Credit scoring model development: customer and risk assessment from €30,000

Scoring helps you decide quickly who to give a loan, instalment plan or access to, based on data rather than intuition. We build a model for your product: from rules to machine learning.

Software development and automationTimeline: from 3 months, after the architecture session

How it looks

Credit scoring is a way to estimate the probability that a customer will repay money or meet their obligations. Each borrower gets a score based on their data: income, payment history, application form. A model is needed by online lenders, instalment providers, fintech services and companies that offer customers deferred payment. This is a case where mistakes cost money, so the model should be built deliberately.

Rules, statistics or machine learning. You can start with simple rules: age, income, length of employment. Once history accumulates, statistics and machine learning come in, finding hidden relationships in the data.
The decision stays with you. The model provides a score and an explanation, while you set the approval policy and thresholds together with a risk specialist.

Approximate display: images and texts are chosen as an example. In your project the features, design and architecture will be different, built for your goals.

Exampleapproximate view

Software development and automation · timeline from 3 months, after the architecture session

Scoring and mathematical models — from €30 000

A model that scores customers and risks using clear rules, statistics and, where needed, machine learning. We start with an architecture session to define the data, criteria and scope of work.

For duck.credit we built a fintech online lending service: scoring, customer verification (KYC), a personal account and a CRM. Scoring there is embedded in the whole chain from application to decision. If you need not only the calculation but the whole platform, see the fintech platform page. See also: fintech platform.

We show prices and stages in advance. The model, code and data belong to you, and infrastructure costs €0 at the start (Cloudflare, GitHub, Supabase, Resend). We explain the model's decisions in plain language, without a "black box" where possible. Your country's regulatory requirements for scoring models and personal data processing are checked by your lawyer.

Good for: fintech companies and lending services · Businesses that need to assess customer or application risk · Teams with accumulated data but no model

Order scoring and mathematical models Compare the category packages →

What a €30,000 scoring model development includes

One price for the whole list: no extra charges for hours or individual items.

Scoring and mathematical models start from €30,000, and work begins with an architecture session for €3,500, which is credited toward the project. The project includes data preparation and cleaning, model building, quality checks on a holdout sample, decision rules and connecting the model to your service. See also: architecture session, integrations with your systems.

Data preparation and model building. We assemble features, check data quality and build the model, most often logistic regression as an understandable baseline, and more complex methods when needed.
Validation and monitoring. We check how the model performs on new data and set up quality tracking so you notice when it becomes outdated.

1Product map and design

Architecture session (€3 500)We define goals, data, criteria and the estimate. The result stays with you, and €3 500 is credited toward the project.

2Development

Data preparationWe collect, clean and check the data. A model is only as good as its data.
Rules and statisticsWe build clear criteria and scales. Simple rules often work no worse than a complex model.
Machine learning, if it is justifiedWe train a model and compare it with simple rules. We choose whatever is more accurate and easier to understand.

3Review

Quality testingWe test the model on a separate sample and describe its limits. You know where it can be trusted.
Connection to your systemWe embed the model in your CRM or service. An application gets a score in seconds, and the decision stays with the employee.

4Launch and handover

Monitoring dashboardWe watch for the model drifting over time. Warning signs are visible right away.
Documentation and handoverWe hand over the model description, code and access. You are not dependent on us.

Approximate display: images and texts are chosen as an example. In your project the features, design and architecture will be different, built for your goals.

Can be added to the project

Optional, now or later. The price is fixed before work starts.

We work with companies from the EU, the US, Kazakhstan and other countries. The dataset, permitted features and explainability requirements depend on the market, so at the architecture session we discuss separately which data can be used. See also: admin panel for application decisions.

Analytics and reportsReports on scores, decisions and rejection reasons in one place, with no manual spreadsheets.from €590Details
Reports on scores, decisions and rejection reasons in one place. Useful when you want to understand how the model works in practice.
Timeline: 1–2 weeks
SupportWe monitor operation, make backups, install updates and make improvements according to an agreed plan.individualDetails
After launch we look at what the system needs: what to monitor, how often to update, which improvements are planned. We name the monthly price in advance. There is no hourly billing.
Timeline: after launch
Model review on dataWe check the model's quality on new data and update the rules so that scoring does not go stale over time.+ from €1 990Details
We take the data accumulated over the period, compare the model's decisions with actual outcomes, and adjust the rules. Useful when several months have passed and conditions have changed.
Timeline: 2–3 weeks
External customer verification (KYC)We connect a document verification service so the customer's identity is checked before scoring, not after.+ €990Details
We connect the identity verification service you choose to the scoring process. Useful when the law or your partners' rules require verification. The client pays for the service itself.
Timeline: 1–2 weeks

Paid separately, not by us: purchase of external data and service subscriptions · Regulatory and legal opinions on the model: from your lawyers. All add-ons →

How we work

How a scoring model is built: the stages

The steps switch automatically, or click any of them to read more.

First we define the goal: whom we count as a "bad" customer and over what horizon. Then we collect data, calculate indicators, build several variants and compare them. The final model comes with a description: what data it uses, how it calculates the score, where its limits are. If you have little data, we will say honestly that it is better to start with rules and accumulate history. See also: CRM for your processes, dedicated team.

What we need from you. An export of historical customer data and their outcomes, a description of the product and risk policy, access to the person responsible for decisions.

1. Brief

A short 15-minute questionnaire: what the business is, who it is for, what you need and by when. By voice, text or a call.

We ask only what affects the result and the price
Materials (logo, photos, texts) can be sent later
We reply the same business day: what we offer, what it costs and how long it takes

Start the brief →

How long15 minutes of your time

Resultan offer with a price and a deadline

Questions

FAQ

How much does scoring model development cost?

From €30,000. We start with an architecture session for €3,500, which is credited toward the project. The final price depends on data volume and model complexity.

What is credit scoring?

A method of assessing a customer from data: they are given a score showing the probability of repaying a debt. The higher the score, the more reliable the customer.

How do you build a credit scoring model?

Define who counts as a bad customer, collect historical data, choose features, train the model, test it on new data and embed it in the decision process.

Why is logistic regression so often used?

It is simple, fast to compute and easy to explain: you can see how each feature affects the score. This matters for audits and for communicating with the customer. We add more complex methods when they give a noticeable gain.

What does scoring model validation mean?

Checking that the model works not only on the data it learned from but also on new data, and stays stable over time.

What if I have little data?

Then we start with rules and careful data collection, and build a full model once history accumulates. We will say so honestly at the architecture session.

Does the model decide on the loan?

The model calculates a score and gives an explanation. You define the approval policy, thresholds and manual review.

Who owns the model?

You do: the documentation, code and trained parameters.