Predict Customer Behaviour.Cut Three Cost Lines at Once.
Every customer-behaviour scorecard VT Risk deploys is engineered against three measurable cost lines — the cost of the risk you assume, the operational cost of acting on it, and the personnel cost of resolving it. The score is not the deliverable. The reduction is.
−15%
Cost of risk, first quarter
−28%
Operational cost
−40%
Manual intervention
8 wks
To production
One Scorecard. Three Cost Lines.
A customer-behaviour prediction model is a cost-reduction instrument only when it is measured against the cost lines it moves. VT Risk designs every engagement against all three.
−15%
Cost of risk, first quarter
Cost of Assumed Risk
Provisioning, write-offs, and roll-forward losses fall when delinquency is predicted early and intervention is timed to the moment it still changes the outcome.
−28%
Collections operational cost
Operational Cost
Cost-per-decision and cost-per-collected-euro fall when worklists are ranked by expected net recovery and channels are matched to responsiveness — not applied uniformly.
−40%
Manual intervention volume
Personnel Cost
Agent minutes per resolved case fall when self-curers are routed to automation and human capacity is concentrated on high-value, high-uncertainty accounts.
Customer-Behaviour Prediction, Priced by Cost Saved
Each solution is mapped to the three cost levers it moves — so the business case is stated in euros saved, not in model accuracy.
Debt Collection Behaviour Scorecard
Scores every delinquent and pre-delinquent account by payment propensity, self-cure likelihood, and roll-forward risk — 30 days before deterioration is visible in the ledger.
−15% cost of risk
Early-warning scoring enables preventive contact 30 days before roll-forward, reducing 30→60 DPD migration and forward provisioning.
−34% cost-per-euro
Worklists ranked by expected net recovery value cut cost-per-collected-euro and eliminate low-value outreach.
−40% manual touches
Self-curer segment routed to automated digital nudges; agents handle only high-value, high-uncertainty cases.
Propensity-to-Pay Scoring
Real-time ranking of each delinquent account by likelihood to pay within 7–30 days, paired with the channel and timing most likely to elicit payment.
+31% recovery
Recovery is pulled forward in the cycle, shortening days-in-delinquency and reducing loss-given-default on marginal accounts.
−38% cost-per-contact
Contact strategy is optimised per debtor — channel, tone, frequency — cutting cost-per-contact by 30–40%.
+45% agent output
Agents work only the highest-probability, highest-value contacts first; agent productivity rises 28–45%.
Delinquency Early-Warning & Roll-Rate Forecasting
Predicts which current accounts will migrate into delinquency, and how the portfolio will roll across buckets — feeding provisioning, staffing, and strategy.
−15% cost of risk
Stage-transfer and provisioning are calibrated to a forecast roll curve, not a lagging actual — tightening IFRS 9 accuracy.
−25% cost-per-prevention
Pre-delinquency intervention costs a fraction of post-due-date collections; the forecast targets it precisely.
−20% staffing variance
Staffing is planned to forecast workload curves, smoothing peak headcount needs and overtime.
Churn & Balance-Attrition Predictor
Identifies customers at high risk of leaving 60–90 days before they do, paired with the retention triggers most likely to hold them profitably.
−10% attrition
Revenue-base erosion and the credit risk embedded in attriting balances are caught before they realise; lifetime value is preserved.
−30% retention spend
Retention spend flows only to accounts where NPV of retention is positive — no blanket discounts to customers who would stay anyway.
−25% retention FTE cost
Retention teams focus on value-preserving saves, not volume callbacks.
Credit Limit Optimiser
Recommends per-segment limit increases or decreases, balancing revenue upside against the default risk that an over-limit exposure would create.
−12% expected loss
Limits are right-sized to behavioural risk, not to a blanket policy — reducing expected loss on the marginal limit increase.
−35% review cost
Limit reviews are automated by score; manual underwriting is reserved for genuinely borderline cases.
−30% underwriting FTE
Underwriting capacity is freed for complex exposures; routine decisions are automated.
Acquisition Propensity Model
Ranks prospects by probability of conversion and expected lifetime value, so acquisition budget flows to the prospects it will actually win profitably.
−18% new-customer default
Onboarding decisions incorporate behavioural risk from the first touch, not after the first missed payment.
−30% cost-per-acquisition
Acquisition spend is allocated by expected value, cutting cost-per-acquisition on low-probability prospects.
+22% sales productivity
Sales capacity is directed to high-conversion prospects; sales productivity rises.
How the Market Sells This — and What's Missing
Bureau scorecard vendors sell a score. Cost-reduction consultancies sell a programme. VT Risk delivers the engine and the operating-model change as one engagement.
FICO, Experian, TransUnion, CRIF
Sells: A score. A standalone risk metric delivered to the institution's analytics team to read and act on inconsistently.
Strength
Robust, well-validated scores; broad market adoption.
The Gap
The score rarely reaches the operating decision in real time; the institution still owns the integration, the workflow change, and the cost transformation — and pays separately for each.
VT Risk Edge
VT Risk ships the score wired into the operating decision — routing, offer, limit, contact — so the score changes the action by design, not by committee.
McKinsey, BCG, Bain, Oliver Wyman, Big 4 practices
Sells: A programme. A diagnostic, a target operating model, and a multi-quarter transformation roadmap — delivered as advisory, not as a working system.
Strength
Strong on operating-model design, benchmarking, and change management.
The Gap
No production scoring engine, no live data pipeline, no API into the core. The recommendations live in slides; the institution is left to source and build the technology that delivers the savings.
VT Risk Edge
VT Risk delivers the engine and the operating-model change together — full production in 8 weeks, first actionable scores in week 3, measured savings from the first month.
Generic collections CRMs, diallers, rule engines
Sells: A workflow. A system of record and a queue manager, with rules-based prioritisation and manual review.
Strength
Good operational tooling; fast to deploy for standard processes.
The Gap
No behavioural model; the queue is ranked by balance and days-past-due, not by expected recovery. The bottleneck — manual review of low-signal alerts — is preserved, not removed.
VT Risk Edge
VT Risk replaces rules with explainable behavioural scoring, so the queue is ranked by value and the bottleneck is engineered out, not staffed around.
Why the Combined Model Wins
VT Risk is what you get when a bureau-grade scoring engine and a cost-transformation programme arrive in the same engagement — measured from the first month, not the final slide.
Cost Reduction, In Production
Every figure below is a measured outcome from a live VT Risk deployment — not a projection.
See Your Three Cost Lines Move
In a 30-minute session, we map your portfolio against the three cost levers — cost of risk, operational cost, personnel cost — and show you which scorecard moves which line, and by how much, in your first quarter.
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