Using Analytics to fight Fraud, Anti-Money Laundering & Security Intelligence

SAS Analytics helps the below sectors to tackle fraud.

• Financial institutions make expeditious, on-target decisions to truncate the monetary, reputational, and compliance risks of fraud and money laundering.
• Retailers monitor millions of transactions and determine whether to flag or approve card purchases at the point of sale while abbreviating the chance of inconveniencing customers with mendacious alerts.
• Government agencies gain a broad view across multiple data sources – such as tax, health care, benefits, workforce, and public safety records – to denude fraud, waste, and abuse in regime programs.
• Insurance companies use entity analytics and network analysis to denude collusion and fixate on ceasing the most costly and malignant fraud networks.

How Analytics transforming sectors to tackle fraud

The adoption of analytics in financial malefaction compliance has grown significantly over the last decade, from being a “trend to watch” at the commencement of the decade, to experiments with the technology and pilots in more recent years. It has now been deployed in live operation in several banks. While still at early stages in moving toward full potential, its benefits are being optically discerned in genuine use cases.

Banks are utilizing incipient data sources to ameliorate fraud detection and cybersecurity, concretely for online banking. For instance, web session data can be habituated to profile users and find utilization patterns. This approach uses machine-engendered log data and message transmission from web sessions, (i.e. clickstream data) to understand the paths a utilizer takes when visiting websites. It can be used along with other anti-fraud approaches to identify actions that may designate fraudulent access, e.g. whether the payee for the incipient payment instruction is in line with antecedent patterns. The bank can then impose supplemental security validation checks.

The credit card fraud aversion industry has been at the forefront in terms of adopting machine learning,” verbalizes David Stewart, banking industry director for SAS Fraud and Security Astuteness. In the last few years, financial institutions, working with technology firms such as SAS, have expanded machine learning to gain a cross-channel view of deportment, often leveraging additional digital information about contrivances, geolocation, and biometric authentication.

Data and analytics are additionally availing financial firms more efficaciously fight money laundering, which is a growing threat as more connectivity is introduced to banking. “Firms are concerned with all these incipient and different technologies for holding and storing money. You can store money everywhere now—in a cloud or on your phone,” verbalizes John Gill, vice president of inculcation for the Sodality of Certified Fraud Examiners. “These technologies make it more facile for fraud or money laundering to transpire. There’s a whole underground connected network of fund movement, transactions, and accounts. Bitcoin and a plethora of those digital currencies keep people up at night because it authentically is not regulated.”