Curated Engineering Insights

Financial fraud is no longer a static problem. It is adaptive, automated, and increasingly powered by artificial intelligence. Traditional fraud detection systems, built on rules, thresholds, and retrospective analysis, are struggling to keep pace with modern attack patterns. This is where agentic AI for fraud detection is emerging as a transformational approach.

In the early days of AI, a lot of focus was on prompt engineering; writing short, smart instructions to get the right answers from language models. This worked well for simple tasks.  However, as we move into the era of Agentic AI solutions, where systems act with autonomy and reasoning, prompt engineering alone isn’t enough. What’s needed now is a structured approach to designing workflows, data flows, and decision logic.