Following a request by South Korean prosecutors, Interpol has placed Terraform Labs founder Do Kwon on a "red notice" list, TechCrunch has reported. That will create a request for law enforcement agencies around the world to arrest Kwon following his blockchain company's collapse that took $40 billion from investors with it.
After Korean authorities issued an arrest warrant for Kwon last week, he tweeted that he was "not on the run" or "anything similar." However, prosecutors said that they believed Kwon left Korea to "evade investigation" as he told them through his lawyers that he didn't intend to appear before questioning. "He is clearly on the run as his family members and the company's key finance people also left for the same country [Singapore] at the same time," they said.
Kwon and other Terraform Labs' employees are under investigation for financial fraud and tax evasion following the collapse of its stablecoins, TerraUSD and Luna. The investors, many of whom lost their life savings following the collapse, filed complaints accusing him of running a Ponzi scheme. The crash of the Luna token also played a roll in the collapse of the crypto hedge fund Three Arrows Capital.
If you have your eye on Samsung's new Galaxy Watch 5 but were waiting for a deal, one has already arrived. Amazon's Woot portal is selling the 40mm model in several colors (Grey, Pink Gold and Silver) for $250, a savings of $30 or 11 percent off the regular price.
The Galaxy Watch 5 scored a solid 85 in our Engadget review, and we once again called it "the best non-Apple smartwatch." Samsung was focused more on perfecting it over the Watch 4, adding extra battery life (a runtime of up to 80 hours), greater durability with Sapphire Crystal glass and an inactive temperature sensor.
Otherwise, it carries the same design and features as before, which is a good thing. Powered by a responsive 5-nanometer Exynos processor and running Wear OS, it uses Samsung's bezel-based navigation with a touch-sensitive ring framing the screen. That gives you access to numerous apps, along with sleep-tracking and coaching plus health and activity tracking. You can get your body composition reading using the body-impedance analysis tool, take ECG scans, reply to messages, control music playback and more.
The lightly curved underside keeps the sensors in contact with your wrist, and it's rated IP68, 5ATM and MIL-STD-810H for durability (water, dust and pressure resistance). The main downside is that battery life is considerably lower with the always-on display compared to the Apple Watch 7. Still, it's the best Android smartwatch available and it's rare to see a discount on such a new device. Bear in mind that sales from Woot are time limited and have a different return policy from parent Amazon.
The US Environmental Protection Agency (EPA) has formed a new office designed to help marginalized communities deal with the extra burdens of pollution and climate change, Reuters has reported. The Office of Environmental Justice and External Civil Rights will be staffed by 200 EPA employees located in the agency's Washington head office and 10 regional bureaus.
"The establishment of a new office dedicated to advancing environmental justice and civil rights at EPA will ensure the lived experiences of underserved communities are central to our decision-making while supporting community-driven solutions," said US Vice President Kamala Harris.
One of the primary jobs of the new office will be to oversea the distribution of $3 billion in environmental justice grants created by the passage the of Inflation Reduction Act, as part of a $60 billion investment in environmental justice. It'll also check that other EPA programs hew to President Biden's Justice40 initiative designed to ensure that 40 percent of certain government investments flow to disadvantaged communities. Finally, it'll help communities access grants, enforce civil rights laws and resolve environmental conflicts.
The new office was launched at an event in Warren County, North Carolina, the site of 1982 protests over toxic waste dumping in the region. The resulting civil disobedience actions and arrests failed to stop the 22-acre dump, but gave birth to the modern environmental justice movement. The 40th anniversary of the protests was commemorated by participants last week.
After weeks of rumors, Amazon has officially announced that it plans to hold a second sales event this fall exclusively for Prime members. The second Prime Day of the year, dubbed "Prime Early Access Sale," will be held on October 11th and 12th in the US, UK, Canada and 12 other countries, following the same two-day format as the original event.
Amazon Prime Day has historically been an annual event in which Prime members have access to thousands of sales from the online retailer. It's been not only a way for Amazon to increase sales during the summer months, but also helps the company to drum up more subscribers for Prime. This year's Prime Day on July 12th and 13th brought a plethora of discounts on things like household essentials, clothing, electronics and more, and most of them were reserved for Prime members. However, like years past, there were select sales available to anyone on Prime Day as well.
