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Artificial Intelligence for ROP Screening and to Assess Quality of Care: Progress and Challenges – American Academy of Pediatrics

The goal of retinopathy of prematurity (ROP) screening is to detect the constellation of clinical signs that suggest a high risk of progression to retinal detachment so that urgent treatment can be given. At each screening episode, there are 3 considerations: whether urgent treatment is needed, whether follow-up screening is needed, and whether there is no risk of sight-threatening ROP so that the screening can stop. The decisions are based on a detailed examination of the retina focused on the severity (ie, stage), location (ie, zone), and degree of dilation and tortuosity of retinal blood vessels (ie, plus disease). If ROP is not present, the peripheral retina needs to be assessed to determine the degree of maturity of the retinal vessels; if they are mature or ROP detected earlier is definitely regressing, the screening can stop.

Telemedicine with artificial intelligence (AI) image analysis could transform ROP screening, especially in settings with an insufficient supply of ophthalmologists, which can happen either because of absolute workforce shortages

Address correspondence to Clare Gilbert, FRCOphth, MSc, MD, Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, London WC1E 7HT, United Kingdom. E-mail: clare.gilbert{at}lshtm.ac.uk

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Artificial Intelligence for ROP Screening and to Assess Quality of Care: Progress and Challenges - American Academy of Pediatrics

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How Gainesville city officials are using artificial intelligence to improve its road conditions – Gainesville Times

Data-driven developer RoadBiotics developed the road-rating software, and its been implemented by municipalities in 34 states and 14 countries.

Public works director Chris Rotalsky said the software provides an algorithm that takes pictures of roadways every 10 feet, and rates the road by segments and points.

Utilizing this system provides several benefits to the Public Works Department, said Rotalsky. Staff time for data input is reduced, and the citys street network is evaluated within a short timeframe while applying the same visual criteria for analysis to each segment.

According to RoadBiotics representatives, its all done through labeled image data. Road images are captured from a cars windshield camera, and through-machine learning and digital paint brushing, the AI begins to scan the roads.

What does the AI look for when assessing each road image? The machine is designed to check for everything from unsealed cracks to cold patches to potholes before determining a final grade.

The system grades city roads on a five-level scale from green to red.Dark green roads are optimal and in the best condition. Yellow and orange roads, graded between 2, 3 and 4 respectively, are declining road conditions. And the worst-conditioned roads are coded red and are rated a 5.

According to the Pittsburgh-based company representatives, road ratings and reports are posted on an interactive, GIS-based platform called RoadWay.

Those ratings and reports help the city prioritize which roads need immediate improvement.

The data provided from RoadBotics is combined with other rating criteria such as base condition, ride condition to help determine repair and resurfacing actions needed for the street network, said Rotalsky.

In 2018, the city did its first road assessment using the software, with most of the citys roads graded as green or yellow.

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Machine Learning Can Help The Insurance Industry Throughout The Process Lifecycle – Forbes

Artificial Intelligence

Insurance works with large amounts of data, about many individuals, many instances requiring insurance, and many factors involved in solving the claims. To add to the complexity, not all insurance is alike. Life insurance and automobile insurance are not (as far as I know) the same thing. There are many similar processes, but data and numerous flows can be different. Machine learning (ML) is being applied to multiple aspects of insurance practice.

Insurance is about risk. The insurance industry sets rates based on expected payouts so that, hopefully, they end up with positive revenue. Setting rates and understanding payout in order to maintain profitability is complex, and the industry hope is that ML can help in achieving that goal. Note, here, Im focusing more on ML than artificial intelligence (AI), because many of the complex statistical tools that are now considered ML can more efficiently accomplish some of the tasks than would neural networks, expert systems, or other purely AI tools.

There are multiple ways machine learning can help in the insurance industry. Let us take a look at three.

Health and life insurance are complex. There are multiple factors that go into understanding an individuals risk factors for disease, illness, and mortality. Insurance underwriters have historically used a core set of factors such as male/female, age, and smoker/non-smoker. When other factors have been used, such as zip code, the problem of red-lining has appeared in insurance as well as the more well-known area of financial red-lining. Therefore, there are regulations about how some demographic information must be used.

