Batch-based risk models that refresh quarterly. Template-based reminders that do not change between borrowers. Channels that do not share what the borrower said yesterday. Right-party-contact stays below 30%. Cost-per-recovery climbs every quarter. The team is busier than ever. The book ages quietly into provisioning.
What is UNFYD.KOLLECT?
Most collection platforms still run static risk models, template outreach and rigid waterfalls: the same SMS at month-end, the same script at week three, a dialler that calls seven times while a competitor sends one WhatsApp message. UNFYD.KOLLECT scores behavioural risk, optimises channel and timing, runs agentic GenAI communications, orchestrates promise-to-pay and payments, and keeps consent, compliance and audit as first-class versioned records with a live recovery dashboard.
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Collection was once a manual follow-up team with a list and a script. Then it became a list, a script and a few channels. Today it is a behavioural decisioning problem across the full delinquency lifecycle, or it is a missed recovery. The lender that wins on collections is the one that reads each borrower, picks the right channel and the right tone for each one, and stops chasing the accounts that would have paid anyway.
The same script. The same cadence. The same 7 calls. Right-party-contact stays below 30%. The customer who would have paid anyway is interrupted at lunch. The customer who is actually struggling gets pushed into dispute. The customer who has already disputed gets another call from the same agent. Dialler-led recovery is busy work that looks like work. The book does not move. The cost line does. The regulator notices. The competitor sends one WhatsApp and gets paid first.
Waterfall cycles. Static buckets. Strategy locked in at 9am, applied to every customer in the segment regardless of what happened in between. By the time the cycle refreshes, the high-risk account is in deeper trouble and the regular payer has been over-contacted. The collection model was designed for a slower world.
Reaching out more is not a recovery strategy. Deciding better is.
UNFYD.KOLLECT is the AI-powered, end-to-end collection automation platform that orchestrates the full delinquency lifecycle, from the first early-warning signal on an account through to final recovery and reconciliation. It scores every account on real behaviour, picks the right channel, time and tone per borrower, drafts personalised communications with GenAI, captures promise-to-pay events in the same conversation, and reconciles payments back into the core banking system. Where the legacy collection stacks treat the willing and the perilous the same way, and template-based tools send the same reminder to every bucket, this is the layer that decides, account by account, what should happen next.
Each account carries a live propensity-to-pay score and a propensity-to-default score. Refreshed against every new payment, conversation and channel interaction, with next-best action surfaced per account. Early defaulter detection improves 60%.
A channel attribution engine learns which surface each borrower actually responds to. The night-shift driver gets WhatsApp at 9pm, the HNI gets email at 11am, the senior citizen gets voice IVR after lunch. Promise-to-pay rate climbs 35%.
Agentic AI runs the conversation end-to-end. GenAI drafts every reminder, settlement offer, dispute response and partial-payment plan in brand voice and regulator language, across personalised video, dynamic PDF, conversational WhatsApp and voicebot. The agent steps in only where a human is needed.
UPI, cards, net-banking, wallets and payment-link surfaces integrated end-to-end. Promise-to-pay detected in conversation, payment link triggered in the same moment, reconciliation with core banking automatic. The recovery closes itself, end-to-end.
DPDP, RBI, IRDAI and SEBI guardrails baked into the platform layer. Consent management as a first-class versioned workflow, with PII masked at ingest at field-level granularity. Every contact, override and approval carries a timestamp and an attribution.
Bucket-wise recovery, agent performance, channel ROI and predictive NPL forecasting on one screen. Refreshed in real time, drillable by region, product and agent. The Head of Collections walks in with the answer, not the rebuild project.
UNFYD® orchestrates collections across the full BFSI delinquency lifecycle. Personal loans, credit cards, auto loans, home loans, MSME credit. ML risk-scores every account in real time, picks the right channel, time and tone per borrower, drafts the personalised reminder with GenAI in the borrower’s language, captures the promise-to-pay event, sends the payment link in the same conversation, reconciles with the core banking system, closes the case. Early-bucket recovery lifts 35%. Manual collection effort drops 85%. Cost-per-recovery halves. NPL provisioning eases on the next regulator filing.
Every payment history record, every transaction velocity signal, every channel response, every NLP-flagged distress moment, every life-event hint, feeds one decisioning surface. The right account gets the right channel and the right tone at the right hour. The wrong account stops getting the 11th call.
Early-bucket recovery rises, severe-delinquency slippage falls, provisioning models flex accordingly. The next regulator filing reads cleaner. The auditor moves on faster. The board minutes get shorter.
Recovery handled where the borrower actually responds, not where the playbook said to call. Agents step in only at the 20% of accounts that actually need a human and the platform handles the rest. Cost-per-recovery drops 50%, capacity opens, the line on the contact-centre P&L shrinks.
Recovery handled with the right tone preserves the relationship. Today’s defaulter becomes tomorrow’s promise-to-pay, becomes next quarter’s top-up loan. Hard-recovery cohorts shrink. Lifetime value rises. The CMO and the CRO finally agree on something.
Channel mix, message tone, time-of-day and frequency self-tune against what actually produced a promise-to-pay last week. No quarterly retraining project. No vendor SOW for the next model. The recovery model the CRO inherits in Q4 is sharper than the one they signed off in Q1.
Payment history, bureau scores, contact transcripts, consent records and recovery actions held inside the residency boundary your regulator specifies. Field-level PII masking at ingestion, AES-256 at rest, TLS 1.3 in transit, consent honoured at every contact attempt. DPDP, RBI, IRDAI, SEBI, ISO 27001 and SOC 2 aligned by default.
Multi-tenant or dedicated hosting, auto-scaling and a 99.9% SLA. The fast path when time-to-value matters most.
Full deployment inside your own data centre. Complete data sovereignty, no third-party cloud dependency. The deployment regulators sign off without a redline.
Processing and storage split across an on-premise core and cloud edge, for mixed compliance needs across business units.
Granular RBAC across users, teams, channels and campaign types, with full audit logging.
Architecture aligned to the frameworks regulated enterprises are measured against.
Data held within specified geographic boundaries for GDPR, PDPA and RBI requirements.
Enterprise identity across every UNFYD module via your existing directory.
AES-256 at rest, TLS 1.3 in transit, end-to-end encrypted campaign payloads.
Active-passive DR with automated failover and an RPO under 4 hours across all modes.
UNFYD.KOLLECT is AI-powered collection automation that works from borrower behaviour across the full delinquency lifecycle rather than from a static risk band. It is one of the UNFYD Deep-Domain operating systems: the UNFYD.COMPASS platform configured for a specific industry rather than a generic product sold into it.
Static risk models, template-based outreach and rigid waterfalls. The strategy is set on Monday and the customer changes on Tuesday, so the same message goes out at month-end regardless of what has happened since.
Behavioural risk scoring decides who to contact, and channel and time optimisation decides how and when. Seven dialler attempts are not better than one well-timed message on the channel the borrower actually responds to.
Consent is managed as a first-class, versioned record and honoured at every contact attempt, with DPDP, RBI, IRDAI and SEBI guardrails built into the platform layer so an audit trail does not have to be rebuilt after a regulator asks.
Cloud / SaaS, on-premise or hybrid, with a 99.9% SLA, AES-256 encryption at rest, TLS 1.3 in transit, ISO 27001 and SOC 2 alignment, and disaster recovery with an RPO under four hours across all modes.
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