How Wells Fargo Uses AI, Biometrics To Fight Money Laundering

“’The fact that [customers are] connected to the internet of things opens the door to the broader spectrum of payment activity. That allows us to do is to build deeper profiles, [which AI can use] to better predict if [a transaction] is something [the customer] would do,’ Monroe said.

This influx of new data means banks must look beyond authenticating login credentials. Users’ payment histories, how they hold their phones and type in their passwords, as well as other factors should be considered during the authentication process.”

AI Advancements Are Making It Easier to Hack Biometric Systems

  • “Though the methods above are tricky for a hacker to complete, artificial intelligence could end up making the process of stealing your identity much easier. Researchers at New York University have created a tool that can generate fake fingerprints to unlock mobile devices.
  • Even more so, researchers have demonstrated how deep artificial neural networks can be trained over time to recreate faces, or just create faces in general. What is stopping someone from using these same tools to access your world?”

DataVisor CEO, an AI expert, to Address Stanford University’s Global Women in Data Science Conference on the Use of Machine Learning to Combat Online Fraud

  • “DataVisor was founded with an ambitious vision, by Xie and co-founder Fang Yu, DataVisor CTO. The company’s mission is to stop fraudsters in their tracks and to restore online trust with the help of big data and machine learning.
  • Xie will present DataVisor’s quarterly Fraud Index Report, which takes a deep dive into the current cyber fraud landscape, based on sample data gathered by the company’s Global Intelligence Network from 44-plus billion events that took place across 800-plus million active user accounts in Q4 of 2018.”

From virtual assistants to anti-money laundering tech, AI is transforming banking

“PelicanSecure brings together tools that use natural language processing and machine learning to analyse patterns of behaviour to flag up “subtle anomalies” pointing to instances of fraud.

Factors like user location, spending patterns and unusual device configuration are all integrated into Pelican’s detection system.

Describing the role AI has to play in turning the tide against scammers, CEO Parth Desai says: “Traditional fraud detection methods are reactive in nature, meaning if a fraudster came up with a new idea to defraud an organization, the existing rules will fail to prevent it.

“AI, on the other hand, predicts those behaviours and protects against trending and future fraud typologies.

“AI, including machine learning, is unquestionably the future of fraud detection. Financial institutions are shifting towards AI gradually.

‘We believe the industry is still in the launching phase of this technology and that there is a lot more to explore over the course of the coming few years.'”

AI Changing The Face Of Digital Advertising

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  • “With an increased digital consumption the world is creating massive amounts of data on a daily basis. According to Domo’s Data Never Sleeps 5.0 report, there are 2.5 quintillion bytes (1 million terabytes) of data created each day! And it is estimated that a staggering 1.7MB of data will be created every second for every person on earth by 2020.
  • Ad fraud is so rampant that nearly 30% of the ad budget lay waste owing to such fraudulent activities. Seemingly impossible for humans, AI can keep an eye on the bots in real time to find fraudulent patterns.
  • The changes that AI has brought and will bring in digital marketing are huge. The AI market in digital marketing is set to grow at a compounded annual growth rate of around 30% globally to reach USD 40.09 billion by 2025, according to estimates by Markets&Markets. This growth will be fuelled by Asian giants such as China, India, Japan, and South Korea.”

Singapore goes AI: training, incentives and regulation

“Earlier this year, both the United Overseas Bank (UOB) and the OCBC Bank in Singapore announced their intent to invest in training sessions in AI for their staff.

In a recent note entitled “Is AI the next revolution in retail banking?”, UBS strategist Philip Finch revealed that the new technology could lead to a 3.4% revenue uplift and cost savings of 3.9% over the next three years. The figure was based on an UBS Evidence Lab survey of 86 banks.

Improving P&L statements with AI

Another business potential of AI comes in credit assessment. UOB is now able to run credit processing and credit decisioning by using a data-enriched AI-powered credit decisioning tool.

