AI – Powered Financial Statement Analytics and Finance Product Recommendation

Employing big data analytics and credit card propensity model to improve credit risk underwriting The main challenge that banks face when trying to market their services is targeting the correct potential clients. This is one of the reasons why you will encounter offers for credit cards which come with the most attractive terms and conditions, targeted at people who do not have the means to benefit from such an offer and do not actually need the card. The problem does not just stop here; as a result, some customers end up incurring a debt burden which is too large for them to afford, leading to default. Identifying patterns in transaction data, predicting if someone has what it takes to own premium reward credit cards, e.g., someone who travels a lot or high net worth individuals. Gathering banking datasets, especially those rare outliers, is extremely difficult, hence the paper employs the help of synthetic data. Presently, research concentrates on credit card propensity, with simplicity and accuracy being taken into account in the process. In short, this is a powerful tool for banking institutions which provides them with a highly sophisticated approach.