Tailored Solutions for Enhanced Decision-Making

Building credit scoring models utilizing credit bureau data, open banking and application scores is expensive and difficult and it is even more difficult to maintain them.

Data drift; concept drift and business performance is just a few of the issues that can occur.

RiskBite has it’s own developed credit scoring development process and engine to maintain scores.

RiskBite offer done-for-you service of building a credit score. RiskBite utilizes advanced

• Machine learning
• Credit bureau integrations (in Poland)
• AIS gate-away integration (in Poland)
• Automated feature calculations for affordability, income stability and more
• Reporting for data drift and concept drift for features in RiskBite Engine
• API access to model

• Analysis of the existing portfolio, credit criteria, and process structure – Evaluating the current state to understand performance and identify potential improvements.
• Recommendation of changes to credit criteria and processes – Proposing modifications to enhance loan approval processes and risk assessment.
• Implementation of additional anti-fraud criteria – Introducing new measures to detect and prevent fraudulent loan applications.
• Adoption of RiskBite scoring models for new and returning customers – Utilizing advanced scoring models to evaluate customer creditworthiness more accurately.
• Provision of a decision engine as a web service – Delivering real-time, fully automated decision-making capabilities through a web-based application.
• Ongoing support for model maintenance and quality monitoring – Ensuring the continued effectiveness and reliability of scoring models through regular oversight.
• Periodic consultations on portfolio KPIs and risk mitigation – Regularly reviewing key performance indicators to recommend strategic changes aimed at reducing risks and/or increasing acceptance rates.

• Existing Portfolio and Process Analysis – Evaluating the current state of the portfolio, credit criteria, and operational processes to identify areas for improvement.
• Recommendations for Credit Criteria and Process Adjustments – Proposing changes to refine credit criteria and streamline processes based on our comprehensive analysis.
• Anti-Fraud Criteria Implementation – Introducing additional, robust anti-fraud measures to strengthen security and mitigate risk.
• Long-Term Risk Assessment Model – Developing and implementing a model to estimate long-term risk levels at the client level, ensuring sustainable risk management strategies.
• Real-Time Decision Engine – Providing a web service-based decision engine that operates fully automatically, enhancing real-time decision-making capabilities.
• Ongoing Model Maintenance and Quality Monitoring – Continuously supporting the maintenance and quality assessment of all models to guarantee their effectiveness.
• Periodic KPI Consultations and Risk Management – Regularly consulting on key performance indicators (KPIs) and recommending strategic adjustments to reduce risks and/or increase acceptance rates.

• Portfolio Analysis – Conducting thorough analyses of current portfolios to identify performance trends and areas for improvement.
• Risk Assessment Data Enrichment – Enhancing the data set used for risk assessments with new, more comprehensive sources to improve accuracy and predictive quality.
• Statistical Scoring Model Construction – Building tailored statistical models that effectively score and rank the risk associated with different elements of the portfolio.
• Decision Engine Provision and Maintenance – Supplying and maintaining a dedicated decision engine that supports real-time decision-making, ensuring it remains robust and effective over time.