YOUR UNDERWRITERS SPEND 70% OF THEIR TIME ON DATA ENTRY

004 seconds. That's how long UWflow takes to score an application.

How does your current process behave? That gap is adverse selection leaking into your P&L. UWflow closes it with Bayesian rigor, WOE precision, and constrained logistic models — every decision fully explainable to your regulator.

LIVE SCORING ENGINE 4ms avg
// The Cost

Every day your underwriting is manual,
you're paying for adverse selection.

The average European insurer loses €18–24M annually to mispriced risk in mortgage and personal lines. Manual scoring can't see the patterns. It can't adapt. It can't explain itself to the ECB.

70%
Time on data entry
4.2hr
Avg decision time
0
Decisions replayable
// How It Works

Three Steps. Zero Black Box.

Every decision explainable. Every weight traceable. Regulators will thank you.

STEP 01

Transform

WOE binning converts raw features into monotonic, interpretable signals.
Chi-Merge and Decision Stump optimization. No arbitrary thresholds.

STEP 02

Score

Constrained logistic regression with Bayesian posterior estimation. Business constraints baked in. Coefficients you can defend to a committee.

STEP 03

Prove

Deterministic state-graph replay. Reproduce any decision at any point in time. Full audit trail. Your compliance team stops dreading model reviews.

// The Proof

Numbers, Not Adjectives

Metric Traditional UW UWflow
Decision time 4–72 hours <10ms
Variables evaluated 15–40 200+
Adapts to market shifts Quarterly (if lucky) Continuous
Decision replayability "Trust me, it's in a spreadsheet" 100% deterministic
Regulatory explainability Heuristic, black-box Weight-level trace
Risk reduction (pilot) — 28–34%
// Under the Hood

Scientific. Not Magical.

Built by actuaries who got tired of watching spreadsheets replace judgment.

Bayesian Posterior

Not just a score — a distribution. Every prediction carries calibrated uncertainty. Your committee sees the range, not just the point.

WOE + Optimal Binning

Chi-Merge and Decision Stump binning. Raw features become monotonic signals. No arbitrary cut-points. No "actuarial intuition" required.

Constrained LR

Logistic regression with business constraints. "Age must be positive" isn't a prompt — it's a hard constraint in the optimizer. Defensible by construction.

Ensemble Interaction Discovery

Boosting methods find feature interactions LR alone misses. "Age × LTV × region" — the three-way interactions that actually drive default.

State-Graph Replay

Every decision is a path through a state graph. Reproduce it. Challenge it. Prove it. Your auditor gets a timeline, not a shrug.

API-First Integration

REST, gRPC, or batch. Drops into your core banking, CRM, or decision engine. Your team's process doesn't change — the quality of the decision does.

// Try It

90 Seconds. Real Logic. No Slides.

Watch the engine think. See every weight. Replay the decision.

UWflow LIVE WALKTHROUGH · 1:23 Real data → Real score → Full decision path replay
Read the source AIDflow v3.0.11 · FSL-Apache
// Next Step

Your portfolio is already priced
on the wrong model.

We'll run 500 applications from your book through UWflow. You get the score distribution, the factor contributions, and a one-page risk gap report. Free. No obligation. No sales call.

AIGENSYS s.r.o. · Bilkova 855/19 · Prague 1 · Czech Republic [email protected] Response within 24h · No spam · NDA available on request