--- title: Building Robust Credit Scoring Models (Part 3) | daily.dev description: Part 3 of a credit scoring model series focuses on data preprocessing: handling outliers and missing values in borrower data using Python. It covers creating a... canonical: https://daily.dev/posts/building-robust-credit-scoring-models-part-3--kwlzqkx9i twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: Building Robust Credit Scoring Models (Part 3) | daily.dev og:description: Part 3 of a credit scoring model series focuses on data preprocessing: handling outliers and missing values in borrower data using Python. It covers creating a... og:url: https://daily.dev/posts/building-robust-credit-scoring-models-part-3--kwlzqkx9i og:image: https://api.daily.dev/og/posts/kWLzqKX9i.png og:image:alt: Building Robust Credit Scoring Models (Part 3) og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # Building Robust Credit Scoring Models (Part 3) **[Towards Data Science](https://daily.dev/sources/tds)** · 18 min read · 0 upvotes · 0 comments ## Summary Part 3 of a credit scoring model series focuses on data preprocessing: handling outliers and missing values in borrower data using Python. It covers creating a synthetic time variable for train/test/OOT splits, applying stratified splitting to preserve default rate and temporal structure, treating outliers with the IQR method and winsorization, and imputing missing values using conservative strategies (MAR vs MCAR mechanisms). All preprocessing parameters are computed on training data only and then applied to test and OOT sets to prevent data leakage. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Building Robust Credit Scoring Models with Python](https://daily.dev/posts/building-robust-credit-scoring-models-with-python-avvk552gx) · Towards Data Science · 1 upvotes · 0 comments - [How to Build an Acquisition Credit Scorecard in Python \(Step by Step\) in 2026](https://daily.dev/posts/how-to-build-an-acquisition-credit-scorecard-in-python-step-by-step-in-2026-hyohrj6sm) · Medium · 0 upvotes · 0 comments - [How to Train a Scoring Model in the Age of Artificial Intelligence](https://daily.dev/posts/how-to-train-a-scoring-model-in-the-age-of-artificial-intelligence-ns6kgmudc) · Towards Data Science · 0 upvotes · 0 comments - [From Raw Data to Risk Classes](https://daily.dev/posts/from-raw-data-to-risk-classes-qye2zmgfs) · Towards Data Science · 1 upvotes · 0 comments - [How to Detect and Handle Outliers in Python](https://daily.dev/posts/how-to-detect-and-handle-outliers-in-python-9lb3li1la) · Medium · 0 upvotes · 0 comments --- Tags: [#python](https://daily.dev/tags/python), [#data-analysis](https://daily.dev/tags/data-analysis) [View this post on daily.dev](https://daily.dev/posts/building-robust-credit-scoring-models-part-3--kwlzqkx9i) ```json {"@context":"https://schema.org","@graph":[{"@type":"Organization","@id":"https://daily.dev/#organization","name":"daily.dev","url":"https://daily.dev","logo":{"@type":"ImageObject","url":"https://daily.dev/apple-touch-icon.png","width":180,"height":180},"sameAs":["https://twitter.com/dailydotdev","https://github.com/dailydotdev","https://www.linkedin.com/company/daily-dev-ltd"]},{"@type":"WebSite","@id":"https://daily.dev/#website","url":"https://daily.dev","name":"daily.dev","publisher":{"@id":"https://daily.dev/#organization"},"potentialAction":{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https://daily.dev/search?q={search_term_string}"},"query-input":"required name=search_term_string"}}]} {"@context":"https://schema.org","@type":"TechArticle","headline":"Building Robust Credit Scoring Models (Part 3)","url":"https://daily.dev/posts/building-robust-credit-scoring-models-part-3--kwlzqkx9i","mainEntityOfPage":{"@type":"WebPage","@id":"https://daily.dev/posts/building-robust-credit-scoring-models-part-3--kwlzqkx9i"},"datePublished":"2026-03-20T15:03:23.620Z","dateModified":"2026-03-20T15:23:57.841Z","description":"Part 3 of a credit scoring model series focuses on data preprocessing: handling outliers and missing values in borrower data using Python. 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