Risk Manager

Job description

  • Ongoing analysis of the risks of the loan portfolio, monitoring of credit risks, key risk indicators, identifying new trends, analyzing cause-effect relationships, and developing measures to limit risks.
  • Improving the effectiveness of risky decisions.
  • Development of effective tools to control and monitor credit risks.
  • Preparation for management of analytical reports/presentations on the risks of retail lending, the quality of the loan portfolio, measures aimed at reducing risks.
  • Construction of various models (credit scoring, collection scoring, behavioral scoring, fraud scoring, etc.) and rules for assessing credit risks in making decisions. 
  • Monitoring call reports to make sure collectors are making enough phone contacts each day.
  • Identification areas of the collection process that need improvement and implements an enhanced process that will help collectors be more effective.
  • Oversee the collection of outstanding credit and invoices to minimize profit loss while ensuring it is handled appropriately and per company policy. 
  • Create and implement strategies to increase the number of successful collections on outstanding debt.
  • Customization, implementation, and testing of developed models and rules in the decision-making system.
  • Support for the performance of models and monitoring/evaluation of their effectiveness and quality.
  • Detection and analysis of credit fraud events, verification of incoming fraud signals and customer complaints.
  • Investigating credit fraud incidents.
  • Analysis of concentrations and anomalies for various risk indicators.
  • Conducting operational actions to prevent, detect and eliminate fraud.
  • Identification of new types of fraud, as well as participation in improving and finalizing; the process of fraud monitoring.
  • Making suggestions for improving business processes.

Job requirements

  • Higher education in mathematics/statistics, economics/finance, IT.
  • Possession of MS Office, Excel at the advanced user level (pivot tables, data tables, VBA, etc.).
  • Knowledge of high volume collections, credit authorization, and billing procedures and practices.
  • Ability to conduct statistical data analysis, vintage analysis.
  • Knowledge of risk analysis methods (scorcards, models).
  • Experience in analyzing large amounts of structured and unstructured data.
  • Knowledge of SQL.
  • Good knowledge of machine learning methods, experience with data analysis tools, and Python libraries.
  • High learning ability.
  • Analytical mind.
  • Ability to work with large volumes of data.
  • Stress resistance.
  • Skills and ability to visualize and present data.
  • Experience in risk management, retail lending will be an advantage.
  • Experience in risk assessment and automatic credit rating will be an advantage.