What Is Sensitive Personal Information? Definition and Examples

Protecting sensitive personal information (SPI) is a critical aspect of data privacy, acknowledged by various regulations like GDPR and CCPA. Unlike basic personal data, SPI carries higher risks, including discrimination, identity theft, and financial fraud, if exposed or mishandled. This guide from GConsenteo, your expert in cookie consent management and privacy law, clarifies what sensitive personal information is and how businesses should approach its processing.

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Privacy regulations differentiate between standard personal data and sensitive categories due to the elevated risks associated with the latter.

GDPR's Definition of Special Categories of Personal Data

Under the GDPR, data considered sensitive (referred to as "special categories") includes:

Racial or ethnic origin
Political opinions
Religious or philosophical beliefs
Trade union membership
Genetic data
Biometric data (when used for identification purposes)
Health information
Data concerning a person's sex life or sexual orientation

Processing these categories is generally prohibited unless specific conditions are met, such as explicit consent, processing for public interest, protecting vital interests, or legal claims.

CCPA's Definition of Sensitive Personal Information

The CCPA, amended by the CPRA, defines SPI to encompass:

Social security numbers, driver's license numbers, and other government-issued identifiers
Financial account information and credentials
Precise geolocation data
Religious beliefs, ethnic origin, and trade union membership
Contents of emails and text messages (unless the business is the intended recipient)
Genetic data, biometric information, and health records
Information about a person's sex life or sexual orientation
Personal data collected from a known child

Consumers have distinct rights regarding their SPI under CCPA, including the ability to limit its use and disclosure, requiring businesses to implement clear opt-out mechanisms.

Sensitive Personal Information Under US State Privacy Laws

While there's no single federal privacy law in the US, many states have enacted their own regulations. Most of these laws align with CCPA's definition of SPI. A key difference in some state laws, like New Hampshire's, is the requirement for explicit consent before processing sensitive data, offering stronger protection than CPRA's opt-out model for certain processing activities.

Understanding the Difference: Personal Information vs. Sensitive Personal Information

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Examples of Sensitive Personal Information

Let's explore some common examples of SPI and the reasons behind their sensitive classification:

Financial Information: Bank account numbers, credit card details, and access credentials are prime targets for fraud and identity theft if breached.
Health and Biometric Data: Health records, genetic data, and biometric identifiers (fingerprints, facial scans) fall under stringent regulations due to their potential for discrimination and severe privacy risks.
Social Security Numbers & Government Identifiers: SSNs, driver's licenses, and passport details are highly valuable for identity fraud and criminal activities.
Precise Geolocation: Real-time location tracking can intrude on personal security and lead to stalking or targeted threats.
Racial or Ethnic Origin: This data is sensitive due to the potential for discrimination and bias.
Citizenship or Immigration Status: Exposure of this information can result in legal risks and discriminatory treatment.
Religious or Philosophical Beliefs: This data can be misused for targeted harassment or persecution.
Trade Union Membership: Revealing this information can lead to workplace discrimination.

Real-World Cases of Businesses Handling Sensitive Personal Information

Sensitive data isn't confined to databases; it’s embedded in our daily interactions with technology and services.

Language Learning Software: An app that customizes lessons based on a user's native language might inadvertently collect data related to racial or ethnic origin, which is considered sensitive.
Online Health Tracking Tools: Sleep tracking apps that monitor patterns and disturbances collect health information, highlighting the need for careful handling of this sensitive data category.

In these scenarios, ensuring lawful processing, often by obtaining prior consent or complying with specific regulatory requirements like CPRA's "limit the processing of my sensitive personal information" link, is crucial.

[Guide Lawful data processing under GDPR]

SPI is also encountered in offline settings, as illustrated by examples from the Information Commissioner’s Office:

[Source: Information Commissioner’s Office] [Source: Information Commissioner’s Office]

Implications for Businesses Handling Sensitive Data

Handling SPI without proper safeguards can lead to significant consequences:

Legal and Regulatory Non-Compliance: Violations of privacy laws can result in substantial fines. GDPR breaches can incur fines up to €20 million or 4% of global turnover, while CCPA fines can reach $7500 per incident per consumer.
Reputational Damage: Data breaches involving SPI can severely damage consumer trust and lead to long-term financial and customer losses.
Operational and Financial Risks: Improper handling of SPI increases the risk of lawsuits, fines, and operational disruptions. Businesses must implement robust information security measures.

What is Not Considered Sensitive Personal Information?

Defining what does not constitute sensitive personal information can be complex. However, generally, the following are not considered sensitive:

Basic Personal Information: Name, age, contact number, email address, and birthdays are typically not classified as sensitive.
Publicly Available Information: Information lawfully made available by the government or the individual is often not considered sensitive, though definitions can vary by jurisdiction.
De-identified Data: Data that cannot be linked back to an individual's sensitive attributes is generally not considered SPI.

Best Practices for Protecting Sensitive Information

Businesses handling SPI should adopt robust practices to ensure compliance and build consumer trust:

Implement Strong Security Measures: Utilize encryption, access controls, and conduct regular security assessments.
Limit Data Collection and Retention: Adhere to data minimization principles and establish data retention policies.
Obtain Explicit Consent and Provide Opt-Out Options: Obtain consent where required (GDPR, some US state laws) and provide opt-out mechanisms (CPRA).
Conduct Regular Risk and Impact Assessments: Perform Data Privacy Impact Assessments (DPIAs) and stay updated on regulations.
Maintain Legal Awareness: Monitor changes in privacy laws and definitions of SPI.

Why Does SPI Protection Matter?

Responsibly handling sensitive personal information is no longer optional; it's a business imperative. By implementing strong security, compliance frameworks, and consumer protection strategies, businesses can avoid significant penalties, enhance data privacy, and cultivate consumer trust.

FAQ on Sensitive Personal Information

What is consent for processing sensitive personal information?

Consent often serves as a crucial legal basis for processing sensitive personal information, particularly under laws like GDPR and some US state regulations (e.g., Virginia, Colorado). CPRA takes a different approach, requiring businesses to provide consumers with the option to restrict or limit the processing of their SPI.

Do you need consent to process personal data?

Unlike sensitive personal information, consent is not always mandatory for processing general personal data. Many laws require businesses to offer opt-out mechanisms for specific activities like targeted advertising or the sale of personal data. Under GDPR, consent is just one of several legal bases for processing personal data.

What are 10 examples of sensitive personal information?

Here are 10 examples commonly defined as SPI under privacy laws like GDPR and CPRA:

Racial or ethnic origin
Political opinions
Religious or philosophical beliefs
Trade union membership
Genetic data
Biometric data (for identification)
Health information
Sex life or sexual orientation
Precise geolocation data
Social security & financial data

These categories necessitate enhanced protection due to the significant risks of discrimination, fraud, or identity theft if misused.