What are the most effective credit scoring methods?

1 Traditional credit scoring

Traditional credit scoring methods rely on historical data from credit bureaus, such as payment history, credit utilization, length of credit history, types of credit, and new credit inquiries. These data are used to calculate a numerical score that reflects the probability of default or delinquency. The most widely used traditional credit scoring model is the FICO score, which ranges from 300 to 850. Traditional credit scoring methods are simple, standardized, and transparent, but they also have some drawbacks. For example, they may exclude or penalize people who have limited or no credit history, or who have experienced financial hardship or identity theft. They may also be slow to adapt to changing economic and social conditions, and may not capture the full picture of a borrower's financial situation and behavior.

2 Alternative credit scoring

Alternative credit scoring methods use non-traditional data sources, such as utility bills, rent payments, bank transactions, social media activity, mobile phone usage, and psychometric tests, to evaluate a borrower's creditworthiness and risk profile. These data are often processed by advanced analytics and machine learning techniques, such as neural networks, decision trees, and random forests, to generate a score or a classification. Alternative credit scoring methods aim to overcome some of the limitations of traditional credit scoring methods, such as data scarcity, bias, and rigidity. They may also provide more granular, dynamic, and personalized insights into a borrower's financial situation and behavior. However, alternative credit scoring methods also face some challenges, such as data quality, privacy, regulation, and explainability.

4 Future credit scoring

Future credit scoring methods are emerging or potential credit scoring methods that may leverage new technologies, data sources, and techniques to further improve the credit scoring process and outcomes. Some examples of future credit scoring methods are blockchain-based credit scoring, which may enable more secure, transparent, and decentralized data sharing and verification; biometric credit scoring, which may use physical or behavioral characteristics, such as fingerprints, facial recognition, or voice analysis, to identify and authenticate borrowers; and gamified credit scoring, which may use interactive and engaging elements, such as quizzes, puzzles, or simulations, to measure and influence a borrower's financial literacy, personality, and behavior. Future credit scoring methods may offer more innovative, efficient, and inclusive ways to evaluate and enhance a borrower's creditworthiness and risk profile, but they may also pose new ethical, legal, and social issues and challenges.

5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?