Credit is everywhere. Though it's often pitched as a modern corporate invention, credit is nothing new. In fact, it's built into our very history.
People have been lending and selling on credit since the heyday of Babylon and the Roman Empire, right through to 19th century England, when lenders started to compare notes about consumers who failed to pay their debts. As time went on, credit systems became more standardized, which gave way to credit reporting agencies. and increasingly sophisticated ways of tracking consumer credit. From detailed analog ledgers to comprehensive credit scoring models, technology has gradually changed the landscape of credit reporting. Modern credit scoring came about as a more objective way for lenders to distinguish between credit-worthy consumers and those who were less likely to pay their debts on time, if at all.
Credit reporting agencies gather and report on the credit and payment history of a consumer using traditional logistic regression. A three-digit credit score is calculated based on this history. These three digits are designed to predict a specific consumer behavior, such as the likelihood a consumer will pay their debts on time, or whether the consumer is likely to go bankrupt within days. two years.
While credit scores vary based on the scoring model a lender chooses, a higher score usually correlates with a better risk profile, and thus better terms and offers. But consumers are more than the sum of their credit scores, and and lenders realized this. Up until now, potential creditors, lenders, and other companies, such as rental or insurance companies, have lacked a true 360-degree view of a consumer's creditworthiness. This information asymmetry may disadvantage individuals like college students with limited credit histories, or people outside the credit system, like recent immigrants who may only have a credit history in their home country. While traditional credit scoring methods take only a point-in-time snapshot of a consumer's credit standing, advancements in analytics and technology allow us to take a deeper look.
With the advent of big data and machine learning, we now have the power to create a more comprehensive portrait of consumers who might otherwise be considered risky or have limited traditional credit reports. We can now pull data from alternative sources and analyze patterns and trends to extract more data. more meaningful insights about a person's financial profile. In the future, the credit industry will develop even more precise methods to help paint a more complete financial picture of an individual. Big data continues to grow exponentially, while the continued development of machine learning and neural networks will enhance our ability to mine that data for valuable insights.
Blockchain and biometrics will transform identity management, helping to reduce the risk of fraud and its devastating impact. impact on the credit industry. And dynamic new algorithms will make limited traditional credit scoring models a thing of the past. With these advancements on the horizon, the credit game is changing and new players are coming to the field. Using big data, advanced analytics, and modern technology, lenders can leverage new opportunities to meet the evolving financial needs of consumers and gain a true 360-degree view of the modern consumer.