The need to address those legal concerns means that underwriting isnt only about individual health risks, but about legal risks as well. Analysis must be done to back out some features that could cause legal risk while still creating pools that remain profitable.

This is where machine learning comes in. The performance of modern computing can handle large amounts of data, and complex regression analysis can perform clustering that can help with analysis. Those ML techniques provide value without the need for AI. For insurance underwriting, statistical models and procedural code are providing an improvement in analysis for companies, said Paul Ford, CEO & Co-Founder, Traffk. We are working with neural network models, but the overhead for training and runtime must be balanced with the accuracy improvement necessary to make it worthwhile to roll-out those engines. While things might change, down the road, our existing ML models provide advances in analysis and profitability for our customers.

At the other end of the insurance process is the issue of claims. It is not only the insured who have problems with claims complexity. In the automotive industry, the need to understand the variety of repair options and parts available create a challenge for both service providers and the insurers.

With automotive claims, providing an estimate based on the typical costs for repair is not sufficient. Its not only that vehicle types vary, within a class of vehicle the repair costs can vary based on the insurance coverage, as well as the availability of parts in geographic regions.

Machine learning can help with claims in a number of ways. In addition, multiple ML tools can be used throughout the claims process.

Take the First Notice of Loss (FNOL), the initial notification to the insurer about the accident or damage. If theres a quick estimate of total loss, theres a different process flow that is much simpler. No ML is needed in the review of damage, but robotic process automation (RPA) might be used to simplify the claim flow to payment.

With other damage, or even to understand if there is a total loss, ML can be used. The most obvious tool is AI vision, but even this can have multiple processes. A phone app can step a customer through taking pictures that an AI system can then analyze for damage, with a backend AI system working to link to parts and estimate. A repair shop, in comparison to the insured, is more familiar with the process and can have a different front-end asking more detailed questions to more quickly get a more educated response from the repair experts.

Note that two different approaches were mentioned. It would be overly complex to have a single AI system that could support every step in the claims process. More efficiency is gained by letting separate systems process claims, identify damage and provide repair estimates, said Evan Davies, CTO, Solera. By using different approaches to machine learning through the claims process, you maximize the benefits of automation and enable skilled workers to focus on more complex cases.

One thing Evan Davies also pointed out was how the process flow can change depending on the severity of accident or the type of insurance coverage provided. Minor damage and standard coverage can be fully automated, as all parties are fairly comfortable with the process and dollar amounts. Totals, as mentioned, dont require AI. Those claims in the middle, however, can be helped with an adjuster reviewing the analysis and working with the customer, for the benefit of both short term monetary issues and long term customer relations.

Yes, we keep coming back to fraud. Sadly, it is a human condition and a risk in so many areas of business. Insurance is no exception. As Ive recently talked about fraud and ML in other business arenas, I wont go into detail here. Let it be sufficient to point out that analysis of claims doesnt stop at processing all claims as if they are proper.

Cluster analysis is used to understand, for instance, if a similar type of accident is happening in an area at above normal amounts; potentially indicating organized fraud.

In the analysis of potential fraud, multiple tools are used, some are in ML, such as statistics, rules based approached and even neural networks.

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Startup bets on artificial intelligence to counter misinformation | TheHill – The Hill

U.K.-based fact-checking startup Logically launched a new service Monday aimed at helping governments and nongovernmental organizations identify and counter online misinformation using a blend of artificial intelligence and human expertise.

The Logically Intelligence (LI) platform collects data from tens of thousands of websites and social media platforms then feeds it through an algorithm to identify potentially dangerous content and organize it into narrative groups.

Over the last few years, the phenomenon of mis- and disinformation has firmly taken root, evolved and proliferated, and is increasingly causing real world harm, Lyric Jain, founder and CEO of Logically, said. Our intensive focus on combating these untruths has culminated in the development of Logically Intelligence, based on several years of frontline operations fighting against the most egregious attacks on facts and reality.

The company views the service as a way to help institutions, including social media platforms, to be quicker to react to burgeoning misinformation narratives.

Jain told The Hill that he hopes the platform will help information and intelligence sharing in the wake of the deadly insurrection at the Capitol earlier this year, which was planned in publicly-accessible online spaces but was seemingly missed by some authorities.

