More than 80 million new credit cards are expected to be issued worldwide; it is therefore not a surprise that credit scoring is essential on financial decision-making. Payment history is one of variables associated with credit scoring but our project, the Dual Credit Scoring one, strives to improve this by taking the spending habits as well into account. By using both the categorization of the user’s transactions (e.g., health, clothing, investments, etc.) linear structure from bank statements and the secondary score that we generate, we obtain new quantitative features of the financial activity and behavior’s characteristics. This system provides more insights about how the users manage their money and can be really helpful in assessing individuals who are “credit invisible” or do not have a promising credit history. This dual score system’s philosophy is powered by Artificial Intelligence (AI) and machine learning technology, thus providing a more detailed picture of the customer with an additional scoring system that adds value to the existing Traditional Credit Scoring system.