While
Florida’s program will be the first targeted on youth education, awareness
campaigns have become a critical component of the fight against this $150 billion
industry,
which impacts as many as 40.3 million people
annually.
The Department of Homeland Security’s Blue Campaign is one example. This national public awareness campaign is focused on increasing detection of human trafficking and identifying victims.
Increasing detection of victims
The
campaign works to educate the public, law enforcement and industry partners to
recognize the indicators of human trafficking, and how to appropriately respond
to possible cases.
“Every online communication between
traffickers, ‘johns,’ and their victims reveals potentially actionable
information for anti-trafficking investigators.”
The study noted the potential for integrating human experts and computer-assisted technologies like AI to detect trafficking online.
AI and human trafficking
Similar research conducted at Carnegie Mellon University looked at how low-level traffickers and organized transnational criminal networks used web sites like Craigslist and Backpage to advertise their victims. The researchers developed AI-based tools to find patterns in the hundreds of millions of online ads and help recover victims and find the bad actors.
The conference brought together researchers, policy makers, social scientists, members of the tech community, and survivors.
One of those researchers – from Lehigh University – is working on a human trafficking project to help law enforcement overcome the challenges of turning vast amounts of data, primarily from police incident reports, into actionable intelligence to assist with their investigations.
Providing better alerts and real risks
Former Federal government officials share the optimism about the power of AI to aid law enforcement in weeding out the criminals and finding the victims.
“For
example, law enforcement can look at young women of a certain age entering the
country from certain high-risk jurisdictions. Marry that up with social media
and young people missing from home, or people associated with a false
employment agency or who think they are getting a nanny job, and you start to
develop a complete picture. And the information can be brought up all at once,
rather than an analyst having to go through the Dark Web.”
To report suspected human trafficking to Federal law enforcement, call 1-866-347-2423.
To get help from the National Trafficking Hotline call 1-888-373-7888 or text HELP or INFO to BeFree (233733).
Learn more
about AI-powered Radiance and its risk sensing capabilities for issues like human trafficking.
While commonly maligned as one of the laggard industries when it comes to technology, insurance companies are increasingly investing in AI and machine learning across all aspects of their business.
Carriers Investing $5+ million on AI Annually
A study
by Genpact found that 87 percent of carriers are investing more than $5
million in AI every year. This is more than both banking (86%) and consumer
goods and retail companies (63%).
Two practical applications for this technology – claims and underwriting fraud – provide opportunity to help solve some of the industry’s biggest challenges.
Solving the Fraud Issue with Tech and AI
Fraud
is estimated to be more than $30 billion every year in the U.S. alone.
And, according to the Coalition
Against Insurance Fraud, 2018 was the third consecutive time in six years that
insurers reported increasing amounts of fraud. Nearly three-quarters of
insurers reported that fraud had increased either significantly or slightly, an
11-point increase since 2014.
To address this issue the Coalition’s survey reinforced
Genpact’s findings: nearly two-thirds of insurers planned to acquire new
technology in the next year for enhanced detection of claims fraud, and another
one-third would add technology to address underwriting fraud.
Deloitte further notes that among the areas that will see the greatest impact are fraud detection and risk analysis. Beyond these important use cases, AI and machine learning assist with customer due diligence, augmenting existing processes with analysis of external data sources.
Transformation to ‘Predict and Prevent’
The power of AI, according
to experts, is its ability to analyze mass amounts of data from a wide
range of sources including previous claims, customer information, and social
media, to help combat fraud.
A senior data scientist at AXIS Capital recently
noted that 80 percent of internal data is unstructured in the form of PDF
and emails, and that AI’s text mining and natural language processing could
help reveal core hidden information.
Additionally, she pointed to AI’s ability to scrape
information from the Internet, gathering information in real time to understand
evolving risks.
With these capabilities, AI can transform the industry, and underwriting in particular, into the ‘predict and prevent’ mode.
McKinsey recommends that as insurers onboard these technologies, they take a multi-pronged strategy that begins with getting smart on AI-related technologies and trends and includes the development and implementation of long-term technology plan.
Comprehensive Data Strategy
The firm also underscores that AI technology performs best with a high volume of data from multiple sources, and that carriers must develop a comprehensive data strategy. Internal data will need to be organized in ways that enable and support the agile development of new analytics insights and capabilities. With external data, carriers must focus on securing access to data that enriches and complements their internal data sets.
The Radiance Solution
Radiance is a powerful tool to help identify potential fraud and other concerns. It ingests and processes large amounts of unstructured data, providing actionable, prioritized results that can be further refined by entering publicly-available identifiable information.
Radiance’s deep web
listening goes beyond traditional social media monitoring tools, using
internally-developed and proprietary algorithms to capture online content
relevant to insurance fraud.
Radiance can apply the same machine learning capabilities against existing legacy databases, integrating those disparate sources and analyzing that data against risk and other industry specific needs.
Insider threat incidents range from data security breaches which have cost firms like Capital One as much as $100 – $150 million to violent threats from disgruntled employees, like the case of Coast Guard Lieutenant Christopher Hassan who was arrested after a joint Coast Guard and FBI investigation found he was stockpiling weapons and seeking to launch a major attack.
Every Organization is Vulnerable
While these high-profile incidents grab international headlines, the reality is that every organization is vulnerable to insider threats. On average, insider threats cost almost $9 million, take more than two months to contain and include issues related to careless workers, disgruntled employees, workplace violence and malicious insiders.
As part of National Insider Threat Awareness Month this September, the National Counterintelligence and Security Center (NCSC) is reminding companies of the need for strong insider threat protection programs and the signs to look for with existing employees.
Look for These Concerning Behaviors
William Evanina, who heads up NCSC, shares that those individuals engaged or contemplating insider threats display “concerning behaviors” before engaging in these events.
financial difficulty or unexplained extreme change in finances; and
job performance problems.
Early Detection Technologies
The Center suggests deploying solutions for monitoring
employee actions, correlating information from multiple data sources, having
tools for employees to report concerning or disruptive behavior, and monitoring
social media.
Surveys like the one conducted by Crowd Research Partners
show more and more organizations are increasingly using behavior monitoring and
similar methods to help
with early detection of insider threats.
And, a report from Accenture found that while advanced identification, security intelligence and threat sharing technologies are widely adopted, automation, AI and machine learning are now being used by about 40 percent of companies.
Costs Savings from AI Automation
According to the same report, once investment costs are considered, AI automation could offer the highest net savings of about $2 million and begin to address the shortage in skilled security staff.
Following the Common Sense Guide to Mitigating Insider Threats
Companies looking to follow the CERT National Insider Threat Center’s guidelines, should consider how the Radiance platform can help with monitoring social media, correlating disparate information, and providing a tool for employees to report concerning behaviors.
Radiance
OS-INT monitors all publicly available information across the entire deep
web, not only social media. And, it can
ingest massive amounts of unstructured content from disparate internal data
sources for further correlation and verification.
Radiance’s
HUM-INT platform, known as S4, is a mobile application that allows users to
confidentially report concerns in real time.
It can be configured as a workplace tool, with a centralized management
portal to allow clients to access real–time threats to geo-fenced facility
locations.
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