Since Amazon has not had a second Prime Day in one year before, it's hard to anticipate what this new sales event will bring. Since it'll be held in the middle of October, we expect it to unofficially mark the start of the holiday shopping season for Amazon. It's also possible that the discounts available to Prime members only during this sales event may not come back around for everyone until Black Friday or Cyber Monday. That may encourage some shoppers to stock up on holiday gifts as early as they can snag them on sale.
Engadget will cover all of the best tech deals we can find during this second sales event, held in 15 countries including the US, Canada, the UK, much of Europe, and Turkey. If you plan on taking advantage of those sales, be sure to check Engadget for more information leading up to the event, and follow @EngadgetDeals on Twitter and sign up for our Engadget Deals newsletter so you never miss the latest news.
Next year’s iPhone could introduce a change to Apple’s naming convention. According to Bloombergreporter Mark Gurman, the company could call its largest and most expensive device in 2023 the iPhone 15 Ultra instead of the iPhone 15 Pro Max as you would expect given its recent track record. The shift would reportedly coincide with the most significant redesign of the iPhone since Apple released the iPhone 12 in 2019. Gurman expects the iPhone 15 to feature USB-C, among other “bigger changes.”
Apple’s smartphone line has seen a couple of branding tweaks over the years. In the early days of the iPhone, when the company released a substantial update every two years, iterative models carried an “S” designation. Since 2019 and the diversification of the line to include separate mainstream and premium variants, the company has employed “Pro” and “Pro Max” designations to market its most advanced phones. Moreover, earlier this year saw the return of the Plus branding, which Apple had not used since 2017. Dropping Pro Max in favor of Ultra would make a lot of sense since the Apple Watch line now includes an Ultra model.
The iPhone 15 rumor mill has already produced a few interesting predictions. Gurman previously reported that Apple was testing USB-C iPhones ahead of the European Union implementing a law requiring all new smartphones made after 2024 to feature the port. More recently, display analyst Ross Young said the entire iPhone 15 line would feature the iPhone 14 Pro’s Dynamic Island display cutout.
Looking to the more immediate future, Gurman also wrote today that Apple might not hold another event this fall. He says the company plans to announce new Mac mini, MacBook Pro and iPad Pro models before the end of the year. However, as those will be primarily iterative updates to existing devices, Gurman suggests Apple is “more likely” to share the existence of those products with the world through a series of press releases.
NieR: Automata’s anime spinoff will arrive early next year. The adaptation, now titled NieR: Automata Version 1.1a, will debut in January 2023. NieR creator Yoko Taro shared the release window during Aniplex Online Fest over the weekend (via Gizmodo), revealing at the same time that the story of the anime would differ from its source material. The two will at least share the same premise. NieR: Automata opens with a ruined Earth and a proxy war involving human-made androids. "Nier: Automata was a story we created to be a game, so copying it as-is wouldn’t make an interesting story for an anime," Taro said during the panel.
A-1 Pictures, best known for its work on series like Erased, From the New World and Your Lie in April, is producing the project, with Ryouji Masuyama co-writing the script alongside Taro. Masuyama’s previous credits include Gurren Lagann and Evangelion: 2.0 You Can (Not) Advance. "I'm the one going around and breaking things for [A-1 Pictures], so if anyone is dissatisfied [with the anime's story], it's likely to be my fault," Taro warned fans. Given that NieR: Automata features multiple endings, it’s probably for the best the anime won’t hew too closely to the game.
The panel didn’t mention details about distribution outside of Japan. However, since Sony owns both Aniplex and Crunchyroll, there’s a good chance simulcast rights will go to the streaming service. It will be interesting to see if the anime brings renewed interest to NieR: Automata, much like the recent release of Edgerunners on Netflix did for Cyberpunk 2077. Commercially, Automata performed better than publisher Square Enix expected, but the company has yet to announce a proper sequel – though we did get a mobile spinoff and remaster of the original NieR last year.