We think it's a really good time for us to be able to empower individuals to national governments with something like Logically Intelligence, he said in an interview, noting that the service could also help identify drivers behind coronavirus vaccine hesitancy.

LI provides users with a customizable Situation Room that organizes potentially dangerous pieces of content and shows links between them. For example, the platform could chart how a particular concept traveled from a fringe platform to a mainstream social media site, helping the user figure out to block off falsehoods before they proliferate.

It also identifies inauthentic accounts and can potentially be used to locate networks of them.

Logically touts its artificial intelligence and team of expert researchers as a differentiating factor that will help it be quicker and better at organizing content in useful ways.

What separates this from traditional social monitoring and internet monitoring tools is we then use all of the learning that we've done in terms of our artificial intelligence model, everything weve learned from our consumers products and projects weve worked on previous to this to then classify that content, global head of product Joel Mercer explained.

The platform also offers users several countermeasures once misinformation narratives have been detected, including investigative reports from Logicallys subject-matter experts, ways to flag content to platforms and built-in fact checks.

LI has been tested with some government agencies over the last year. The company worked with an undisclosed battleground state during the 2020 American election to identify misinformation and coordinated activity that might hurt election integrity.

It helped the state, according to Logically, push back on the false narratives by figuring out who was being targeted and boosting true information contradicting them through trusted local officials.

The company has built in safeguards aimed at ensuring the LI platform is not misused. The company has a list of permissible use cases and plans to monitor how the tool is being applied.

Logically, which was founded in 2017, has previously worked on a service focused on fact-checking news. It also produces research on misinformation, like the QAnon conspiracy theory.

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Fantom Is Top Performing Cryptocurrency Again: Here’s What You Need To Know – Yahoo Finance

FTM, the native cryptocurrency of the Fantom project, is up 44% over the last 24 hours. It was trading at $0.5882 at press time.

What Happened: The token previously reached $0.7652 on Feb. 25, gaining 259% in one week.

The current spike seems to follow the news of Fantoms wallet integration to the Binance exchange. The crypto exchange has also enabled deposits and withdrawals for the cryptocurrency.

Why It Matters: The FTM momentum's primary reason is its new cross-chain functionality with the Ethereum (CRYPTO: ETH) blockchain.

While Ethereum is the most used network in the crypto space, transaction costs have reached record highs due to congestion on the network.

This has led to users seeking alternative blockchains with lower fees to facilitate their transactions. Users on the Ethereum network will now be able to transfer their tokens to Fantom and benefit from faster and cheaper transactions.

According to Fantom, these transactions will be confirmed within 1-2 seconds and will cost a fraction of a cent.

The cross-chain bridge between Ethereum and Fantom was enabled by Andre Cronje of Yearn.Finance. This "DeFi architect" has built several features across decentralized platforms in the crypto space.

According to Cronje, the idea behind this functionality was not intended to be positioned as an Ethereum competitor.

Cronje stated on Twitter, The goal with Fantom from the beginning was simple, it was never meant to be an ETH killer. ETH is winning, ETH just needs some load balancers to help out a bit.

What Else: Aside from the cross-chain bridge, users on the Fantom network now also have the ability to stake tokens on the network while still accessing their value for use in the crypto ecosystem.

Alameda Research, led by the founder of major cryptocurrency exchange FTX, Sam Bankman-Fried, has also invested $35 million into the Fantom Foundation.

This investment will align the incentives between Alameda and Fantom, allowing us to push towards a non-tribalistic cross-chain ecosystem with other platforms such as Solana, while also reducing friction for developers who want to build on multiple ecosystems., said Fantom in a blog.

Story continues

Image: Maxim Hopman via Unsplash

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2021 Benzinga.com. Benzinga does not provide investment advice. All rights reserved.

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This Utah Startup Just Raised $100 Million To Solve Cryptocurrencys Looming Tax Problem – Forbes

TaxBit cofounders Justin Woodward and CEO Austin Woodward have raised $100 million to build the ERP for cryptocurrency.

With bitcoins market capitalization approaching $1 trillion, and hundreds of billions more in value in a host of other coins and projects, boring old taxes are becoming a big headachenot just for consumers, but also the exchanges, businesses dabbling in the sector and governments getting involved.

