Olger Hasa

I focus on SAS, SQL and Python using logistic regression, decision trees and machine learning for developing IRB-compliant probability of default (PD) models. Conduct data analysis to identify trends, patterns, and relationships in retail loan portfolios, and make recommendations for risk management strategies and actions. Develop and implement statistical models for credit risk assessment in retail lending portfolios, including credit scorecards, application scoring models and behavioral scoring models.

I was responsible for assessing the creditworthiness of prospective tenants and property lessees, relying on thorough financial analysis, credit reports, and historical payment records. Analyzed credit risk of potential tenants with high-risk scores and contributed to keeping the rent default rate under 5%. Continuously seeking opportunities for process improvement and risk mitigation strategies. Applying data analysis to spot tenant payment behavior patterns, improving risk assessment and decisions

Developing and fine-tuning pricing models and strategies, considering factors such as vehicle types, customer segments, geographical regions, and demand fluctuations. Ensuring the precision of demand forecasts and pricing models, minimizing forecasting errors to enhance revenue and profitability. Conducting in-depth competitive market analysis to stay ahead of market trends, identify opportunities, and respond to pricing and promotional initiatives

Examining data and competitive rates to set rental prices that are attractive to customers and profitable for the company. Continuously checking how our prices are doing and making adjustments when needed. Helping develop pricing plans that work for different customer groups and market conditions.