Overview
Sirma is a leader in delivering AI-driven solutions specifically designed for financial institutions. These solutions help organizations meet stringent regulatory requirements while enhancing their risk management processes. For financial institutions, effective risk management and compliance with Basel standards are essential. Sirma provides advanced machine learning models for predicting the Probability of Default (PD) and Loss Given Default (LGD). These models are vital for accurate risk assessment and play a key role in calculating Economic Capital and Risk-Weighted Assets (RWA) in full alignment with the Basel Risk framework.
The Challenge
Financial institutions face growing complexities in managing credit risk under Basel frameworks, which require precise quantification of risk factors influencing capital allocation. Regulatory expectations tighten the need for transparency, accuracy, and governance in risk models, while data heterogeneity, evolving economic scenarios, and compliance pressures pose significant hurdles. Traditional statistical models often struggle to capture complex, nonlinear relationships in risk factors and fail to adapt dynamically to new information. Banks require scalable, explainable, and robust ML solutions that not only meet Basel compliance but also improve decision-making speed and accuracy under regulatory scrutiny.
The Project Scope
The project focused on developing and deploying sophisticated machine learning (ML) models specifically designed to ensure compliance with Basel regulations, which mandate the strict assessment and management of credit risk. Core objectives included:
- Utilizing historical loan and default data to train predictive models that generalize well across portfolios;
- Ensuring model design and implementation adhered strictly to Basel regulatory standards and audit requirements;
- Facilitating integration with existing risk management systems for real-time capital calculation and reporting;
- Addressing interpretability and transparency to satisfy regulatory validations and internal governance;
- Supporting ongoing model retraining and performance monitoring to adapt to market and portfolio changes.
The Solution
Leveraging our deep understanding of Basel regulatory requirements, Sirma engineered ML models that combine advanced algorithms such as gradient boosting, neural networks, and ensemble learning, tuned for financial risk data. Comprehensive feature engineering extracted predictive signals from borrower profiles, macroeconomic indicators, and transaction histories. The models were embedded within a secure and scalable architecture, supported by explainability tools that provide transparency into model decisions for compliance purposes. The solution also incorporated automated data validation and governance layers, ensuring data quality and regulatory audit readiness.
Results
The implementation yielded measurable improvements in the client’s risk management capabilities:
- Highly accurate PD and LGD predictions, reducing capital misallocation and enhancing risk sensitivity;
- Full Basel compliance with audit trails and documentation satisfying regulatory authorities;
- Accelerated risk reporting cycles enabling timely capital adequacy assessments and stress testing;
- Enhanced risk stratification capabilities supporting better credit decision-making and portfolio optimization;
- Reduced operational burden on risk management teams through automation and integration.
Technologies
The project employed a robust technology stack combining:
- Machine learning frameworks such as TensorFlow, PyTorch, and XGBoost are tailored for financial data;
- Data engineering tools for preprocessing large-scale historical and real-time loan datasets;
- Explainable AI (XAI) frameworks to provide interpretable model insights for governance;
- Secure cloud infrastructure ensuring compliance with data protection regulations;
- APIs enabling seamless integration with existing Basel reporting and risk systems.
Sirma’s Relationship with Client
We simplify regulatory challenges by blending our expertise with AI technologies to ensure compliance with evolving standards. Sirma partners with financial institutions to promote collaboration and innovation. Our deep understanding of Basel requirements enables us to develop reliable models for critical parameters. By leveraging historical data and advanced machine learning, our solution helps banks make informed decisions on credit risk, optimize capital allocation, and meet regulatory obligations. Our approach includes joint governance and regular model reviews, reinforcing Sirma’s role as a trusted partner in risk management transformation.
