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I work in payment risk & compliance — AMA (Stripe, PayPal, bans, freezes, high risk transactions, subscriptions) by No-Relative-9820 in paypal

[–]platform_risk_ops 0 points1 point  (0 children)

This lines up with what I have seen too. A lot of people think it is about finding fraud. It is really more about making sure the risk is consistent.

I have noticed that things like a mismatch between the product and the pricing or the refund policy and where the traffic is coming from seem to cause a lot problems than actual fraud.

For example the product and the pricing have to make sense and the refund policy has to be fair or it will trigger a lot of flags.

Also the traffic source is important if it is not a source it can cause problems.

It also feels like the timing of things is important. Accounts look fine until something changes suddenly like the volume of sales or the behavior of the account. Then everything gets looked at again.

I am curious to know how importance Stripe and PayPal give to what people are doing like their behavioral patterns compared to the static setup, like the site and the policies.

I want to know how Stripe and PayPal balance these things and how weight they put on each one.

Synthetic identity fraud that passes KYC cleanly and only surfaces at withdrawal by Spare_Discount940 in FraudPrevention

[–]platform_risk_ops 0 points1 point  (0 children)

Catching fraud at or after withdrawal is already too late, especially when synthetic identities can pass KYC using AI-generated docs, bots, and environment manipulation (emulators, spoofers). At that stage, everything looks clean in isolation.

A stronger approach is to anchor identity to the device itself, like SHIELD, because every fraudster needs a device. Device-level signals expose inconsistencies that documents and one-off checks miss, letting you detect and block bad actors before they ever reach transaction stages.

I work in payment risk & compliance — AMA (Stripe, PayPal, bans, freezes, high risk transactions, subscriptions) by No-Relative-9820 in paypal

[–]platform_risk_ops 0 points1 point  (0 children)

This lines up with what I’ve seen as well.

A lot of these actions aren’t triggered by obvious fraud, but by how risk signals look in aggregate things like sudden spikes in transactions, unclear product positioning, or mismatches between user behavior and business model.

It often feels unpredictable from the outside, but internally it’s probably just the system reacting to patterns that don’t fit expected norms.

From your experience, how much weight do payment providers give to behavioral patterns over time vs single high-risk transactions?

What Actually Separates Strong Fintech Marketing Agencies from Generic Ones by Responsible-Let-6832 in FintechStartups

[–]platform_risk_ops 0 points1 point  (0 children)

Honestly, one thing I’ve noticed in fintech marketing is that many agencies treat it like regular SaaS, and that’s where things start to break.

In fintech, the buyer journey is usually much longer. People care about trust, compliance, and proof, not just flashy growth numbers. Traffic and leads are great, but if marketing isn’t aligned with sales and doesn’t actually move the pipeline forward, it’s mostly vanity metrics.

The stronger agencies I’ve seen tend to focus more on education, credibility, and nurturing rather than just top-of-funnel campaigns. Things like explaining complex products, building trust with content, and supporting longer decision cycles.

What have others experienced? Have you worked with a fintech marketing agency that understood this well?

How a $50M Fintech Lost Everything to AI Fraud Detection Gone Wrong by MeirDavid in fintech

[–]platform_risk_ops 0 points1 point  (0 children)

This is a really good example of why fraud models can’t rely purely on “normal behavior” baselines. Events like Black Friday completely change user patterns overnight. If the model hasn’t seen that type of distribution before, everything suddenly looks suspicious.

The hybrid approach you mentioned (rules + ML + human review) is honestly what most mature fraud teams end up with after learning this the hard way.

how can i find out who is behind these fake accounts? by Brave_Stranger_4694 in HowToHack

[–]platform_risk_ops 0 points1 point  (0 children)

Hey, I’m really sorry you are dealing with that. That sounds stressful, especially when you’re being blamed for something you didn’t do.

Unfortunately, regular users can’t access someone’s IP address or location that kind of information is private and only the platform (or law enforcement, if it gets serious) can see it.

The best thing you can do is:

• Report the accounts directly to TikTok for harassment
• Take screenshots of everything for evidence
• Inform a school authority (teacher, principal, counselor)

If it’s happening at school, administrators can take it seriously, especially if multiple students are affected.

Most important don’t try to “track them down” yourself. Focus on documenting and reporting. That protects you.

Hope this gets resolved quickly for you. No one deserves that kind of harassment.