Night School Studiohas delayed the release of Oxenfree II: Lost Signals. The sequel to 2016’s Oxenfree won’t arrive until next year, the developer announced on Saturday. “To make Oxenfree II truly special and add more localizations, we’re moving our release window to 2023,” the studio posted on Twitter. News of the delay came shortly after Netflix announced subscribers could download the original game for free.
The streaming giant acquired Night School Studio in 2021. Given Netflix’s global audience, taking more time to localize the game in more languages makes a lot of sense. To that point, the new “Netflix Edition” features subtitle support in more than 30 languages. Oxenfree II: Lost Signals will be available on Steam, PlayStation 4, PS5 and Nintendo Switch when it arrives next year.
Apple Pay Later may not arrive until next spring, according to Bloomberg’s Mark Gurman. As you may recall, Apple announced the buy now, pay later feature at WWDC 2022 and said, at the time, that it would arrive alongside iOS 16. Well, the latest version of the company’s mobile operating is here and Apple Pay Later is nowhere to be found.
A footnote on Apple’s website states the feature will arrive “in a future update.” As Gurman notes, other previously announced iOS 16 features that aren’t available yet are listed as coming “later this year.” Gurman believes the discrepancy is due to the fact Apple doesn’t know when Pay Later will be ready, and the feature may not arrive until iOS 16.4 ships in 2023. “I’m hearing there have been fairly significant technical and engineering challenges in rolling out the service, leading to delays,” he notes.
It’s interesting to learn Apple is encountering technical challenges implementing a Pay Later service. Based on Gurman’s previous reporting, the company has been working on such a feature for more than a year. It even went out of its way to create a subsidiary called Apple Financing to conduct credit checks and customer approvals. All those moves suggest the company sees financial services as a significant part of its future.
Yes, robots are coming to take our jobs. That's a good thing, we should be happy they are because those jobs they're taking kinda suck. Do you really want to go back to the days of manually monitoring, flagging and investigating the world's daily bank transfers in search of financial fraud and money laundering schemes? DBS Bank, Singapore's largest financial institution, certainly doesn't. The company has spent years developing a cutting-edge machine learning system that heavily automates the minutia-stricken process of "transaction surveillance," freeing up human analysts to perform higher level work while operating in delicate balance with the antique financial regulations that bound the industry. It's fascinating stuff. Working with AI by Thomas H. Davenport and Steven M. Miller is filled with similar case studies from myriad tech industries, looking at commonplace human-AI collaboration and providing insight into the potential implications of these interactions.
Since the passage of the Bank Secrecy Act, also known as the Currency and Foreign Transactions Reporting Act, in the US in 1970, banks around the world have been held accountable by governments for preventing money laundering, suspicious cross-border flows of large amounts of money, and other types of financial crime. DBS Bank, the largest bank in Singapore and in Southeast Asia, has long had a focus on anti-money laundering (AML) and financial crime detection and prevention. According to a DBS executive for compliance, “We want to make sure that we have tight internal controls within the bank so the perpetrators, money launderers, and sanctions evaders do not penetrate into the financial system, either through our bank, through our national system, or internationally.”
The Limitations of Rule-Based Systems for Surveillance Monitoring
As at other large banks, the area of DBS that focuses on these issues, called “transaction surveillance,” has taken advantage of AI for many years to do this type of work. The people in this function evaluate alerts raised by a rule-based system. The rules assess transaction data from many different systems across the bank, including those for consumers, wealth management, institutional banking, and their payments. These transactions all flow through the rule-based system for screening, and the rules flag transactions that match conditions associated with an individual or entity doing suspicious transactions with the bank—those involving a potential money laundering event, or another type of financial fraud. Rule-based systems—in the past known as “expert systems” — are one of the oldest forms of AI, but they are still widely used in banking and insurance, as well as in other industries.
At DBS and most other banks across the world, rule-based financial transaction surveillance systems of this sort generate a large number of alerts every day. The primary shortcoming of rule-based surveillance systems is that most — up to 98 percent — of the alerts generated are false positives. Some aspect of the transaction triggers a rule that leads the transaction to be flagged on the alert list. However, after follow-up investigation by a human analyst, it turns out that the alerted transaction is actually not suspicious.
