solutions fraud-detection 
AWS Machine Learning
AUGUST 11, 2022
Frauds could cause a significant loss for businesses and consumers. billion to frauds in 2021, up more than 70% over 2020. Many techniques have been used to detect fraudsters—rule-based filters, anomaly detection, and machine learning (ML) models, to name a few. Building such a solution, however, is challenging.
AWS Machine Learning
FEBRUARY 7, 2024
In the first post of this three-part series, we presented a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. Set up permissions that allows your AWS account to access Amazon Fraud Detector.
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AWS Machine Learning
MARCH 10, 2023
Online fraud has a widespread impact on businesses and requires an effective end-to-end strategy to detect and prevent new account fraud and account takeovers, and stop suspicious payment transactions. Detecting fraud closer to the time of fraud occurrence is key to the success of a fraud detection and prevention system.
24-7 InTouch
MARCH 6, 2024
In this blog, we will delve into the pivotal role of artificial intelligence (AI) in advancing cybersecurity, specifically focusing on fraud detection, and showcase how innovative solutions are essential in safeguarding the integrity of financial transactions. million by the year 2033.
AWS Machine Learning
MAY 24, 2023
In this three-part series, we present a solution that demonstrates how you can automate detecting document tampering and fraud at scale using AWS AI and machine learning (ML) services for a mortgage underwriting use case. These fraud attempts can be challenging for mortgage lenders to capture.
AWS Machine Learning
APRIL 17, 2023
As more businesses increase their online presence to serve their customers better, new fraud patterns are constantly emerging. Traditional rule-based fraud detection systems are capped in their ability to quickly iterate as they rely on predefined rules and thresholds to flag potentially fraudulent activity.
AWS Machine Learning
OCTOBER 10, 2022
In this post, we present a solution that combines rich mobile device intelligence with customized machine learning (ML) modeling to help you catch fraudsters who exploit mobile apps. This solution rides on a larger global wave of anti-fraud efforts, which experts forecast to grow to USD $62.70 billion by 2028. billion by 2028.
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