SME Credit Fraud Modeling — Master Thesis (Stockholm)

Qred; Stockholms kommun; On-site; SEK 36,000 - 47,000; Full time

Benefits offered by this job

Computer

Office access

SEK 20,000 compensation

Job summary

Qred is seeking a Master’s thesis student to join the risk analytics team in Stockholm on-site from January 2027 to June 2027. The project focuses on detecting first-party fraud in SME lending by analyzing historical loan data and engineering features for predictive modeling.

The role involves developing and validating a predictive model, documenting findings, and delivering robust risk assessment insights to support credit decisions.

Qualifications

• Master thesis project in risk analytics or related field.
• Experience with data analysis and modeling preferred.
• Availability Jan 2027 – Jun 2027 and on-site in Stockholm.

Responsibilities

• Data Analysis: Analyze historical loan and repayment data to uncover behavioral patterns of intentional first-payment defaults.
• Feature Engineering: Create variables that distinguish intentional fraudsters from honest customers in financial distress.
• Model Development: Develop a predictive model that integrates the newly engineered features.
• Validation and Testing: Validate the model to ensure accuracy and robustness.
• Documentation and Reporting: Document the analysis, findings and model results.

Skills

Data analysis

Feature engineering

Predictive modeling

Documentation

Education

Master student in a relevant field

Job description

Qred is seeking a Master’s thesis student to join the risk analytics team in Stockholm on-site from January 2027 to June 2027. The project focuses on detecting first-party fraud in SME lending by analyzing historical loan data and engineering features for predictive modeling.

The role involves developing and validating a predictive model, documenting findings, and delivering robust risk assessment insights to support credit decisions.