk Management automation enables organizations to intelligently monitor high-risk data and assess risk scores for every data asset, asset location, or personal data category. Key features include identifying data risk hotspots, customizing risk scores, eliminating risk blind spots and much more.
Securiti is the pioneer of the Data Command Center, a centralized platform that enables the safe use of data and GenAI. Securiti provides unified data intelligence, controls, and orchestration across hybrid multi-cloud environments. Large global enterprises rely on Securiti's Data Command Center for data security, privacy, governance, and compliance.
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