A few years ago, machine learning and artificial intelligence were only performing backstage to deal with the enormous amount of data available online. But, now, these two technologies have acquired the front stage to interact directly with people through AI-powered chatbots and software. Be it healthcare, finance, travel, banking, or IT, they are there in almost every industry.
From helping businesses to get useful insights, build powerful strategies for the future, deliver unmatchable customer experiences to increase customer base, and improve sales, AI and ML are offering much more than that. Another key benefit machine learning renders to various industries is to prevent them from fraud detection.Yes, machine learning in fraud detection is aiding businesses to tackle security issues efficiently.
Fraud detection and prevention are the main concerns in many industries, mainly eCommerce, finance, and banking. Machine learning together with artificial intelligence can help these sectors to keep various types of frauds at bay. Read this article to know the same:
How machine learning models and algorithms work to detect frauds?
Here are the ML algorithms that facilitate fraud detection:
Based on predictive data analysis, this type of algorithm is the most common way of applying machine learning for fraud detection. To train the algo, one has to feed and label information as good and bad. However, it cannot detect frauds that occur outside of the historical data sets.
This type of ML algorithm stores data related to the crucial group parameters. Based on those parameters, it defines patterns that further detect spam or fraud.
An unsupervised learning model can detect the strange behavior in the transactions. After training, the algorithm looks for the specific patterns in the data to determine fraud in transactions.
This kind of algorithm makes software or machine to automatically verify behavior in a particular context. Reinforcement learning algos train themselves from the environment to find out risks in the transactions.
[Related Blog: How to Leverage AI in Brand Safety and Counterfeit Detection ]
Why machine learning is used for fraud detection?
- It acts fast to assess users’ behavior and make real-time decisions.
- ML systems are capable of dealing with large datasets to label them as good or bad.
- Machine learning is an efficient technique to do data analysis in less time.
- Technology brings accurate results.
How does a machine learning system work?
Machine learning systems follow a systematic approach to find loopholes to prevent scams or frauds. Here is how it works:
Input data -> fetch features -> build and train an algorithm -> create an ML model
When a customer places an order or makes a transaction, the ML system creates features such as the identity of the customer, their order history, method/mode of payment, location of the customer, network, and more. These features are then analyzed to generate an ML model to predict the risk score. To know more about the process or develop such a process, contact an ML or AI app development company right away.
Use cases of machine learning in fraud detection
Machine learning together with artificial intelligence is capable of processing avast amount of data to define patterns that help businesses to avoid fraud. Here are some of the real-life cases where ML and AI help in fraud detection:
- Capgemini, a multinational consulting and technology company, uses an ML fraud detection system that can raise the accuracy by 90% and minimize the fraud investigation time by 70%.
- Feedzai also uses an ML-based detection system to spot and prevent 95% of frauds.
- Other popular corporations, such as Yelp, Jet.com, Airbnb, etc., are relying on various AI-based solutions to deal with data-related problems like account takeovers, abusive content, fake accounts, and more.
Machine learning and artificial intelligence provide a plethora of benefits to industries that are more prone to frauds and scams. Using ML-based algorithms businesses such as eCommerce, online gaming, finance, banking, and more can prevent fraud. The technology analyzes and processes data to find out patterns that can automatically detect if there is some strange behavior or activity. To know more about how ML and AI works, read this complete article. On the contrary, if you want to develop an ML-based app or software that can help you improve your fraud detection system, then hire ML/AI developer or reach out to a reliable ML company.