While others speculate on the coins themselves in the new gold rush, entrepreneur Austin Woodwards happy to provide the picks and shovels. His startup, TaxBit, automates all those gains and losses for the customers of exchanges and power users alike. And with Utahs largest-ever Series A funding round in the bag, hes on track to build a buzzy business in the process.

The entire existence of this asset class that can be so disruptive to our financial sector is at risk because of tax and accounting compliance at scale, Woodward says. Theres no NetSuite, Oracle or SAP of cryptocurrency.

Founded in 2018, TaxBits raised $100 million in its Series A financing, led by investment firms Paradigm and Tiger Global. PayPal Ventures, Winklevoss Capital, the investment firm of the billionaire Winklevoss twins, Coinbase Ventures and others, including Bill Ackman and Qualtrics cofounder Ryan Smith, joined the round, which takes the Utah-based startups total funding raised to more than $107 million.

Initially a consumer-facing product, today TaxBit offers its software to a mix of individual practitioners and, more lucratively for the startup, the businesses that help them invest and trade: crypto exchanges, wallet providers, lending platforms and the like. TaxBits software is white-labeled, meaning that users of those tools will sometimes know theyre working in the startups software, sometimes not, often accessing it through the tax center sections or pages of the companies websites. TaxBit has processed more than one million tax forms to date, the company says.

TaxBit got its start as Woodward and his brother, Justin, began to explore the emerging crypto category while in their previous jobs. Justin was working in a federal judicial clerkship while attending law school at the University of Chicago; Austin was spending nights researching and dabbling in crypto assets while an early employee at Qualtrics, the customer experience company that is one of Utahs recent tech breakouts. Austin Woodward says one formative moment was when he was responsible for Qualtrics missing payroll in Australia because he sent a wire ten minutes late that took 48 hours to cleara problem, he believed, that crypto could solve, alongside others like transaction fees, cross-border payments and the ability for nonaccredited investors to buy small pieces of assets like real estate through tokens.

TaxBit cofounders Justin Woodward, Brandon Woodward and CEO Austin Woodward launched their startup from Justin and Austin's dad's basement.

When SAP bought Qualtrics, in a shock move, for $8 billion just days before it was supposed to go public in November 2018, Austin Woodward, whod worked closely on its S-1 filings for that process, saw his cue to work on a tax solution in crypto full time. (Qualtrics eventually went public, after all, in a spinout this past January.) With their cousin Brandon Woodward focused on front-end development and design, the Woodward brothers moved into their dads basement; their father was also their first financial supporter, cutting them an initial check to get going.

Soon, Album Ventures backed TaxBit in a pre-seed round, and as the business scaled to many thousands of individual users for its consumer-facing tool, it raised a $5 million seed round in December 2019. In January, the venture arms of Coinbase and PayPal invested in a strategic round alongside its previous investor, Winklevoss Capital. Scant weeks later, Paradigm, the crypto-focused venture fund founded by Sequoia veteran Matt Huang and Coinbase cofounder Fred Ehrsam, had come knocking, as did Tiger Global, a leading growth equity investor in the software world.

They bring a ton of energy to solving crypto tax, says Huang. For the pitch, the whole team got on a Zoom call on a Saturday night, and Austin was almost jumping through the Zoom screen.

Why raise $100 million so fast? Austin Woodward, TaxBits CEO, says the money is to invest in the companys enterprise tools and international expansion, with the United Kingdom coming first. Eventually TaxBit hopes to offer something like a traditional enterprise resource planning tool for corporations, helping them manage crypto transactions for optimal tax results much like other software tools do for foreign currencies. Governmentsboth the tax-collecting agencies and municipalities that offer crypto as paymentcould also prove natural clients. That means hiring from about 40 employees to more than 100 by years end, Woodward says, and building out a sales and marketing team that largely comprised the founders and vice president Michelle OConnor, a veteran of crypto exchange Uphold, until now.

We were called the TurboTax of crypto really early in this, and that was glamorous to us for whattwo weeks? Woodward says. And then we realized we dont want to be your tool you log into on April 14 because you have to, just to file stuff.

