FinTech & Loan Apps: Handling Sensitive Data in 2026

What Counts as Sensitive Data in FinTech and Loan Apps?

GDPR defines two types of sensitive data: personal data (including financial data) and special category data (Article 9).

FinTech and loan apps collect financial data and special category data, that must be treated with extra care.

Financial data is personal data when it can identify a person directly or indirectly (in combination with a name, account number, device ID, etc.).

Examples of financial data include:

Bank account numbers / IBANs
Transaction histories
Card details
Salary and income statements
Loan repayment history
Social Security Number
Personally owned property
Individual user spending patterns.

Examples of special category data include:

Health data
Biometric data
Photo of a face
Racial/ethnic origin
Political opinions
Religious or philosophical beliefs
Trade union membership
Sex life and sexual orientation

Special category data can directly reveal a person’s identity; therefore, it must be subject to additional restrictions. Financial data must still be protected, even though less strict security standards apply to it.

In FinTech and loan apps, financial data can reveal special category data. Sometimes – even accidentally. That’s why in 2026, FinTech and loan apps must also treat financial data with high security standards.

Credit scores, income, and bank transactions per se are not sensitive and usually do not fall into the sensitive data category. However, when such data is combined with device IDs, location data, user behavior data or marketing identifications, it could become sensitive data. financial data can become special category data when it reveals special category information, even indirectly.

For example:

Transactions showing medical payments may reveal health data.
Donations or payments to a church may reveal religious beliefs.
Payments to a political party may reveal political opinions.

Remember: if personal data could be used for profiling or automated decision-making, treat such data as special category data, since regulators and users treat it in this way.

Why Loan and FinTech Apps Face Higher Data Protection Risk

Most apps collect personal data. FinTech and loan apps collect the data like identity documents, bank accounts, income, debt, and spending habits, that could cause severe and unacceptable security issues if leaked.

Financial data that loan and FinTech apps collect could cause the following risks:

Fraud and financial harm risks If attackers access this data, they can open fraudulent accounts or loans or run targeted phishing using real financial details.
Identity theft Attackers could take over accounts or use the data to bypass identity verification elsewhere.

Since loan and FinTech apps could cause significant harm to people if the data is leaked, regulators often classify financial data processing as high-risk processing by default.

Supervisory authorities expect FinTech companies to:

Clearly explain what financial data is collected and why.
Limit data collection to a minimum.
Conduct Data Protection Impact Assessments (DPIAs).
Ensure vendors and APIs meet GDPR processor requirements.

Key Regulatory Frameworks in FinTech and Loan Apps in 2026

FinTech and loan apps in 2026 are regulated by several regulations, including:

General Data Protection Regulation (GDPR)

Any FinTech or loan app handling personal data of EU residents, must comply with the GDPR.

GDPR regulates:

Collection and processing of personal and financial data of FinTech or loan apps.
Credit profiling and automated decision-making (Article 22).
Security requirements and breach notifications.
User rights (access, deletion, portability, objection).

Any FinTech or loan app handling personal data of EU residents must:

Have a lawful basis to collect user data (contract, legal obligation, consent, legitimate interest).
Respect the data minimization principle.
Respect data retention limits.
Implement data security measures.
Perform a Data Protection Impact Assessment (DPIA).

Failure to comply with the GDPR could lead to severe penalties and fines, which can be up to 4% of the organization's global annual revenue.

Use CookieScript CMP to provide a Cookie Banner, obtain and store Cookie Consent, and comply with the GDPR.

In 2024, CookieScript Consent Management Platform (CMP) was nominated as the best CMP on G2, a peer-reviewed website for compliance with the GDPR and other privacy laws!

eprivacy Directive

The ePrivacy DirectiveThe ePrivacy Directive regulates websites and mobile apps using cookies, SDKs, and other tracking tools. In the EU, if you want to use analytics or behavioral tracking, you need valid user consent.

The eprivacy Directive sets the following requirements:

Before setting cookies or other trackers, FinTech and loan app must obtain valid user consent.
Consent must be prior, explicit, and specific.
Users must have the ability to withdraw consent at any time.

EU AI Act

The EU AI Act regulates high-risk AI applications, including loan approval, credit scoring, bank transaction analysis, and biometric identity verification.

If a FinTech or loan app uses AI to perform some of their core functionalities, for example, automated decisions, credit scoring, content generation, or fraud detection, the EU AI Act applies to the FinTech or loan app.

The EU AI Act uses a risk-based approach: the Act categorizes AI systems based on how much harm they could cause to individuals and sets the appropriate requirements. The higher the potential risk of AI, the stricter the requirements are set.

The full application date of the Act, when most of the rules become enforceable, is August 2, 2026.

Payment Services Directive 2 (PSD2) and Open Banking Rules

PSD2 applies to FinTechs or loan apps that access bank accounts, payment data, or connect to user bank accounts in the EU.

