Every time you make an online transaction, there’s a vast and complex process that intricately links you and the vendor so that your purchase can be complete. Financial services are the backbone of our economics and thanks to the advances in machine learning, these services are able to provide more secure handling of cash, improvements in their capabilities, and faster ways to get money where it needs to go, whether it be in your hands or safely deposited.
How Machine Learning Is Implemented
Machine learning use cases in finance can be found everywhere in the industry, from fraud detection to forecasting the market. The purpose of machine learning is to create complex algorithms that chart and analyze data in order to optimize tasks. This is being utilized in the finance industry to improve consumer loyalty, assess risk, predict customer churn, or to predict outcomes automatically. This is accomplished when the software determines similarities between massive quantities of data through artificial intelligence and then derives useful insights to generate immediate solutions for financial services and consumers.
By greatly simplifying many common operations, machine learning in banking and finance greatly provides benefits. Companies will now deliver immediate solutions with the highest precision, to better their own services or improve the customer’s experience.
Anti-fraud solutions are used for financial protection to decrease any kind of consumer risk and mitigate threats.
Banking and finance fraud prevention is key to ensuring a secure climate.LAN algorithm made possible by machine learning can take advantage of any data from established patterns, which are extensively analyzed to identify and predict rising threats and stop similar ones until they emerge. This allows cash, sensitive information, and private data to be protected well as databases are ready for any unique cyberattacks. External risks like identity theft can’t breach a secure space and new forms of attacks can be detected before they unfold.
How These Services Are Growing
As financial services continue to grow and expand their service offering, they find more uses for machine learning algorithms beyond this as well. Individual businesses are able to use machine learning in order to predict where customers are staying loyal, or where they happen to be dropping off. Customer churn is analyzed and evaluated to discover where faults may lie and how they may be addressed. Most businesses typically try to maximize profits, consumer satisfaction, and increased word of mouth. When financial services implement machine learning solutions, they are able to provide businesses with the tools needed to keep their customers staying on.
These innovations were implemented by the financial industry, so machine learning algorithms and solutions can be carried out in seconds where processes that would once take a lot of resources, and money can happen much quicker. Machine learning measures and extracts data from, if vast quantities of data points, and is continuously growing. Services implementing these innovations can exponentially improve their efficiency and enable consumers to be served better. This technology will continue to produce deep learning infrastructures that are designed to satisfy the growing needs of any financial institution for years to come.
Different ways tech plays a key role in securing igaming platforms
The tremendous growth witnessed by the gaming and online casino industry is well evident in the revenue figures reported by them in the world’s prominent economies. United States, United Kingdom and some other European countries are leading the pack today.
There’s no denying the fact that it’s the technological innovations which have led to this sudden explosion of the iGaming sector over the past few years. Today, gamers can indulge in the best of online casino games from anywhere they like, at any time of the day/night. There are top rated platforms like JackpotCity online casino and others which are making things possible and are successfully ushering in the next era of online gambling.
Other than further increasing the popularity of casino games like slots roulette etc., new-age technologies have also improved the quality and safety of the gaming experience, offering players highly secure environments wherein they can share their bank details and other crucial information in a worry-free manner. Let’s tell you about 3 such ways in which tech is playing a key role in securing online gambling platforms today.
SSL is the acronym for Secure Sockets Layer, a technology used by online casinos for protecting confidential user data against phishing attempts. Players share a lot of sensitive information, such as their credit card details, addresses, phone numbers, bank details etc., while registering at these online casinos. It’s the SSL encryption technology which keeps all this information safe.
These online casinos are also required to employ such high security protocols as per law, in order to legally continue their operations. However, some operators opt for TLS (Transport Layer Security) instead of SSL encryption, something that’s not as good as the latter, but is nevertheless better than an unencrypted network.
With SSL, the player data is locked in the form of different pieces of codes which can’t be broken into easily. Hence, the information stays 100% safe whenever it’s passed on to/from the servers over the Internet. Here’s more on why an SSL certificate is important for any business website today.
All modern-day online casinos accept digital payments through debit cards, credit cards, wire transfers, e-wallets and even cryptocurrencies nowadays. Regardless of the payment method used, the servers make sure that the pertinent details stay secure from any type of unauthorised access.
Strictest security and verification protocols are employed by the financial institutions to prevent any fraud. Authentication emails and one-time passwords are good examples of few such measures. On the other hand, cryptocurrencies provide truly anonymous and safe transactions.
Random Number Generators are basically computer programs that make sure that the outcome of a casino game is completely fair, transparent and random for every player. These have the seed number algorithm at their core, which is basically a predefined mathematical formula for calculation of results based on odds. Several online casinos get their RNGs authenticated by third-party services, proving the transparency and fairness of their games.
Regardless of the measures taken by the casino platform, the onus is on the gamer to sign up with only platforms that can be trusted in every aspect.
Denmark’s News Agency Rejected a Ransom Demand by Hackers to Release Locked Data
Following a hacking attack this week, Denmark’s biggest news agency will remain offline for at least another day and has refused a ransom demand by hackers to open locked records, the wire service said Wednesday.
Ritzau CEO Lars Vesterloekke could not tell how high the demand for ransom was because those behind the “professional assault” left “a file with a message” that was not opened by the department following his advisers’ orders.
Ritzau, which sends text and images to the Danish media, said it had moved its consumer emergency delivery to six “better overview” live blogs.
“If it goes as expected, then on Thursday we can gradually return to normal,” Vesterloekke said, adding that the attack forced the editorial systems to shut down as approximately a quarter of Ritzau’s 100 servers were destroyed.