The transaction surveillance analysts have to follow up on every alert, looking at all the relevant transaction information. They must also consider the profiles of the individuals involved in the transaction, their past financial behaviors, whatever they have declared in “know your customer” and customer due diligence documents, and anything else the bank might know about them. Following up on alerts is a time-intensive process.
If the analyst confirms that a transaction is justifiably suspicious or verified as fraud, the bank has a legal obligation to issue a Suspicious Activity Report (SAR) to the appropriate authorities. This is a high-stakes decision, so it is important for the analyst to get it right: if incorrect, law-abiding bank customers could be incorrectly notified that they are being investigated for financial crimes. On the other side, if a “bad actor” is not detected and reported, it could lead to problems related to money laundering and other financial crimes.
For now at least, rule-based systems can’t be eliminated because the national regulatory authorities in most countries still require them. But DBS executives realized there are many additional sources of internal and external information available to them that, if used correctly, could be applied to automatically evaluate each alert from the rule-based system. This could be done using ML, which can deal with more complex patterns and make more accurate predictions than rule-based systems.
Using the New Generation of AI Capabilities to Enhance Surveillance
A few years ago, DBS started a project to apply the new generation of AI/ML capabilities in combination with the existing rule-based screening system. The combination would enable the bank to prioritize all the alerts generated by the rule-based system according to a numerically calculated probability score indicating the level of suspicion. The ML system was trained to recognize suspicious and fraudulent situations from recent and historical data and outcomes. At the time of our interviews, the new ML-based filtering system had been in use for just over one year. The system reviews all the alerts generated by the rule-based system, assigns each alert a risk score, and categorizes each alert into higher-, medium-, and lower-risk categories. This type of “post-processing” of the rule-based alerts enables the analyst to decipher which ones to prioritize immediately (those in the higher- and medium-risk categories) and which ones can wait (those in the lowest-risk category). An important capability of this ML system is that it has an explainer that shows the analyst the evidence used in making the automated assessment of the probability that the transaction is suspicious. The explanation and guided navigation given by the AI/ML model helps the analyst make the right risk decision.
DBS also developed other new capabilities to support the investigation of alerted transactions, including a Network Link Analytics system for detecting suspicious relationships and transactions across multiple parties. Financial transactions can be represented as a network graph showing the people or accounts involved as nodes in the network and any interactions as the links between the nodes. This network graph of relationships can be used to identify and further assess suspicious patterns of financial inflows and outflows.
In parallel, DBS has also replaced a labor-intensive approach to investigation workflow with a new platform that automates for the analyst much of the support for surveillance-related investigation and case management. Called CRUISE, it integrates the outputs of the rule-based engine, the ML filter model, and the Network Link Analytics system.
Additionally, the CRUISE system provides the analyst with easy and integrated access to the relevant data from across the bank needed to follow up on the transactions the analyst is investigating. Within this CRUISE environment, the bank also captures all the feedback related to the analyst’s work on the case, and this feedback helps to further improve DBS’s systems and processes.
Impact on the Analyst
Of course, these developments make analysts much more efficient in reviewing alerts. A few years ago, it was not uncommon for a DBS transaction surveillance analyst to spend two or more hours looking into an alert. This time included the front-end preparation time to fetch data from multiple systems and to manually collate relevant past transactions, and the actual analysis time to evaluate the evidence, look for patterns, and make the final judgment as to whether or not the alert appeared to be a bona fide suspicious transaction.
After the implementation of multiple tools, including CRUISE, Network Link Analytics, and the ML-based filter model, analysts are able to resolve about one-third more cases in the same amount of time. Also, for the high-risk cases that are identified using these tools, DBS is able to catch the “bad actors” faster than before.
Commenting on how this differs from traditional surveillance approaches, the DBS head of transaction surveillance shared the following:
Today at DBS, our machines are able to gather the necessary support data from various sources across the bank and present it on the screen of our analyst. Now the analyst can easily see the relevant supporting information for each alert and make the right decision without searching through sixty different systems to get the supporting data. The machines now do this for the analyst much faster than a human can. It makes the life of the analysts easier and their decisions a lot sharper.
