See repayment risk building before a payment is missed.
Continuous monitoring of transaction, balance and repayment behavior that flags borrowers whose repayment risk is rising, signals portfolio deterioration, and prioritizes who to contact first.
For illustrative purposes only
Origination analytics decide who to lend to. Cashflow Servicing watches what happens after that decision, working at two levels at once: portfolio-level deterioration signals across segments and vintages, and borrower-level repayment risk with a prioritized queue of who to contact first. The result is visibility into repayment trouble weeks before a scheduled payment is actually missed.
Monitoring is calibrated per lending product, because repayment patterns, servicing context and treatment options differ by product.
For consumer lending, ongoing monitoring runs across cash advance, personal loans, BNPL, credit cards and lines of credit, auto, overdrafts and debt consolidation, with deterioration and repayment models calibrated to each product's own repayment pattern.
For business lending, the same monitoring applies across invoice financing, term loans, lines of credit, business credit cards, equipment finance, merchant cash advance and working capital, aligned to each product's own loan tape and servicing context.
One borrower, twelve weeks. The pattern that precedes a missed payment is usually visible well before the due date.
Income deposits: on time at weeks 2 and 4, missed at week 6, partial or late at weeks 8, 10 and 12.
Repayment risk flag, probability to pay the next instalment, and the signals behind it.
Deterioration signals by segment, vintage and product.
A prioritized queue: who to contact first, and the suggested treatment.
For illustrative purposes only
A persisted data connection keeps the view current between payments, not just at application.
A persisted connection to ongoing account and repayment behavior
Bank transactions
Balances
Payment history
Loan tape and schedule
Servicing context
Prior outreach outcomes
Cashflow Servicing
Monitoring and action models
Repayment risk flag
Probability to pay
Next best action
Want to see how portfolio and borrower-level signals turn into action before a payment is missed?
Flags, alerts and prioritized queues are delivered by API or batch into your servicing systems. Carrington Labs does not contact your customers or set treatment policy: you decide what action is taken.
LMS
CRM
Portfolio analytics
Decision engine
Scorecard
Origination platform
You retain full control of outreach timing, channel and treatment policy: Carrington Labs surfaces the signal, your servicing team decides the response.
Your DPD buckets, payment-failure retries and collections triggers activate once a payment has already failed. A persisted data connection surfaces deterioration in transaction and balance behavior in the weeks before that failure, so outreach can start earlier in the cycle.
A single flag rarely has enough context. Every output arrives with where it sits in the portfolio and where it ranks in the action queue, so no alert has to stand alone.
Every alert carries signals and a suggested next best action, so servicing teams know why a borrower surfaced and what to do.
The signals are behavioral and forward-looking, which is what makes contact possible weeks before arrears rather than at the point a payment fails.
Each step below keeps monitoring current as your portfolio and your outcomes evolve.
01
Transaction, balance and repayment data is connected on an ongoing basis, de-identified.
02
Monitoring is aligned to your repayment schedules and servicing context.
03
Deterioration and repayment models are calibrated to your portfolio and your treatment outcomes.
04
Flags, alerts and queues are returned by API or batch into your LMS, CRM and portfolio reporting.
05
Prior outreach outcomes feed back in, so prioritization improves as you act on it.
Early warning is assessed retrospectively on loans that have already run: apply the models to historical behavior and measure how far ahead of the missed payment the alert would have raised, and what share of eventual arrears would have been flagged. Lead time and capture rate are the two numbers that matter, and both are measured on your portfolio.
Lead time and capture rate are measured retrospectively on your own loan history; figures shown are illustrative. Alert volume is not a fixed rate: it is tuned to the review capacity your team sets.
Explainability, lender control and data handling built into every deployment.
Every risk flag returns its contributing signals in plain English, so your team can see why an account was surfaced.
Carrington Labs flags and prioritizes. Contact, hardship handling and treatment decisions remain entirely yours.
Monitoring runs on the account, transaction and repayment activity you already hold post-origination, within the terms of your agreement. No new data collection is required, and no personally identifying fields are needed to raise a flag.
Each early-warning signal carries the account activity that triggered it, so servicing and risk teams can see exactly why an account was surfaced before contacting the borrower.
Risk flags, payment probabilities and next-best-action queues are delivered by API or scheduled batch into your loan management system, CRM or portfolio analytics dashboard, whichever your servicing team already works from.
A back-test on your own loan history measures lead time and capture rate against your current process, before anything is deployed.
Leave your details below and our team will schedule a call to discuss your business and how Carrington Labs can help.