PSD2 regulates:

Access to bank accounts via APIs (Open Banking).
Strong Customer Authentication (SCA).
Secure handling of payment credentials.
Consent requirements for accessing financial accounts.

AML and KYC Regulations (Anti-Money Laundering laws)

AML and KYC regulations set requirements for loan providers, digital lenders, neobanks, and many FinTech platforms that handle users’ identity and financial data.

The laws regulate:

Identity verification (KYC – Know Your Customer).
Transaction monitoring.
Fraud prevention and monitoring.
Record-keeping requirements.
Reporting suspicious activity.

Digital Operational Resilience Act (DORA)

It’s a new EU regulation, regulating financial entities and their ICT providers. It sets obligations to FinTech companies to implement adequate technical and organizational security measures to safeguard users’ personal data.

DORA sets these requirements for FinTech or loan apps:

Cybersecurity means.
Incident reporting.
Vendor risk management.
Operational resilience testing.

Consumer Credit Directive (CCD) and national lending laws

CCD and national lending laws regulate apps offering consumer loans in the EU. The laws regulate what data you can collect and how to use it.

They regulate:

Creditworthiness assessments.
Transparency of loan terms.
Responsible lending obligations.
Consumer protections.

AI and Data Handling in Lending: How to Manage Sensitive Data om 2026?

Handling sensitive data in lending now requires a Privacy-by-Design architecture that treats data as a liability rather than just an asset.

When handling sensitive data, use the following approaches:

Comply with regulatory frameworks, such as GDPR, eprivacy Directive, the EU AI Act, PSD2, DORA, and others.
Implement Privacy-Enhancing Technologies (PETs) that enable AI to process data and “learn” without directly accessing raw data or identifying a real person. PETs include: Homomorphic encryption, Zero-Knowledge Proofs (ZKP), federated learning, differential privacy, and others.
Shift to alternative & cash-flow data
In 2026, traditional credit scores are being supplemented by real-time data:
Cash-flow underwriting: Instead of relying on users’ willingness to pay, AI now analyzes ability to pay via real-time income and spending patterns.
Data minimization: Lenders are now collecting only what is needed for the specific loan purpose and deleting it immediately after the right to contest period expires.
Neural & biometric data: Some jurisdictions (e.g., Colorado) have expanded sensitive data to include neural data. If your AI uses eye-tracking or biometric sentiment analysis for fraud detection, you must obtain explicit consent and implement ultra-high data security levels.
Explainability
In 2026, FinTech or loan apps can’t simply reject users a loan provide no other financial service. You must provide Specific Reason Codes:
Adverse Action Notices: if a FinTech or loan app rejected a service, you must use Explainable AI tools like SHAP or LIME to tell the borrower exactly which variables caused the rejection.
Bias Auditing: FinTech or loan app must perform regular fairness audits quarterly to ensure AI don’t discriminate against borrowers using proxy variables, for example, zip codes, age, or gender.

How to Secure Sensitive Financial Data

For FinTech and loan apps, security comes first; it’s a GDPR requirement. Article 32 explicitly requires “appropriate technical and organizational measures,” and regulators expect strict control of financial and identity data.

FinTech and loan apps must protect data at every stage: collection, transmission, storage, access, and deletion.

To secure sensitive financial data, FinTech or loan apps must:

1. Encrypt data in transit and at rest

When transferring financial data, implement the following security measures:

Enforce HTTPS (TLS 1.2 or 1.3) across your entire app and APIs.
Secure mobile app traffic with certificate pinning where possible.
Never send financial data over unencrypted channels.

When storing sensitive financial data:

Encrypt databases, backups, and object storage.
Encrypt sensitive fields (IBAN, national ID, account numbers) separately.
Store encryption keys securely using a key management system (KMS), not in code or config files.

2. Restrict and monitor access to financial data

Most breaches occur because of human errors, when employees have excessive internal access, not because of hackers.

Thus, it is very important to restrict access to financial data using these principles:

Limit the data employees can access (no excessive data).
Use role-based access control (RBAC).
Require multi-factor authentication for admin access.
Monitor all access to sensitive financial data.

Developers, support staff, and analysts should never have full access to sensitive financial profiles by default.

3. Minimize data collection and storage

FinTech and loan apps should collect only the minimal data needed to approve the loan.

Once a decision is made, the data must be deleted. Delete uploaded identity documents after verification.

It is good practice to store a token or reference instead of raw data. For example, store last 4 digits instead of full account numbers when possible.

To safeguard sensitive financial data, align with GDPR’s data minimization and storage limitation principles.

4. Secure APIs, integrations, and third-party vendors

Loan apps rely heavily on external services, such as open banking providers, identity verification technologies, fraud detection tools, analytics and tracking tools. These integrations can become your weakest point, where sensitive financial data could be leaked.

