Internet fraud continues to be a menace to society, especially in healthcare and financial institutions. Many fintech companies have been victims of fraud. Detection of these attacks comes via two paths: through inconsistent traditional methods or using ever-growing artificial intelligence (AI) mechanisms. Entrepreneur brought this interesting information to us in their article, “How AI and Machine Learning Are Improving Fraud Detection in Fintech.”
Traditional methods, such as the rule-based method, are still widely used by most fintech companies instead of AI. Some companies are adjusting, however, by leveraging machine learning and AI, greatly improving their chances of detecting fraud.
Some of the potential solutions to fintech fraud issues are obvious and available today. Once addressed industrywide, fintech can access a seemingly endless set of features, functions, and benefits. Instead of constantly being one step behind, fintech companies can actively foresee fraud, embracing AI and machine learning techniques and thereby safeguarding their financial integrity.
Understanding the technology will be key. Most organizations have little knowledge regarding how AI systems make decisions, and they are ill-prepared to apply any results they obtain from these technologies. Explainable AI allows users to comprehend and trust the results and output created by machine learning algorithms. Why is this important? Because explainability becomes critical when the results can have an impact on data security or safety.
| Data Harmony is an award-winning semantic suite that leverages explainable AI. |
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Melody K. Smith
Sponsored by Access Innovations, the intelligence and the technology behind world-class explainable AI solutions.
