Score customer risk before you onboard them
{ "email": "new.customer@example.com", "deliverability": "DELIVERABLE", "quality_score": 0.35, "is_disposable_email": false, "is_free_email": true, "domain_age_days": 5, "address_risk_status": "high" }
The signals behind a customer risk score
+ IP intelligence: VPN, proxy, Tor, and data-center detection, plus location mismatch.
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How to build a risk assessment workflow
Why teams score customer risk with Abstract
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Frequently asked questions
What is customer risk assessment?
Customer risk assessment is the practice of scoring how risky a new customer is before you onboard them. You combine signals about the email, phone, and IP they sign up with, then decide whether to approve, review, or block. For SaaS, ecommerce, and marketplaces it keeps fraud out without slowing down real customers.
What is the difference between a risk score and a risk rating?
A risk score is a number you calculate from live signals at a moment in time, like signup or checkout. A risk rating is a broader, longer-lived category you assign a customer, often for compliance. Abstract gives you the raw signals to build the score; how you turn that into a rating is your call.
What is a fraud risk score?
A fraud risk score is a single value that summarizes how likely a customer or transaction is to be fraudulent. Instead of one opaque number, Abstract returns clear true or false flags (disposable email, VOIP phone, VPN or proxy IP) so you can weight them into a score you can actually explain.
How often should you reassess customer risk?
Re-score at the moments that matter, not just at signup. Good triggers are login from a new device or country, checkout or payout, a plan change, and any spike in activity. Because each check is a single request, you can re-run it inline whenever risk could have changed.
Is a single black-box fraud score enough?
Usually not. A black-box score you cannot explain is hard to tune, hard to defend, and hard to debug when it is wrong. Transparent flags let you see why a customer was risky, set your own thresholds, and adjust rules as fraud patterns change.
What signals go into a customer risk score?
The strongest signals are the email (disposable, free, domain age, address risk), the phone (VOIP or invalid line type, carrier, country), and the IP (VPN, proxy, Tor, data center, and location mismatch). Combined, they separate real customers from risky ones at onboarding.
How does Abstract help with customer risk assessment?
Call Abstract's Email Reputation, Phone Validation, and IP Intelligence APIs when a customer signs up or transacts. Each returns transparent risk flags you combine into your own score, one request per check. You can start on the free tier with no credit card.
