Freelance projects

Freelance projects

Development and training of a credit scoring model for a financial company

Databases & SQL, Python — incorrectly specified categories?

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1. Project Objective

Develop a credit scoring model for predicting the solvency of clients with three target classes:

repayment within 30 days;
repayment within 60 days;
default.

2. Output Data

Data from credit applications, client questionnaires, and UBKI.
Access to data via PostgreSQL queries.
Mandatory: include financial data from UBKI.
Do not use: scoring indicators from UBKI due to high correlation with the target.

3. Target and Model Requirements

Target: 3 classes (30_days_paid, 60_days_paid, default).
Model: AutoGluon (Python).
Minimum accuracy: 70% (for binary classification).
Optimization metric: macro F1-score (for three classes).
The model must support binary and three-class classification.

4. Business Requirements

The model must consider different categories of clients and assist in making decisions regarding the approval of applications with regard to an acceptable level of risk:

For new clients: expected application approval rate — about 8%, with a maximum allowable default rate — up to 30%.
For repeat clients: expected application approval rate — about 45%, with a maximum allowable default rate — up to 10%.

Such indicators should serve as a benchmark for tuning the model and assessing its effectiveness in real business conditions.

5. Technical Requirements

The model must support updating / retraining.
Provide metrics: accuracy, precision, recall, F1-score, ROC-AUC.
Validation: stratified k-fold (k ≥ 5).
Must provide:
- feature importance,
- SQL queries for dataset formation,
- feature description,
- instructions for retraining.

6. Expected Results

Model file (.pkl or .model).
SQL queries for dataset formation.
Report with metrics, analytics, and result graphs.
Instructions for deploying and retraining the model

Deadline by 14 calendar days from the moment of access to the database

Proposals 4

Konstantin Kuzmichev

0 0

Projects -
Rating -
Rating 164

Budget: 27000 UAH Deadline: 10 days

I have 20 years in development. I have developed various systems including forecasting. I have worked with different models: LSTM, RandomForest, XGBoost, MLP, and others. I have experience in developing large projects with a large volume of data (Deutsche Bank and Oracle Field Service Cloud). I would be happy to discuss the details.

Illia Antipiev

63 2

Budget: 6000 UAH Deadline: 10 days

Hello
I am ready to complete your project
I can consider different types of models (tree, mlp, clustering) and choose the best one
I will provide code for retraining and a report on the work

Roman Z.

7 0

Budget: 1000 UAH Deadline: 1 day

Good day!
My name is Roman, and I am among the top 5 developers in the category of "Artificial Intelligence and Machine Learning" among ~1600 specialists on the platform.
I guarantee:
- Fast and quality execution of the task
- Strict adherence to deadlines
- Regular communication throughout the entire process
I would be happy to discuss the details of your project in private messages.

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