Leverage the Full Potential of Your Data for Credit Decisions
Take advantage of unique information contained in alternative data to improve your decisions. Alternative scorecards are models designed to use alternative data sources such as payment, telecommunication or utility data to assess the risk of customers. Incorporating alternative data into scoring models usually increases the proportion of customers covered by a reliable score and strengthens the predictive power of existing models. Creditinfo has demonstrated that the following alternative data sources boost the performance of scoring models.get in touch
How can alternative data support your business?
- Assess the creditworthiness of customers with little or no prior credit history.
- Identify new segments of unbanked prospective customers.
- Combine standard and alternative data to achieve the best performance.
- Improve the accuracy of profiling and segmentation of your portfolio.
There are two approaches to the development of alternative models depending on the use case and regulation:
These logistic regression models can be considered as an industry standard. They provide high robustness and interpretability.
These models (e.g. random forest, neural network, etc.) are more complex and thus they tend to have a higher predictive power and a lower degree of interpretability.
Facilitate Customer Acquisition
Alternative scoring will increase a pool of customers for whom you will be able to accurately assess risk.
Drive Financial Inclusion
By facilitating access to finance for segments of unbanked or underbanked customers.
Gain Competitive Advantage
By extracting valuable information from datasets unavailable to your competition.