By business type

Privacy Policy Generator for fintech

Written for KYC, open banking, automated decisions and the regulator that reads your terms.

Generate your privacy policy Read the privacy policy guide

A fintech privacy policy has to explain why you keep data a customer wants deleted, and how automated decisions about them are made. Those two clauses carry more weight than everything else in the document, and both are usually missing from generic templates.

Fintech privacy documentation sits under two regimes at once: data protection, and financial services regulation that imposes its own record-keeping, disclosure and fair-treatment duties. The two pull in opposite directions - anti-money-laundering law requires retention that data minimisation would otherwise forbid - and the policy has to explain both without appearing to contradict itself.

Automated decision-making is the clause that matters most. Credit decisions, fraud scoring, risk-based pricing and account restrictions frequently meet the Article 22 threshold, which entitles the individual to information about the logic, human intervention and a route to challenge.

Open banking adds a third layer. Where you access account data through an aggregator, the consent architecture is regulated separately, consent expires on a defined cycle, and the customer’s relationship with the aggregator has to be explained rather than hidden behind your own brand.

What a privacy policy for a fintech or financial services business has to cover

KYC and AML processing under legal obligation, with the statutory retention period stated
Automated decision-making: which decisions, the logic in meaningful terms, and the human review route
Credit reference searches and their effect on the individual’s file
Biometric processing with its Article 9 condition, where used
Open banking: the aggregator, the scope, the consent duration and how to revoke it

How a fintech or financial services business actually moves personal data

KYC and identity verification

Identity documents, selfies, liveness checks and sanctions screening, usually through a specialist vendor that becomes a significant sub-processor.

Credit and affordability data

Bureau searches, which leave a footprint on the individual’s file, and affordability models that constitute automated decisions.

Transaction monitoring

Continuous screening for fraud and money laundering, generating alerts and suspicious activity reports with their own confidentiality rules.

Open banking account access

Aggregated account and transaction data accessed with time-limited regulated consent.

Biometric authentication

Face or fingerprint matching for onboarding or login, which is special category data under GDPR when used to identify a person uniquely.

Regulatory reporting

Data disclosed to regulators and reporting bodies under legal obligation, which the policy should acknowledge.

Third parties the draft will ask you about

Onfido or Persona · ComplyAdvantage · Experian, Equifax or TransUnion · Plaid or TrueLayer · Stripe or Modulr · AWS · Featurespace or Sift

The rules that apply

Anti-money-laundering retention

Identity and transaction records must be retained for statutory periods - commonly five years after the relationship ends - which is a legal obligation basis, not a choice.

GDPR Article 22

Automated decisions with legal or similarly significant effects require disclosure of the logic, human intervention and a challenge route.

Open banking consent

Regulated consent flows with defined durations and re-authentication, plus a distinct relationship with the account information provider.

Financial promotions and fair treatment

Marketing is separately regulated, with rules on clarity, risk warnings and target-market appropriateness.

Operational resilience and outsourcing

Regulators expect due diligence and exit plans for critical third parties, which overlaps heavily with processor governance.

What the generated privacy policy contains

Identity and contact details of the controller
Your legal entity, trading name, registered address and a working contact route - plus a representative or DPO where one is required.
Categories of personal data and their sources
What you collect directly, what you observe automatically, and what you receive from third parties such as payment providers or ad platforms.
Purposes and lawful basis, purpose by purpose
A table that pairs each processing purpose with its lawful basis rather than listing all six bases and hoping one fits.
Recipients and sub-processors
The categories of recipient, and for the ones that matter to users - payment, hosting, analytics, support - the named provider.
International transfers and their safeguards
Where data leaves its home jurisdiction, and the mechanism relied on: adequacy, standard contractual clauses, the UK addendum or IDTA.
Retention periods per data category
Concrete periods or the criteria used to set them, which is what regulators ask for first when a complaint lands.
Rights and how to exercise them
Access, rectification, erasure, portability, objection and restriction, with the actual route to make a request and the deadline you work to.
Complaints and supervisory authority
The regulator a user can escalate to, named, with a link - not a generic "your local authority".

Fintech compliance essentials

Map every automated decision
And write the Article 22 disclosure, the human review route and the challenge process.
Document AML retention as a legal obligation
With the period and the statute, so erasure refusals are explicable.
Identify the Article 9 condition for biometrics
Before onboarding goes live.
Explain the open banking chain
Who the aggregator is, what they access, how long consent lasts and how it is revoked.
Word the AML section carefully
Enough transparency to be lawful, without breaching tipping-off restrictions.
Align outsourcing due diligence with processor governance
The regulator and the data protection authority want overlapping evidence.

Where this usually goes wrong

No Article 22 disclosure for credit or fraud decisions

Automated decisioning is the norm in fintech and the disclosure is routinely missing.

Deleting data an AML obligation requires you to keep

Erasure requests do not override statutory retention, and the policy should explain why.

Biometric onboarding treated as ordinary processing

Unique identification via biometrics is special category data and needs an Article 9 condition.

Open banking consent presented as your own

The aggregator relationship and the regulated consent duration have to be explained.

Suspicious activity handling described in the policy

Tipping-off rules constrain what you may tell a customer, which means the policy has to be carefully worded rather than fully transparent.

Marketing to customers acquired through regulated flows

Financial promotion rules apply on top of consent, and the two are frequently conflated.

Frequently asked questions

Can a customer ask me to delete their KYC records?

They can ask, and you will usually have to refuse. Anti-money-laundering law requires retention for a statutory period, which is a legal obligation basis that overrides erasure - but the refusal has to be explained.

Does automated credit scoring trigger Article 22?

Where the decision is solely automated and has legal or similarly significant effects, yes. That entitles the individual to meaningful information about the logic, human intervention and a route to contest the outcome.

Is facial recognition for onboarding special category data?

Where it uniquely identifies a person, yes - biometric data processed for identification requires an Article 9 condition, typically explicit consent in a consumer context.

How should I describe open banking access?

Name the account information service provider, explain what is accessed, state the consent duration and re-authentication cycle, and explain how access is revoked.

Is a privacy policy legally required?

If you process personal data, in almost every market yes. GDPR and UK GDPR require the disclosure at the point of collection, CCPA/CPRA requires a notice at collection plus an annually reviewed policy, and app stores and payment processors require a public policy URL before they will list or onboard you.

Can I copy another company’s privacy policy?

It is both a copyright problem and a compliance problem. A copied policy describes someone else’s data flows, processors and retention periods, so it is inaccurate the moment you publish it - and an inaccurate transparency notice is itself a breach of GDPR Article 13.

How often does a privacy policy need updating?

Whenever your processing changes - a new analytics tool, a new payment provider, a new market - and as a backstop, review it annually. CPRA makes the twelve-month review explicit.

Does PolicifyAI give legal advice?

No. PolicifyAI is a technology provider, not a law firm. The output is a structured, jurisdiction-aware draft that a qualified adviser should review before you rely on it.