The importance of data validation in modern credit management

What is data validation and why is it important?

Data validation is the process of checking customer data for accuracy, completeness, and topicality. For example, verifying email addresses, phone numbers, IBANs, or address details.

Incorrect data leads to:

• Poor accessibility
• Unreliable risk profiles
• Ineffective reminder campaigns
• Poor basis for credit decisions

For modern credit management — where communication, risk analysis and customer focus come together — data validation is essential.

The legal obligation: GDPR and the principle of “accuracy”

The GDPR states that organizations must take “all reasonable measures” to keep personal data accurate and up to date. This is explicitly described in chapter 3 of the GDPR, including the schedule about the controller's role.

Concretely, this means:

• Inaccurate or outdated data must be corrected or deleted.
• Customers must be able to view and correct their data.
• You must be able to demonstrate that you are actively working on data quality.

Anyone who does not arrange this properly risks sanctions from the Personal Data Authority and damages customer trust.

Why up-to-date customer data is essential for credit management

As a credit manager, you want to assess risks, predict payment behavior and target customers in a targeted manner in case of arrears. That is only possible if you are over current and accurate customer data features.

Errors in your customer database lead to:

• Incorrect credit limits or payment arrangements
• Memories that don't arrive
• Wrong risk classification
• Low follow-up response rate

A well-designed data validation process increases your strength, reduces errors and saves costs.

Multichannel communication requires channel-specific data validation

In credit management, we communicate via multiple channels: email, text, mail, telephony, payment apps and even WhatsApp. Each channel has its own data requirements:

• E-mail: correct structure, domain validation
• Mobile numbers: correct layout, mobile detection
• Addresses: zip code validation and house number check
• WhatsApp: mobile and active user required

Without proper validation, your contact attempts are futile — and you lose valuable time in your follow-up strategy.

AI and machine learning in credit management: data is key

AI and machine learning are increasingly being used in credit management. Think about:

• Customer segmentation based on payment behavior
• Risk forecasting
• Customized automatic reminder flows

But: AI is just as good as the data it's trained on. Bad, incomplete or erroneous data leads to wrong conclusions and therefore to incorrect risk assessments or ineffective communication.

Data validation is the prerequisite for smart, data-driven credit management strategies.

Smart ways to enrich customer data

In addition to controlling, you can also enrich customer data. This gives you more control over the customer profile without burdening your customer unnecessarily.

Examples of enrichment:

• Allow customers to confirm their email address or mobile number while paying via QR code.
• When signing up, ask for additional data via a smart, user-friendly flow.
• Use data links with external sources such as KVK, postcode.nl or validation APIs.
• Add logic to your customer portal: “Is this phone number still correct?”

This way, you can build richer customer profiles in an AVG-proof way.

Why you should never buy customer data

Some organizations are trying to accelerate growth by purchasing customer data. But this is almost always unreliable and legally risky.

The risks of purchased data:

• Not up to date: these lists are often years old.
• No permission: without an explicit opt-in, you are not allowed to use the data.
• Conflict with the GDPR: there is no valid basis for processing.
• Fines and reputational damage: the Data Protection Authority actively enforces.

Trust and data are built through interaction, transparency, and clear communication — not by buying email lists.

The most important data for effective credit management

For an efficient credit management strategy, the following data is crucial:

• Name and address details — for communication and risk assessment
• Email address & mobile number — for digital follow-up
• Payment behavior & history — for segmentation and forecasting
• IBAN — for refunds or direct debit
• Chamber of Commerce number (for B2B) — for verification and creditworthiness

Good data validation ensures that you always work with a reliable basis, which speeds up your workflows and reduces complaints.

Data Validation and Enrichment Best Practices

1. Input Validation: Check customer details directly during registration or payment.
2. Regular data checks: Schedule periodic rounds of validation.
3. Collect enriching data when interacting with customers: For example, when contacting support.
4. Ensure GDPR compliance: Inform customers, document sources, and opt out.

By smartly combining these strategies, you are building a scalable, future-proof data layer.

Data validation in the Netherlands

For Dutch organizations, the following rules are important:

• AVG: The basic regulations concerning data quality, retention periods and permissions.
• Telecommunications Act: Relevant rules for email, SMS and telemarketing.
• Superintendence: The Personal Data Authority monitors and is able to enforce compliance.

By properly implementing data validation, you prevent legal problems and work in a more customer-focused way.

Conclusion: data validation as a foundation for modern credit management

Today's credit management is about data-driven choices, smart communication and customer-oriented follow-up. But without the right data, you won't get anywhere.
Whether you're segmenting, assessing risks or deploying AI: valid and current customer data are the basis.

Investing in data validation is not a cost, but a strategic choice:

• You reach customers faster and more effectively
• You increase the predictability of payment behavior
• You comply with legislation and increase customer trust

Data validation is key to sustainable, scalable credit management.