Preventing fraud

According to early tests conducted by the bank, the technology developed by ThetaRay could help OCBC reduce the number of transactions reviewed by anti-money laundering compliance analysts by 35%, while the accuracy rate of identifying suspicious transactions could be increased by more than four times.”

Cybercrooks harness AI to good advantage

“Hyderabad: Artificial Intelligence is getting good at doing bad things swiftly, evident from the alerts put out by leading cybersecurity companies that attackers won’t just target AI systems but will create AI techniques themselves to amplify their own criminal activities.

Although AI will help automate manual tasks, enhance decision-making and other human activities, it can attack many systems including AI.

Instead of hackers finding loopholes, AI itself can search for undiscovered vulnerabilities that it can exploit.

For instance it can be used to make phishing and other social engineering attacks even more sophisticated by creating extremely realistic video and audio or well-crafted emails designed to fool individuals.  AI could also be used to launch disinformation campaigns.

Researchers have been rising increasingly concerned about the vulnerability of these artificially intelligent systems to malicious input that can corrupt their logic and affect their operations.

The World Economic Forum came out with a report, last week on Adversarial AI, cautioning governments: “Changes in the threat landscape are already apparent. Criminals are already harnessing automated reconnaissance, target exploitation and network penetration end-to-end”. Experts noted that attackers will be employing AI to avoid detection by security software and will even automate target selection, and check infected environments before deploying later stages and avoiding detection.

Chief technology officer, Symantec, Mr Hugh Thompson, said, ‘In some ways, the emergence of critical AI systems as attack targets will start to mirror the sequence seen 20 years ago with the internet, which rapidly drew the attention of cybercriminals and hackers, especially following the explosion of internet-based eCommerce. The fragility of some AI technologies will become a growing concern in 2019.'”

7.6% – average yearly financial expense attributed to fraud

  • According to a 2016 report, the average yearly financial expense attributed to fraud for retailers was 7.6 percent of annual revenue across all channels, including online and offline sales. And that is on a business-as-usual day. On peak-retail days, clients operating on Amazon have reportedly seen an increase of 150 percent in fraud attempts.
  • But the online retail anti-fraud business is about to change, and that change is going to affect consumers and retailers as well. This is due to new EU regulation called PSD2. PSD2, which comes into effect in mid-2019, is mainly about opening bank APIs to 3rd parties. But it also includes provisions applying to online sales.
  • The intention of this directive is good at heart but unnecessarily provides friction to the more than 99 percent of users out there that are good, according to Lee: “We are essentially making buyers conform to a set of rules because the system is being exploited by a select few bad apples.
  • White said this is going to have a tremendous impact on the market, specifically in the e-commerce space: “Conversion rates are already low in this space, and any added obstacles or friction could correlate into an increase in cart abandonments.
    • This can be a difficult task because if it was simple we wouldn’t need the predictive power of machine learning in the first place.

    eBay’s AI can identify 40% of credit card fraud cases with ‘high precision’

    “Our [technique] can be immensely helpful, as out of 284,807 samples we can safely rule out 139,220 [transactions],” they wrote.

    If you’ve purchased or sold something on eBay recently, you might have encountered the system in action. The researchers coyly noted that it was successful in picking out fraudulent transactions in data from an “ecommerce platform”

    Spend of $1 trillion by 2021

    “The cybersecurity market is now worth $120 billion, according to 2018 research, a roughly 13,500 percent increase compared to a decade earlier. What’s more, spending is expected to increase to $1 trillion by 2021 as companies invest in emerging prevention solutions. In fact, more are already turning to artificial intelligence, data analytics, machine learning and other technologies to strengthen their cybercrime defenses.

    These technologies seem to hold promise in the fight against fraud, too, thanks to their ability to track and interpret massive amounts of data. This information can then be used to better understand what separates normal consumer behavior from that of bad actors, improving defenses, reducing false positives and giving consumers more convenient and secure online experiences.”