FiVerity and NCFTA jointly issue a security bulletin on more effective ways to combat synthetic identity fraud
FiVerity, a leading provider of machine learning solutions for cyber fraud detection and threat intelligence, today unveiled its Collaborative AI Platform, a machine learning solution for detecting and preventing cyber fraud. The new FiVerity Platform will benefit from involvement of the National Cyber-Forensics and Training Alliance (NCFTA) as a research partner. Several major banks and credit unions are adopting the solution to combat synthetic identity fraud, or SIF, the fastest growing type of fraud.
FiVerity’s new Collaborative AI Platform reflects the growing realization among financial services, government agencies, and law enforcement, that a broader, well-coordinated and more collaborative approach is needed to address the growing SIF problem. With its advanced machine-learning capabilities, the Platform uses pattern matching rather than consumer personally identifiable information (PII) to share intelligence about fraudsters between participants, including banks and credit unions.
To broaden awareness and spotlight the growing SIF problem, NCFTA and FiVerity jointly published a security bulletin today on this specific type of cyber fraud. Entitled ‘Advisory on Synthetic Identities used by cyber-criminals to infiltrate financial institutions," the advisory outlined the specialized tactics that SIF fraudsters use. It also highlights how the new Collaborative Platform, with its public-private partnership, is a significantly more effective way to fight cyber-crime. To access the bulletin, click here.
"Public-private collaboration, and better communication and information sharing between financial services companies, industry regulators, and law enforcement agencies is the only effective way to fight SIF and other rapidly evolving types of cyber fraud," said Matt LaVigna, CEO of NCFTA. "The FiVerity Platform seeks to bring several great weapons to this fight. It gets everyone past the old PII roadblock, and it leverages but greatly improves upon legacy rules-based methodologies. We are looking forward to working with FiVerity as a new research partner in the fight against today’s well-funded and fast-moving bad actors.
According to the Federal Reserve, SIF has become the fastest-growing type of cyber fraud in the financial sector, projected to cost the industry more than $20B in 2020 and account for over 20% of all credit losses. In SIF schemes, criminals combine real and fake data to create new, fictitious identities which they use to open accounts, applying for loans and other forms of credit. The blending of real and falsified information makes this form of fraudulent activity difficult and time consuming to detect. In addition, SIF fraudsters often use automation tools to generate thousands of phony identities, fraudulent accounts and loan applications, overwhelming banks’ prevention efforts.
"We’re very pleased to see our machine learning solutions detecting more than 35% of previously undetected SIF on a stand-alone basis at financial institutions, which can only improve through industry collaboration," said Greg Woolf, founder and CEO of FiVerity. "While SIF is a great example of the type of complex and difficult problems that collaborative machine learning can solve, it’s only one of many cyber fraud challenges facing financial institutions. We’re just getting started on solving them."
The FiVerity Platform serves as the central resource for the Collaborative AI Platform. Under the program, participating banks, credit unions, and other financial services companies will submit customer account data – minus any consumer PII – to the Platform. The applications are instantly scored with the levels of risk, giving financial institutions retail lending digital account opening departments a faster and more thorough ways to reject high-risk applications, steer questionable ones to deeper reviews, and conversely, fast-track high-quality, low-risk applications for rapid approval. Meanwhile, the FiVerity Platform uses proprietary machine-learning capabilities to learn from the patterns it sees in each application, improving its knowledgebase of fraud techniques and tactics for continual improvement in prevention and detection capabilities.
At present, the Collaborative AI Solution program is in its initial pilot phase. In addition to the involvement of the NCFTA, approximately 20 banks and credit unions now in varying stages of engagement and testing. After the initial phase has been completed, the Collaborative AI Solution will be opened-up for broader industry and government agency participation.
The National Cyber-Forensics and Training Alliance (NCFTA) is a 501(c)3 public benefit non-profit founded in 2002, focused on identifying, mitigating, and disrupting cybercrime threats globally. The NCFTA was created by industry, academia, and law enforcement for the sole purpose of establishing a neutral, trusted environment that enables two-way information sharing. Through the NCFTA, private industry and government work together toward neutralizing cyber threats in a neutral, trusted environment (www.ncfta.net).
FiVerity develops and markets AI and machine learning solutions that detect sophisticated forms of cyber fraud and deliver actionable, proactive threat intelligence. The company’s products meet the unique requirements of financial institutions, including banks, credit unions, and credit card providers. The company’s solutions help financial institutions strengthen, streamline, and scale their consumer-facing business processes, such as application processing, credit verification, and customer onboarding (www.fiverity.com).
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