TaxBits story so far reminds at least one person of Qualtrics own trajectoryits cofounder and chairman, Smith, now the owner of NBA franchise the Utah Jazz and an investor in TaxBit following the raise. Like the Woodwards, Smith built Qualtrics with his brother and father from home for years, only raising capital when the business was well-launched. This is my way of getting into crypto, Smith says. When building a startup like Qualtrics, you wonder how many people are paying attention. Austin was definitely paying attention.

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Himegami is Revolutionizing the Cryptocurrency Market with a Decentralized Elastic Supply Model – GlobeNewswire

Harju County, Estonia, March 02, 2021 (GLOBE NEWSWIRE) -- As the cryptocurrency market continues to mature, crypto projects also continue to evolve further driving the evolution of the market. So far, we have seen cryptocurrency projects with a fixed supply for the native tokens. The ultimate aim here has been to create scarcity and drive crypto prices higher.

Now, we believe its time for creating elastic supply of decentralized digital currencies. KGR is one such dynamic and completely decentralized elastic supply protocol that aims to cater to the liquidity needs of the broader crypto market, and more importantly, to solve the issues of market manipulation.

The KRG cryptocurrency achieves better balance of supply and demand as it correlates a synthetic assets price perfectly with the price of its underlying asset. The KGR token is basically an elastic cryptocurrency with its target price at 1 Japanse Yen adjusted for inflation.

The price of KGR can be higher or lower than 1 Yen, however, the supply is always adjusted to meet the target of 1 Japanese yen (). If high demand drives the price higher above 1 Yen, the Himegami protocol will add more supply creating a selling pressure and a rebase action. To distribute the KGR token to the token holders, the system would be able to issue 100,000 tokens per rebase then sell it on public exchanges following a rst-come-rst-serve rule. The unsold tokens in the day will be burned. This method was implemented in smart contracts. This makes KGR one-of-its-kind cryptocurrency with such flexibility and supply elasticity.

The Himegami rebase system is implemented every 1385 minutesto rebase the supply. The rebase function is a new concept to the crypto market and is basically associated to supply smoothening for decentralized elastic supply tokens like KGR.

Since the KGR tokens expand and contract based on the demand and supply, the rebase mechanism ensures that the percentage holding for users remains the same.

We envision the Himegami protocol to be a hedge asset for all of the crypto world as well as to the emerging sector of Decentralized Finance (DeFi). The stability of KGR can help DeFi investors to reduce their dependency on some of the centralized stablecoins. It can work as a hedge asset, a DeFi collateral, and a stable medium of exchange for the entire crypto space.

We are positioning KGR as a useful crypto token and a collateral asset for Decentralized Finance (DeFi). Its unique qualities like decentralized, profitable, self-governing, and more stable asset, makes it important to DeFi. In the future, KGR may have multiple different applications and can be used to supplement other DeFi projects like Tezos, Polkadot, Cardano, and others.

Furthermore, the programmatic rebasing protocol aims to solve the issue of massive fluctuations in liquidity and volatility by making it more predictable and rewarding for everyone involved.

This allows us to position Himegami not only in the current crypto ecosystem but create a whole new host of applications for it in the private DeFi ecosystems of tomorrow that many havent even been thought about yet.

Himegami Protocol Founder Leo Bai

Media contact:Company: Himegami Name: Leo Bai-Founder Email: info@himegamiprotocol.orgWebsite: http://himegamiprotocol.org/

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Be cautious when accepting salary or payments in cryptocurrency – Mint

NEW DELHI: Increasingly, freelancers working with overseas clients are receiving payments in cryptocurrencies. Instead of sending money through banks or via other remittance services, clients have been transferring cryptocurrencies as such transactions are low-cost, instant, and convenient.

According to a report in the Economic Times, some companies involved in cryptocurrency business are hiring Indian developers as contractors and paying them in virtual currencies as they don't want to deal with the country's regulations and taxes.

Also Read | Assam shakes up the micro loans universe

But lawyers caution against accepting payments in cryptocurrencies. "The government is planning to introduce a Bill to ban all private cryptocurrencies in the country. If it goes through, the only option for the individuals would be to sell it on overseas exchanges," said Probir Roy Chowdhury, Partner, J Sagar Associates.