In the past, due to practical limitations, transaction surveillance analysts were able to collect and use only a small fraction of the data within the bank that was relevant to reviewing the alert. Today at DBS, with our new tools and processes, the analyst is able to make decisions based on instant, automatic access to nearly all the relevant data within the bank about the transaction. They see this data, nicely organized in a condensed manner on their screen, with a risk score and with the help of an explainer that guides them through the evidence that led to the output of the model.
DBS invested in a skill set “uplift” across the staff who were involved in creating and using these new surveillance systems. Among the staff benefiting from the upskilling were the transaction surveillance analysts, who had expertise in detecting financial crimes and were trained in using the new technology platform and in relevant data analytics skills. The teams helped design the new systems, beginning with the front-end work to identify risk typologies. They also provided inputs to identify the data that made most sense to use, and where automated data analytics and ML capabilities could be most helpful to them.
When asked how the systems would affect human transaction analysts in the future, the DBS compliance executive said:
Efficiency is always important, and we must always strive for higher levels of it. We want to handle the transaction-based aspects of our current and future surveillance workload with fewer people, and then reinvest the freed- up capacity into new areas of surveillance and fraud prevention. There will always be unknown and new dimensions of bad financial behavior and bad actors, and we need to invest more time and more people into these types of areas. To the extent that we can, we will do this through reinvesting the efficiency gains we achieve within our more standard transaction surveillance efforts.
The Next Phase of Transaction Surveillance
The bank’s overall aspiration is for transaction surveillance to become more integrated and more proactive. Rather than just relying on alerts generated from the rule-based engine, executives want to make use of multiple levels of integrated risk surveillance to monitor holistically from “transaction to account to customer to network to macro” levels. This combination would help the bank find more bad actors, and to do so more effectively and efficiently. The compliance executive elaborated:
It is important to note that money launderers and sanctions evaders are always finding new ways of doing things. Our people need to work with our technology and data analytics capabilities to stay ahead of these emerging threats. We want to free up the time our people have been spending on the tedious, manual aspects of reviewing alerts, and use that time to keep pace with the emerging threats.
Human analysts will continue to play an important role in AML transaction surveillance, though the way they use their time and their human expertise will continue to evolve.
The compliance executive also shared a perspective on AI: “It’s really augmented intelligence, rather than automated AI in risk surveillance. We do not think we can remove human judgment from the final decisions because there will always be a subjective element to evaluations of what is and is not suspicious in the context of money laundering and other financial crimes. We cannot eliminate this subjective element, but we can minimize the manual work that the human analyst does as part of reviewing and evaluating the alerts.”
Lessons We Learned from This Case
An automated system that generates large numbers of alerts most of which turn out to be false positives does not save human labor.
Multiple types of AI technology (in this case, rules, ML, and Network Link Analytics) can be combined to improve the capabilities of the system.
Companies may not reduce the number of people doing a job even when the AI system substantially improves the efficiency of doing it. Rather, employees can use the freed-up time to work on new and higher-valued tasks in their jobs.
Because there will always be subjective elements in the evaluation of complex business transactions, human judgment may not be eliminated from the evaluation process.
At its Tudum event today, Netflix shared an update on its highly-anticipated adaptation of Liu Cixin’s The Three-Body Problem. First announced in 2020, the upcoming live-action series from Game of Thrones showrunners David Benioff and D.B. Weiss will arrive sometime next year. Netflix shared a behind-the-scenes teaser showing off a few character moments.
First look at David Benioff, D.B. Weiss and Alexander Woo’s new series ‘3-BODY PROBLEM’.
Some of the actors set to star in the project include Benedict Wong (The Martian, Doctor Strange), Eiza González (Baby Driver), as well as John Bradley and Liam Cunningham of Game of Thrones fame. Considered a modern sci-fi masterpiece, The Three-Body Problem was first published in China in 2008. It took another six years before the novel arrived in the west, and it subsequently became the first Asian novel to win a Hugo Award. Cixin and Ken Liu, who translated two of the novels in the Remembrance of Earth’s Past trilogy into English, are consulting on the live-action adaptation.
Netflix signed Benioff and Weiss to a lucrative $200 million deal in 2019. The 3-Body Problem is the first project the duo is writing for the company – though they also produced a series with Sandra Oh. Netflix is likely to share more information about the 3-Body Problem in the coming months.
