With advanced analytics, financial institutions and fintech companies predict the possibility of fraud to prevent it even before it happens. Simultaneously, they can scan transactions for traces of fraudulent activity. If they detect fraud, they can immediately detect any suspicious activity and take other actions, either manually or with the help of automation tools. By using machine learning techniques instead of using a rule-based approach, they gain the ability to detect the often subtle correlations between customer behavior and the potential for fraud.
It works by scanning documents to analyze metadata and information at the pixel level and ensure the integrity of the document. In addition, AI uses known legitimate documents (for example, bank statements from specific institutions) to find variations in fonts and designs. The report, entitled Smoothing the customer journey and preventing fraud, revealed that banking institutions consider AI and machine learning to be critical to preventing fraud in the future. So how do AI and machine learning work together to reduce the risk of fraud? According to Sammy Belose, an expert in ERP and business management software, AI and machine learning stand out when it comes to detecting financial fraud.
There are several different applications of AI for fraud detection in the financial services industry.