Ritzau employed an external defence firm that specialises in washing up after hacker attacks, in addition to the agency’s own IT department, and the insurance company helped with specialists.
It was unclear who was behind the assault that began Tuesday.
Ritzau, based in Copenhagen, has distributed information and produced news for the Danish newspapers, organisations and businesses since 1866.
What is Google Scraping Used For – 5 Use Cases
Google and web scraping are two rather new technologies that are increasingly being used by large businesses. Put simply, a web scraping tool is a technology solution to extract data from web sites in a quick, efficient, and automated manner, offering data in a more structured and easy to use form. When Google is being scraped, the same process applies, except the data is being extracted from the search engine.
Businesses often use Google scrapers to automate data acquisition processes. Scraped data is used to enhance operations, inform executive decisions all the way down to individual customer service experiences. Google provides its own Application Programming Interface (API), it chooses which information is more important to users based on its own analysis. Yet, many businesses choose to build their Google scraper or use third-party services in order to gather data in a more efficient manner.
Google isn’t too keen on letting other tools acquire data from their search engine. Often they will employ anti-bot measures to prevent automated applications from acquiring data. Quite ironically, they have themselves used exactly the same process to build their search engine. Whether people like it or not, web and Google scraping is here to stay as businesses have already started using it for several reasons.
Piracy and Counterfeit Protection
Many large companies and well-known brands utilize Google scraping to monitor search engine results for any malicious entities attempting to illegally use their branding. For example, Adidas might use a search engine scraping tool to monitor for any illegitimate websites that attempt to profit off of their brand illegally.
Google scraping can be used to analyze the competitor pricing policy, evaluate prices and product policies of competitors which is a great deal of information for sales strategies. Data acquired in this manner can be used to create updated and advanced pricing strategies for brand and sales (for example, dynamic pricing utilizes scraping tools to implement their strategy). Implementing advanced pricing strategies requires having access to a reliable and consistent flow of premium data. Price monitoring using web scraped data gives companies the ability to have well-grounded information of the entire market, facilitating dynamic pricing, revenue optimization, and ensuring they’re always one step ahead of their competitor’s pricing strategies. Having detailed information related to competitor sales strategies helps businesses keep up with the competition and customer demand.
Generating organic traffic on a website is mostly about ranking, location, and keyword combinations. Google scraping can show a company or a business the level at which its website page appears on the Google results page. It can also show the keywords the website uses on a given page and what exactly they rank for. SEO experts have to often use third party SEO tools like Ahrefs, Moz, or others to gain insight into rankings. Unfortunately, these tools update their databases once every few days which is often not enough for extremely volatile search engine result pages. Therefore, SEO experts might use Google scraping tools to acquire data that is otherwise unavailable to gain insight into ranking changes.
Keyword Monitoring and Research
SEO experts rely on several sources of data to create their optimization strategies. The first source is often Google blogs, the search engine liaison, and a few other official sources. Other sources are third party providers that scrape the search engine in order to reverse engineer the algorithms. SEO experts use third party providers and Google scrapers to monitor search engine result pages. By monitoring SERPs, insights can be gleaned from the data such as why certain pages rank higher than others. Finding out why certain pages rank better than others can help SEO experts develop strategies that can help companies beat out the competition.
Nearly everyone nowadays is buying PPC (Pay-Per-Click) ads on search engines nowadays. Businesses even bet on the competitor keywords and brand names in order to attract visitors to their website. Keeping track of what the competition is doing is nearly impossible without utilizing Google scraping as all ads will not be shown to all users.
For SEM surveillance, businesses scrape Google or use a third party provider in order to acquire ads from any location and device without using their own business IP address. This way Google will display ads as if it was any regular user doing a search query. As Google thinks the query has been sent by a regular internet user, it will often display many more ads without any restrictions. Business can then easily acquire significant amounts of data on their competitor ad campaigns.
Google scraping has proved purposeful, its advantages are so many, businesses have become successful with the use of Google scraping by gathering data and putting it to good use. A Google data extraction tool is an easy way for businesses to gain a competitive edge in nearly any market. With very little development effort, access to nearly infinite amounts of data appears within hands reach.
Stantinko Observed Using a New Version of a Linux Proxy Trojan
Using a new version of a Linux proxy Trojan, a threat community monitored as Stantinko was observed posing as Apache servers to stay undetected.
Stantinko is thought to have been running since at least 2012, initially outlined in 2017, ensnaring compromised networks into a botnet primarily used in large adware schemes, but also for backdoor operations, brute-force attacks, and more.
The Stantinko group was historically primarily known for attacking Windows applications, but recent attacks have revealed that they are now working on evolving their Linux malware, with a new proxy Trojan masquerading as httpd, the Apache Hypertext Transmission Protocol Server that is used on several Linux servers.
“We believe that this malware is part of a broader campaign that uses compromised Linux servers,” say security researchers at Intezer.
Detected on VirusTotal by a single anti-virus engine, the sample is an unstripped 64-bit ELF binary that validates a configuration file upon execution. The malware prevents execution if this file is absent or lacks the expected structure.
The proxy daemonizes itself if the validation completes, in which it generates a socket and a listener that allows it to accept connections. This may be the way contaminated computers deal with each other, according to Intezer.
The new version, which was discovered almost three years after the previous one has a similar function, but reveals a variety of changes, including the command and control (C&C) IP address stored in the configuration file dropped next to the malware, the absence of the new version’s self-updating capability, and the dynamic connection of the new version.
Several feature names within the dataset have been shown to be similar to the previous version, but the current version does not call them statically. In addition, the C&C routes suggest the same group’s previous campaigns, indicating that the current Trojan is still related to Stantinko.
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