Selling it in the overseas market and then remitting the funds back to India will increase the an individual's compliance burden.

Some countries, like Singapore, have allowed the trading of virtual currencies. For a client based in a country where trading of cryptocurrencies is permissible, and they can make cross-border payments in them.

In India, however, the legal position of cryptocurrencies is unknown. As there is ambiguity and the law is not yet settled, many individuals continue to trade in virtual currencies. "Due to the grey areas, trading or receiving payment is not yet illegal," said Chowdhury.

But those receiving payments in cryptocurrencies need to keep in mind that they are not considered legal tender. "Due to this, it could get challenging to seek relief in court against a client or the employer," said Chowdhury.

The government had planned to introduce The Cryptocurrency and Regulation of Official Digital Currency Bill, 2021, in the Budget session. As it was not tabled, the details are not yet known. There is speculation that the Bill may offer existing investors of cryptocurrencies an exit option within a stipulated time frame.

Reserve Bank of India (RBI) governor Shaktikanta Das had said that cryptocurrencies could hurt financial stability, thus impacting the economy. The central bank is working on launching its digital currency.

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Cryptocurrency theft on the rise – Finextra – Finextra

Last year, the cryptocurrency sector witnessed increased mainstream adoption but it was accompanied by hackings and theft that resulted in the loss of millions of dollars.

According to data researched by Trading Platforms UK, the value of cryptocurrency hacks and thefts between 2019 and 2020 increased by 38.38% from $370.7 million to $513 million. Over the last five years, the value was highest in 2018 at $950 million.

Elsewhere, the value of blockchain fraud and misappropriation declined between 2019 and 2020 by -57.77% from $4.4 billion to $1.3billion. Cumulatively in 2019, the value of both cryptocurrency theft and blockchain fraud was $4.5 billion, while last year, it dropped to $1.9 billion, signifying the cryptocurrency sectors maturity and improved ability to detect fraudulent activities.

Hackers shifting from exchanges to DeFi projects

The increase in the value of cryptocurrency theft comes even as the sector continues to mature with exchanges, wallets, and other digital assets custodians investing in their security mechanisms against hacking. Most custodians have also established relationships with law enforcement making it easy to trace any fraudulent activity almost instantly. However, the rise in crypto theft value is an indicator that hackers are also innovating new means to outpace the current security measures.

Most hackers largely shifted their attention from exchanges and wallets taking advantage of the Decentralized Finance (DeFi) explosion. The sector attracted interest from more investors based on the immense potential to revolutionize the finance sector. Notably, DeFi protocols are permissionless hence they do not have regulatory compliance and anyone can access their code. This nature ultimately attracted hackers.

Besides easy access, DeFi applications are also vulnerable to external exploits. The projects success largely depends on composability hence the more projects that are linked, the more value they can offer. Therefore, the ability to attract more investors opens the door for hackers.

Contributing factors to blockchain fraudAt the same time, the blockchain fraud from last year saw scammers take advantage of the Covid-19 situation. Some scammers impersonated legitimate organizations and prominent people to obtain information and cryptocurrency payment. Some of the payments were disguised as helping people impacted by the pandemic.

One high-profile case was recorded on July 15, 2020, when selected Twitter accounts for prominent people like Elon Musk and organizations were compromised to promote a Bitcoin scam aimed at giving back to society. To date, the value of the scam has not been determined. The scam was further enabled due to the lack of a paper trail that gives scammers more opportunity to embezzle funds.

Worth mentioning is that regulatory bodies are already taking action to curb crypto-related fraud. This explains the drop in value of blockchain fraud in 2020. With fraud involving practices such as money laundering regulatory bodies have increased their oversight of virtual assets.

For example, there is a proposal in the United States that requires transactions between exchanges to include personal information about the sender and the receiver of funds similar to international bank wire transfers. Interestingly, the blockchain infrastructure can significantly help improve the existing monitoring system and detect, deter and document possible fraud.

Overall, most blockchain and cryptocurrency projects are still in their experimental and speculative stage. This means that there might exist some vulnerabilities. However, as the sector continues to mature, the loopholes might be sealed from hackers and scammers.

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