Using AI to Fight Fraud

Platforms are the new frontier for fraud

Cybercrime and customer fraud are presenting challenges across many industries. And the frontier for many organizations has become online platforms: social media, e-commerce, and service sites.

Incidents of fraud may have negative financial impacts, but their could be other undesired consequences as well. Investigations occupy an organization’s limited resources, and fraud can lead to compliance risk and reputation risk.

Advisors are using AI to detect fraud

However, new tools are being used by professionals today to fight fraud. Artificial intelligence is already being used for fraud detection in various industries, including finance, insurance, and e-commerce.

In these industries algorithms use machine learning techniques to identify patterns and anomalies that indicate fraud. The algorithms create models from historical data and continuously update their models to improve their accuracy over time. They may also incorporate additional data sources, such as social media activity, to improve their fraud detection capabilities.

Results of using AI to fight fraud

It's important to note, however, that AI is not a silver bullet for fraud detection. Generally, AI is used to create a fraud score that represents the probably that a transaction is fraudulent or that an account is high risk. There are also challenges associated with ensuring accuracy, avoiding bias, and protecting data privacy.

Companies must carefully design their AI systems and regularly monitor their performance to ensure that they are detecting fraud effectively and ethically.

Learning more about AI

If you want to start learning about the fundamental concepts in artificial intelligence, here are a few steps you can take:

1. Start with the basics: Before diving into advanced topics, it's important to understand the basic concepts of AI. Some of the fundamental concepts include machine learning (mentioned in this post), deep learning, neural networks, natural language processing, and robotics. CPAs familiar with data analytics can start by learning the basics concepts of machine learning.

2. Read industry publications: To stay up-to-date on the latest developments in AI, it's helpful to read industry publications such as the Journal of Accountancy, the Harvard Business Review, MIT Technology Review, and Forbes. These publications often have articles that explain AI concepts in a way that's easy to understand for non-engineering professionals.

3. Attend conferences and webinars: Attending industry conferences and webinars that include content about AI is a great way to learn about the latest trends and innovations in the field. You can network with other professionals at your level and learn from experts in the industry.

4. Take online courses: There are many online courses that teach AI concepts specifically for accountants and finance professionals. Some popular online learning platforms include Coursera, edX, and Udemy. You can take courses on topics such as AI for financial forecasting, AI for fraud detection, and AI for risk management.

5. Join AI groups and communities: Joining AI groups and communities can help you stay connected with other professionals in the field. You can share ideas, ask questions, and learn from others' experiences. LinkedIn is a great platform to connect with AI groups and communities.

Remember that learning about AI is an ongoing process. The field is constantly evolving, and it's important to stay up-to-date with the latest developments to remain relevant in our profession.