Making Faster, Smarter, and Fairer Lending Decisions
Our advanced credit scoring services provide Kenyan lenders with the power to make instant, data-driven, and highly accurate lending decisions. In a competitive market, moving beyond manual assessment to automated, predictive scoring is no longer an option—it's a necessity. A credit score is a numerical representation of a borrower's creditworthiness, enabling institutions to approve loans faster, price risk more accurately, and manage their portfolio more effectively. Swipe Recoveries Experts Ltd develops, validates, and deploys custom credit scoring models for banks, MFIs, and digital lenders, ensuring compliance with the Data Protection Act and delivering a tangible competitive edge.
The Legal and Technical Foundations of Credit Scoring
The implementation of credit scoring services in Kenya must be balanced between innovation and regulation. The primary legal consideration is the Data Protection Act, 2019, and the guidelines from the Office of the Data Protection Commissioner (ODPC). Any credit scoring model that uses personal data must have a lawful basis for processing, be transparent with the data subject, and ensure the data is secure. This is especially critical when using alternative data sources beyond traditional CRB reports.
Technically, a robust credit score is built on a foundation of clean, relevant data. We leverage a combination of sources:
Traditional Data: Information from Credit Reference Bureaus (CRBs) provides the historical backbone of a person's credit behaviour.Alternative Data: This is where modern scoring finds its edge. We ethically incorporate data from mobile money transactions (e.g., M-Pesa), utility payment histories, and even psychometric assessments to build a more holistic profile, which is crucial for thin-file or no-file customers.Internal Data: The lender's own historical data on loan performance is a goldmine for building a predictive model.
Our data scientists use statistical techniques like logistic regression and advanced machine learning (AI) algorithms to identify the variables that most accurately predict the likelihood of default. The entire process is documented to ensure model fairness, explainability, and full compliance with Kenyan law.
Our Process: Developing Your Custom Credit Scorecard
Developing a powerful, custom credit scorecard is a collaborative and systematic process. Swipe Recoveries Experts Ltd guides you through every step.
Phase 1: Data Strategy and Collection. We start by identifying all available and permissible data sources. We work with you to consolidate your historical loan performance data and establish secure connections to external sources like CRBs and alternative data providers.
Phase 2: Model Development and Validation. Our data scientists clean and prepare the data, then use a portion of it (the 'training set') to build the scoring model. We test thousands of variables to find the most predictive combination. The model is then rigorously tested on a separate 'validation set' of data it has never seen before to ensure its predictive power is real and not just a fluke. We measure performance using industry-standard metrics like the Gini coefficient and KS statistic.
Phase 3: Calibration and Policy Integration. The raw score is then calibrated to produce a simple, actionable output (e.g., a score from 300-850). We work with you to define score cut-offs for different actions: for example, a score above 700 might be an automatic approval, 600-699 might require manual review, and below 600 might be an automatic decline. This 'policy matrix' integrates the scorecard directly into your lending operations.
Phase 4: Deployment and Monitoring. The model can be deployed via a secure API for real-time scoring or used for batch processing. We continuously monitor the model's performance over time to ensure it remains accurate as market conditions change, a process known as 'model drift' monitoring.
Investment and Pricing for Credit Scoring Solutions
Investing in custom credit scoring services is a high-ROI strategic decision. It reduces default rates, lowers operational costs through automation, and enables faster market response. Our pricing is structured based on the complexity and scope of the project.
A full, end-to-end custom model development project typically involves a one-time project fee. This can range from KES 750,000 to KES 3,000,000+, depending on the number of data sources, model complexity (statistical vs. machine learning), and integration requirements. This provides you with a proprietary credit scoring model that is your intellectual property.
For lenders who prefer a service-based approach, we can host the model and provide access via an API. In this scenario, pricing is often on a per-API-call basis, for example, KES 50 to KES 250 per score requested. This model provides flexibility and reduces the upfront investment. We work with each client to determine the most suitable and cost-effective structure.
