Accuracy Principle in Data Processing Under the Nigeria Data Protection Act (NDPA)

In the era of digital banking, e-commerce, mobile apps, and AI-driven decision systems, the accuracy of personal data has become one of the most critical pillars of data protection law. Under the Nigeria Data Protection Act (NDPA), the accuracy principle ensures that personal data processed by organisations is correct, complete, and kept up to date.

In simple terms, the accuracy principle requires that organisations must not rely on wrong, outdated, or misleading personal data when making decisions about individuals.

This principle is especially important in sectors like banking, healthcare, telecoms, fintech, insurance, and government services, where inaccurate data can lead to financial loss, wrongful denial of services, identity mismatches, or legal disputes.

What Is the Accuracy Principle Under NDPA?

The accuracy principle under the NDPA states that personal data must be:

• accurate
• complete
• not misleading
• kept up to date where necessary

It also requires organisations to take reasonable steps to correct or erase inaccurate personal data without delay.

This principle is a core part of lawful data processing and applies to all data controllers and data processors operating in Nigeria.

Why the Accuracy Principle Matters

As Nigeria’s digital economy expands rapidly, millions of personal records are processed daily across digital platforms. From mobile banking apps to online identity verification systems, even a small data error can have serious consequences.

Inaccurate data can lead to:

• failed bank transactions
• wrongful fraud flags
• rejected loan applications
• misidentification of individuals
• denial of healthcare services
• compliance violations

With the rise of automated decision making and AI systems, the impact of inaccurate data is now more severe than ever.

Core Requirements of the Accuracy Principle

Under the NDPA, organisations must ensure:

1. Personal data is accurate at the time of collection
2. Inaccurate data is corrected or deleted without delay
3. Data is updated when changes occur
4. Reasonable verification methods are used
5. Third party data sources are reliable

1. Data Must Be Accurate at the Point of Collection

Organisations are expected to collect accurate information from the beginning.

This means implementing proper validation systems during data entry, registration, or onboarding.

Example

A bank collecting customer details during account opening must ensure:

• correct spelling of names
• valid phone numbers
• accurate identification numbers
• verified address information

If incorrect data is collected, all future processing becomes unreliable.

2. Continuous Updating of Personal Data

Accuracy is not a one time requirement. It must be maintained throughout the data lifecycle.

Organisations must ensure that personal data is updated when changes occur.

Example

If a customer changes their phone number or residential address, the organisation must update its records promptly.

Failure to do so may lead to communication failures or security risks.

3. Obligation to Correct or Delete Inaccurate Data

If inaccurate data is identified, organisations must take immediate steps to:

• correct the information
• delete incorrect entries
• notify relevant third parties if necessary

Real-world example

If a fintech platform incorrectly flags a customer as fraudulent due to incorrect identity data, it must correct the error and restore access without delay.

4. Use of Reliable Data Sources

The NDPA requires organisations to ensure that data sources are reliable and trustworthy.

This is especially important when data is obtained from third parties.

Example

A credit scoring company must verify the accuracy of data obtained from external databases before using it for financial decisions.

5. Reasonable Steps Requirement

The law does not demand perfection, but it requires “reasonable steps.”

This means organisations must implement practical systems such as:

• data validation tools
• identity verification systems
• periodic data audits
• customer self-service update portals
• automated error detection systems

Real-Life Case Scenario: Banking Sector

In Nigeria’s banking sector, accuracy errors can cause significant operational issues.

Scenario

A customer’s BVN is incorrectly linked to another individual’s account due to data entry errors.

Possible consequences

• account restrictions
• failed transactions
• fraud investigation delays
• customer frustration

NDPA expectation

The bank must immediately investigate, correct the data, and ensure such errors are prevented in the future.

Real-Life Case Scenario: Healthcare Sector

In healthcare systems, inaccurate data can have life-threatening consequences.

Scenario

A patient’s allergy information is incorrectly recorded.

Consequence

The patient may be given medication that causes adverse reactions.

NDPA expectation

Healthcare providers must ensure strict data accuracy controls and immediate correction mechanisms.

How Organisations Can Ensure Data Accuracy

To comply with the NDPA accuracy principle, organisations should implement:

1. Data validation systems

Automated checks during data entry reduce human errors.

2. Identity verification processes

Use BVN, NIN, OTP verification, or biometric checks.

3. Regular data audits

Periodic review of stored data helps identify inaccuracies.

4. Customer self-service updates

Allow users to update their own personal information.

5. Staff training

Employees should understand the importance of data accuracy in daily operations.

6. Data correction workflows

Clear internal processes for correcting inaccurate data quickly.

Common Violations of the Accuracy Principle

Many organisations unknowingly violate the NDPA accuracy principle through:

• outdated customer records
• duplicate entries
• incorrect identity matching
• failure to update changed information
• reliance on unverified third-party data
• manual data entry errors

These issues often arise from weak data governance systems.

Accuracy Principle vs Other NDPA Principles

Principle	Focus
Accuracy	Correctness of data
Data minimization	Limiting data collected
Purpose limitation	Restricting usage
Storage limitation	Retention control
Integrity and confidentiality	Data protection and security

Accuracy is unique because it directly affects decision-making quality across systems.

Expert Insight: Why Accuracy Is Now a Business Risk Issue

In modern data-driven environments, inaccurate data is no longer just a compliance issue. It is also a business risk.

Poor data accuracy can lead to:

• financial loss from wrong decisions
• regulatory penalties
• reputational damage
• loss of customer trust
• system inefficiencies

With the rise of AI and automated decision-making, inaccurate data can scale errors across entire systems instantly.

Frequently Asked Questions

1. What does the accuracy principle mean under NDPA?

It means personal data must be accurate, complete, and kept up to date, and incorrect data must be corrected or deleted.

2. Why is data accuracy important?

Because inaccurate data can lead to wrong decisions, financial losses, service failures, and legal issues.

3. Does NDPA require perfect data accuracy?

No. It requires organisations to take reasonable steps to ensure accuracy, not guarantee perfection.

4. What should a company do if it finds incorrect data?

It must correct or delete the inaccurate data immediately and update affected systems.

5. Who is responsible for ensuring data accuracy?

Both data controllers and data processors are responsible under NDPA obligations.

6. Can outdated data violate NDPA?

Yes. Keeping outdated personal data without updating or correcting it can violate the accuracy principle.

7. How can organisations improve data accuracy?

By using validation systems, regular audits, identity verification tools, and allowing user updates.

Final Thoughts

The accuracy principle under the NDPA is essential for building trust, ensuring fairness, and maintaining reliable data systems in Nigeria’s digital economy.

As organisations increasingly rely on data-driven technologies, the cost of inaccurate data continues to rise. Businesses that prioritize data accuracy not only achieve regulatory compliance but also improve operational efficiency and customer satisfaction.

In today’s environment, accurate data is not just a legal requirement. It is a strategic business asset.

External References

• Nigeria Data Protection Commission: https://ndpc.gov.ng/
• Federal Ministry of Justice Nigeria: https://justice.gov.ng/