Using spatiotemporal datasets relating to weather & natural disasters allows fraud detection experts in the insurance industry to identify fraudulent claims faster, reducing the strain on their inspector networks.
Whether it’s roof repair, vehicle damages, crop fraud or flood impact – our Data Observatory allows you to enrich with data from providers such as WeatherSource with just a few lines of code.
CLICK HERE to read the FULL Fraud Detection Machine Learning with GIS – CARTO article.
THE TD BANK INSIDER “BRIBE-FOR-DATA” SCHEME (USA)
Date: February 17, 2026 Perpetrator: Edward Low (Former Bank Employee)
Case Description: In a high-profile case of “Insider Threat,” Edward Low, a former employee of TD Bank in New York, pleaded guilty in a New Jersey federal court to accepting bribes in exchange for confidential customer data. Between 2021 and 2022, Low leveraged his internal access to harvest the personal details of high-balance account holders. He then sold this “hot data” to external fraud syndicates for as little as $26,700 in personal kickbacks.
The external fraudsters used the information Low provided to conduct “Account Takeovers” (ATO), creating fraudulent checks and falsifying bank records to drain over $500,000 from unsuspecting customers. Low even went as far as helping co-conspirators open shell company accounts at a second financial institution where he was later employed. He now faces a maximum penalty of 30 years in prison. This case has sent shockwaves through the global banking sector, highlighting that even the most robust external firewalls cannot protect against a “rogue insider” with administrative credentials.
Link to Original: US Dept of Justice – TD Bank Insider Plea