Lock at the right time, not the same time for everyone
Smart auto-lock decision turns rigid enforcement into an intelligent workflow. AI uses past repayment regularity, risk score, and overdue context to decide whether an account deserves a grace window, a reminder, a partial restriction, or immediate lock.
- Reliable customers: get a short buffer when the pattern shows they usually pay.
- High-risk users: move quickly to restriction or lock when the risk is already elevated.
- Escalation logic: sequence alert, voice, app restriction, call restriction, then full device lock.
Outcome
Retailers recover more without making the product feel harsh for customers who normally pay on time.
Decision inputs
- Risk score: current probability of default or delayed payment.
- Repayment pattern: whether delays are rare, frequent, or worsening.
- Portfolio rules: retailer policy, product category, and allowed grace settings.
Step 1
Friendly reminder if the account is low risk and recently due.
Step 2
Partial restriction or strong reminder if risk rises after the due window.
Step 3
Immediate lock for repeated defaulters or high-risk accounts with bypass signals.
Decision engine flow
An auto-lock model can convert account risk into staged actions instead of forcing the same rule on every customer.
Escalation path
Grace Window
Low-risk account with reliable history gets a short buffer and a softer reminder.
Partial Restriction
Medium-risk account moves to stronger reminders and selected restrictions.
Immediate Lock
High-risk or repeat-default account escalates without unnecessary delay.
Sample account logic
- Due date crossed by 1 day but prior six months are clean: delay full lock.
- Third late cycle in four months plus high-risk score: tighten the enforcement window.
- Tamper signal or repeated bypass attempt: skip to lock and callback task.
Build a more intelligent lock policy
AI can make enforcement faster where needed and softer where it should be.