AI Agent Profile · LendingIQ · Bengaluru
Propensity Scoring Agent AI
DivisionCollections
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What this agent does
The Propensity Scoring Agent AI reads the daily delinquent account population — their CBS payment history, CRM contact response patterns, current bank balance signals from Account Aggregator, and bureau refresh data — and produces a ranked triage list telling the collections team which accounts to contact first, through which channel, and why. It is the analytical layer that converts a large delinquent book into a prioritised, actionable work-list for the Collections Head AI and the collections callers. Scores are triage ranks — not default probabilities, not credit grades, not provisioning inputs.
Primary functions
Pay-Propensity Scoring
Daily — all active delinquent accountsInvoked when: daily data pipeline completes before Collections Head AI generates the day's work-list
- Reads the available signals for each delinquent account and synthesises them into a propensity score: CBS payment patterns (recent partial payments are a positive signal; a clean miss with no prior delinquency is different from a chronic pattern); CRM contact response history (accounts that have responded to WhatsApp before are more likely to respond again; accounts with repeated non-contact are harder to reach); bank balance signals via AA where consent is active (a positive balance on the day of scoring is a direct capacity signal); and bureau refresh data (new tradelines at other lenders may signal financial stress or competing obligations).
- Weights signals differently by DPD band: for DPD 0–30, bank balance and recent payment behaviour are the dominant signals. For DPD 31–90, contact response history and PTP compliance rate become more predictive. For DPD 90+, the propensity to settle rather than to pay in full requires a different signal set — the agent applies the appropriate weight configuration per bucket.
- Produces a plain-language propensity narrative for each scored account — 2–3 sentences explaining why the account scored where it did. The narrative is the signal behind the rank, and it is the narrative the collections caller needs to have a productive conversation. A rank without a narrative is a number without context.
Account Prioritisation
Daily — ranked work-list for Collections Head AIInvoked when: propensity scores are complete and the Collections Head AI requires a ranked list for work-list generation
- Ranks accounts within each DPD bucket by propensity score — ensuring the highest-propensity accounts are contacted first within each bucket. Also applies a secondary ranking criterion: exposure size. Two accounts with similar propensity scores are ranked by outstanding exposure — the higher-exposure account is prioritised because the recovery value of success is greater.
- Identifies the accounts that are approaching bucket boundary dates — DPD 27–29 accounts that will move to the mid-bucket, DPD 87–89 accounts that will classify as NPA in the next 1–3 days. These near-boundary accounts receive a priority flag regardless of their propensity score, because the cost of missing a recovery opportunity in the final days before bucket transition is higher than for accounts with more time remaining.
- Flags accounts where the propensity score has changed materially since yesterday's run — a large upward movement (bank balance improved, payment received at another lender) is an opportunity signal worth acting on immediately; a large downward movement (bank account drained, new delinquency on bureau) warrants a same-day review for escalation.
Channel Selection
Per account — based on response history and profileInvoked as part of the prioritisation run — channel recommendation generated alongside each account's rank
- Recommends the optimal first-contact channel for each account based on its prior response history: an account that has responded to WhatsApp in the past 30 days receives a WhatsApp recommendation; an account that has never responded to WhatsApp but has responded to IVR calls is recommended for IVR first. Where no prior response history exists, defaults to WhatsApp as the lowest-friction first contact.
- Flags channel constraints: accounts where the borrower has unsubscribed from WhatsApp (do not contact via WhatsApp), accounts where the phone number is inactive or disconnected (flag for address update before contact), and accounts where TRAI DND status prevents automated messaging (route to human caller only).
- Recommends human caller contact for accounts flagged as requiring empathy or judgment — prior hardship indicators, accounts the Early Warning Agent AI has flagged as stress-signalled, or accounts where the propensity score narrative indicates financial complexity that an automated channel cannot handle.
Hard guardrails
Known limitations
Important Reads
Learn more about how to deploy Propensity Scoring Agent AI to your lending workflow.
- Use case #000140 signals Propensity AI uses to score every borrower's willingness to payA DPD 45 borrower with a propensity score of 82 will pay if contacted today. The same DPD 45 borrower with a score of 31 has already decided not to — and sending a collections agent to call them today is a cost the institution pays to confirm what the model already knows. Propensity scoring separates these two borrowers before the call is made, so that every contact goes to the account most likely to produce a payment today.Read article →
- Use case #0002Channel selection: how Propensity AI picks WhatsApp, call or field for each accountA propensity score of 78 tells the collections system this account is collectible today. The channel selection model then asks: collectible by what means? A borrower who answered every previous call but has never responded to a WhatsApp message should receive a voice call today. A borrower who pays immediately after every payment link but rarely picks up the phone should receive a WhatsApp today. The propensity score and the channel selection model work together — one tells you who to contact, the other tells you how.Read article →
- Use case #0003Propensity AI and recovery rates: the ROI case for AI-driven account prioritisationThe ROI case for propensity-driven collections is not an AI argument — it is a contact economics argument. A collections agent making 60 calls per day on a DPD-ordered queue is spending the same cost per contact regardless of whether each account will pay. A collections agent making 60 calls per day on a propensity-ordered queue is concentrating that cost on the accounts where each call has the highest probability of producing a payment. The difference in recovery rate is not a technology outcome. It is a prioritisation outcome.Read article →
