Using Big Data from the Deep Web for Financial Compliance, Fraud Detection & Fraud Prevention
In our last posting, we featured two case studies on how our customers are using Big Data from the Deep Web in the insurance and risk management industries. In this post, you’ll learn how customers in the financial service industry are using Web data to help understand exposure to risk and better develop initiatives for institutional compliance related to ‘Know Your Customer’ (KYC).
Financial Service Provider Compliance and Deep Web Big Data
The mandatory requirements of ‘know your customer’, commonly referred to as simply KYC, came about because of the U.S.A Patriot Act passed in October of 2001. Regulations required financial service providers to establish anti-money laundering programs to help prevent any inadvertent facilitation of money laundering.
So how does using open source, publicly available Web data help support financial institutions and other groups in its KYC and anti-money laundering initiatives? Collecting data at large scale from thousands of sources is only half the battle. You then have to analyze the data and identify and target red flag indicators that may imply an individual country risk, potential exposure to corruption or other risks associated with compromised accounts.
As an example, red flag indicators regarding compromised account fraud range from postings of compromised account credentials or credit cards, to news identifying new methods being used for fraud across all open sources, including social media, blogs, and message boards. The major advantage of going directly to open sources for red flags that update in real-time is it allows us to provide breach event alerts to our customers in near real-time as well.
Want to learn more about our KYC and fraud detection initiatives?
Use the link below to speak with our Vice President of Business Development, Tyson Johnson, and discuss how OSINT collection can support your Risk Management requirements.
//
Photo: the black pearl (Flickr)
