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Key Challenges for Adoption of AI Fraud Detection Technology

Many businesses that are aware of the risks related to online fraud wonder if they should begin with an AI machine learning solution or if they would be better off introducing incremental solutions first, assuming that machine learning is too technologically sophisticated for their current state.
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If one conducts business online, it's important to understand your responsibility — to one's organization, one's customers, and one's stakeholders — to mitigate digital fraud.
AI is increasingly being developed for detecting and preventing fraud, ideally before it occurs. Nevertheless, two major obstacles prevent many businesses from implementing advanced AI fraud detection technology:
Insufficient Data Infrastructure to Support Machine Learning
Big Data has become a top priority for major digital players such as Google and Facebook, and they have the infrastructure to support it. However, this is not the case for Main Street USA. Many small to medium-sized businesses that are just getting started with their online presence are not completely aware of the threats they could face online and may even believe they are too small to be noticed by a cyber-criminal.
To be sure, these companies likely collect information about their customers, website traffic, and social media engagement. However, they may lack the data infrastructure required to evaluate user activities and behaviors in order to develop a baseline understanding of what fraud looks like. Because AI and machine learning "learn" from data, a lack of data to feed the system can stymie the learning curve, particularly in the case of supervised machine learning.
Many businesses that are aware of the risks related to online fraud wonder if they should begin with an AI machine learning solution or if they would be better off introducing incremental solutions first, assuming that machine learning is too technologically sophisticated for their current state.
The Comparitively New Entrance of Traditional Businesses in the Online Space
Traditional businesses have had fraud prevention and detection policies in place for many years, but those safeguards were not designed for the digital world. Traditional businesses are working to find their footing in a new world, one with rapidly evolving threats and challenges, as digital transformation accelerates across a broad swath of industries and the increasingly digital nature of customer interaction.
Online fraud is sophisticated, complicated, and constantly changing. As a result, it necessitates a proactive rather than a reactive response. Traditional businesses that are dipping their toes into the online space for the first time must change their mindset and method.
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