Use these best practices to safeguard users’ financial data:

Use authenticated and encrypted APIs.
Rotate API keys regularly.
Never expose keys in mobile apps or frontend code.
Sign Data Processing Agreements (DPAs) with vendors.
Audit vendor security measures and GDPR compliance.

Note: Under GDPR, if a vendor reveals your users’ financial data, your company is still accountable. As a data holder, you must ensure that vendors implement adequate security measures to protect users' data.

5. Pseudonymize and anonymize data where possible

To reduce compliance risk, separate person’s identity from their financial behavior.

For example, store user IDs instead of names in analytics systems, tokenize account identifiers, or remove direct identifiers from testing and development environments.

6. Define retention and deletion policies

Financial and identity data must be stored for as minimal time as possible.

Create clear retention and deletion policies for financial data collection and storage. Use these best practices:

Delete rejected loan applications when the loan evaluation is closed.
Delete identity verification documents once a user is verified.
Pseudonymize and anonymize historical analytics data.

7. Prepare for breach detection and response

Even if FinTech and loan apps handle financial data responsibly, data breach and incidents can happen.

Be ready for breach detection and response:

Implement breach detection and alerting systems.
Prepare internal incident response procedures.
Implement the plan how to identify and inform affected users quickly.
Implement a plan to notify regulators within 72 hours if required.

Common Compliance Mistakes FinTech and Loan Apps Still Make

Even if FinTech teams know about GDPR and DPIAs, they still make mistakes.

The most common mistakes include:

Collecting excessive financial data
Some FinTech and loan apps collect excessive financial data “just in case”, because it might be useful later. It could be transaction histories, geolocation, behavioral signals, and other data. That violates GDPR’s data minimization principle.
Wrong lawful basis
Loan apps often mix purposes for data collection: contract vs. consent vs. legitimate interest.
Data needed to process a loan: use contract.
AML identity checks: it’s a legal obligation.
Fraud prevention: it’s a legitimate interest.
Data collection for analytics and marketing: obtain user consent.
Unclear credit scoring and automated decisions
If your app uses AI to automatically approve or reject loans and does not provide an explanation of how scoring works, you may be violating GDPR Article 22.
Systems must have human review.
Users have the right to know that the decision was made using AI tools; platforms should provide the logic how it works.
Storing identity documents for too long
Loan apps collect a lot of information for user registration and verification, such as passport scans and photos of the user's face. Many loan apps retain these indefinitely, even after verification or rejection. This violates the storage limitation principle of the GDPR. You must delete rejected applications and KYC documents after some time, set in your Privacy Policy.
Insufficient security
Security problems still happen.
Remember: financial data should never appear in logs and never be used in raw form in staging.
Use data anonymization to minimize the impact of data breaches.

Consent Management for FinTech Apps and Loan Platforms

The easiest way to manage user consent for FinTech apps and loan platforms is by using a Consent Management Platform (CMP).

CookieScript CMP is one of the best CMPs, valued by users. In 2025, CookieScript received its fourth consecutive badge in a row as the leader on G2, a peer review site, and became the best CMP on the market for a whole year!

CookieScript CMP offers the following cookie compliance solution for FinTech apps and loan platforms:

Provides geo-targeting
Different Cookie Banners and different privacy notices will be delivered to website users based on their geographic locations. Cookie banners will not conflict with each other, and the proper script will be taken for each location.
Provides a fully customizable GDPR and CCPA Cookie Banner.
Provides one of the most configurable Cookie Banner on the market, which allows adjusting to your website's design.
Scans your website for cookies and tracking pixels.
Categorizes your cookies.
Maintains a full history of user consent.
Allows users to withdraw consent at any time.
Blocks cookies until users agree to the Cookie Consent and the Privacy Policy.

CookieScript CMP also has a full automation solution:

Frequently Asked Questions

What counts as sensitive data in FinTech and loan apps?

Article 9 of GDPR defines two types of sensitive data: personal data (including financial data) and special category data. Financial data is personal data when it can identify a person directly or indirectly (in combination with a name, account number, device ID, etc.). Special category data includes health data, biometric data, photographs of a person's face, racial or ethnic origin, political opinions, religious or philosophical beliefs, trade union membership, sex life, and sexual orientation.

How to secure sensitive financial data?

To secure sensitive financial data, FinTech or loan apps must encrypt data in transit and at rest, restrict and monitor access to financial data, minimize data collection and storage, secure APIs, integrations, and third-party vendors, pseudonymize and anonymize data where possible, define retention and deletion policies, and prepare for breach detection and response. Use CookieScript CMP to manage user consent.

What are the common compliance mistakes fintech and loan apps still make?

The most common mistakes include collecting excessive financial data, selecting the wrong lawful basis, using vague credit scoring and automated decisions, storing identity documents too long, and insufficient security. Use CookieScript CMP to manage user consent.

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