It is widely used in credit scoring and risk assessment, because it provides more accurate evaluations of a customer’s creditworthiness. Therefore, fintech companies see a reduction in default rates and better lending decisions. Moreover, ml is crucial in fraud detection and prevention. It detects fraudulent activities in real-time, therefore reducing financial losses.
Another exciting application is in personalized recommendations. pakistan telegram data Thus, having collected customer information, fintech companies can provide customized products. As indicated by cornerstone advisors’ 2024 report, ml was adopted in only 2% of banks in 2019, and that figure has risen to 16% in 2024. Natural language processing Natural language processing (nlp) powers chatbots and 24/7 virtual assistants.
Thus, customer queries are resolved more quickly. This improves overall customer satisfaction. Nlp also powers sentiment analysis, which helps fintech companies gauge market sentiment and make informed investment decisions. By analyzing customer feedback, firms can enhance risk management strategies. Additionally, nlp aids in compliance and regulatory analysis, automating the process and reducing costs while ensuring faster regulatory reporting.