An increasing number of businesses are interested in investing in blockchain technology. The technology is attracting the attention of global business executives due to its huge real-world applications. In addition, blockchain applications are more scalable and secure compared to traditional apps. Enterprise blockchain will greatly benefit businesses due to the continual expansion of digital ecosystems.
According to statistics, global spending on blockchain is anticipated to reach $19 billion by 2024. Now, most businesses are taking active steps to enter and benefit from the blockchain industry. But since its inception, many changes have taken place, and there’s no sign of things slowing down any time soon. If you’re interested in this technology, you need to stay on top of the trending topics.
In this blog post, you’ll see the top four business blockchain trends for 2022 and their long-term benefits.
What is blockchain technology?
Blockchain technology is a distributed and decentralized ledger that stores cryptographic records of transactions and records of digital assets. It’s the technology behind cryptocurrencies and is considered to be trustless and highly secure. You can’t modify records on a blockchain or interfere with the records as they require the consensus of all participants in the chain.
This makes the technology excellent for many industries that require a greater level of trust, confidentiality, and security, like healthcare and payment industries. Learn more on the trending topics within the blockchain arena in 2022 below.
Metaverse
In case you are wondering, the metaverse is a network of virtual apps that help facilitate social connection and interaction. Big techs like Meta, Microsoft, and Epic Games have had businesses globally moving to develop immersive 3D virtual experiences that allow people to connect with others and live a virtual life.
As far as technology is concerned right now, there is no better place to develop a secure and expansive metaverse than on blockchain technology. Due to its decentralized structure, blockchain development can provide secure and frictionless access to the metaverse, free from cybersecurity and fraud issues and inadequate user authentication.
In addition to privacy and security, blockchain also ties the metaverse to the crypto economy, making it an attractive investment for businesses in 2022 and beyond. Some of the benefits of Metaverse include:
Higher engagement: A virtual world closely mimics the real world can help significantly boost customer engagement and experience, spurring content and brand offering consumption.New economic streams: Metaverse offers a chance for your business to create and sell helpful virtual content that’s more engaging than on other social platforms. Besides, technologies like Facebook Meta will have their own economic system.Better communication: Metaverse can allow people to communicate and engage like they are in the same room, even when they’re geographically apart.
Non-Fungible Tokens (NFTs)
For the past two years, non-fungible tokens (NFTs) have been one of the hottest developments in blockchain technology. These are tokens issued on the blockchain as one-of-a-kind, irreplaceable tokens. This allows them to use the concept of scarcity of assets to build their value. In addition to art and digital valuables, NFTs provide a multitude of additional use cases in the blockchain.
Musicians are tokenizing their songs and selling directly to their fans, sports brands and athletes are also tokenizing merchandise and sporting moments. Artists and brands can get automatic royalty payments, record labels, managers, and other players in the specific niche. Similarly, businesses can create NFTs and marketplaces to trade them.
NFTs have also found a huge following in the fashion and gaming industries. It’s also an invaluable technology for tracking and verifying goods in the supply chain.
Digital Identity
Looking at the above two trends, it’s obvious that establishing a digital identity is now important if you want to maintain anonymity in the decentralized space. The transition to digital identities is imminent, whether or not this will be through creating avatars or any other means. And because of the growing push toward the use of digital identities, all players in the blockchain world will need to step up.
This is mainly for providers in the Decentralized Finance (DeFi) system and other required services that require identity verification. With the entry of NFTs and metaverse into the market, the issue of digital identities will continue transactions.
This also raises the issue of more regulation within the space. Most governments are curious to know how digital identities play in the crypto world and how that can affect the laid money transaction regulations.
An established digital identity system will lead to more regulation in Know Your Customer (KYC) and Anti Money Laundering (AML) measures in the DeFi world. In areas like automotive supply chain management, digital identity can be used in blockchain car sharing services through smart contracts. This works by allowing authentication of a transaction through digital identity and proof of payment.
Eco-Friendly blockchain
Among the most criticized aspect of blockchain technology is the high energy consumption rate required by popular protocols. All protocols that rely on Proof of Work (PoW) require validators that perform huge computational tasks. This is, of course, tied to the impact the same has on the environment.
But the newer protocols are more focused on eliminating the energy consumption issue by using Proof of Stake (PoS) and Proof of History (PoH) consensus. For example, Cardano uses PoS while Solana relies on PoH. This has seen protocols like Ethereum moving from PoW to PoS to try and make its algorithm more eco-friendly. The trend is likely to be seen more in 2022 and beyond. This will likely make blockchain even a more attractive solution for many businesses.
Final thoughts
Blockchain technology has evolved quickly from cryptocurrency technology, and most people are accustomed to the enterprise tech disrupting the business landscape. The above are only some trending topics revolving around it and those we’ll see in 2022 and beyond. These include increased adoption of Metaverse, growing use of NFTs, and going for greener blockchain protocols.
Implementing blockchain in your business can create more scalable apps and processes for a more optimized workflow. Your business can gain all the benefits of blockchain technology. All you need is to consult the experts to get started.
Banking is an important sector of the world. People use finances daily, but it doesn’t mean they are completely protected from data breaches. This article discusses four of the most significant data breaches in banking…
We put a considerable amount of trust in our banks. They hold our money and sensitive data. We expect banks to fulfil their duty and provide protection. But unfortunately, there have been historical moments where banks have faced impactful data breaches.
If you are a victim of your bank suffering from a data breach that has impacted you, you could be eligible to claim bank data breach compensation.
To learn more about four of the most significant data breaches in the banking sector and steps banks need to take to keep online data safe, keep reading…
1. Heartland Payment Systems
Heartland Payment Systems is an American-based payment process and technology provider. In 2008 they suffered a cyber incident which impacted more than 130 million debit and credit cards. Some of the compromised data involved credit card numbers, card expiration dates and cardholder names.
One of the threat actors responsible for the breach was Albert Gonzalez, who during the years of his computer hacking, stole more than 170 million debit and credit cards and ATM numbers. During the Heartland Payment System cyber attack, he had two accomplices help commit the crime. As a result of his actions, Gonzalez received a 20-year prison sentence.
The data breach incident against the company resulted in them losing hundreds of thousands of customers and an impacted reputation. Since the 2008 breach, Heartland Payment Systems suffered another data breach in 2015, when their Santa Ana, California office experienced a break-in.
2. Experian
While we cannot consider Experian a bank, we felt this breach was significant enough to talk about, especially considering the company’s close relationship with the financial services and banking sectors.
Experian is an American-Irish company which is frequently used by corporations to process credit applications of individuals across the world, meaning it holds a considerable amount of personal data.
While a significant company like this would be presumed to have high levels of protection against data breaches, the well-known company has become a victim of many data breaches over the years.
One of their breaches, in particular, had a significant impact on their customers. It happened in 2020 when 24 million customers’ data was stolen after a South African employee fell victim to a threat actor by relinquishing a series of crucial, sensitive information. The data breach also impacted nearly 800,000 businesses.
Some of the personal information that was breached included:
Mobile phone numbersHome phone numbersWork numbersEmail addressesResidential addressesPlaces of workWork addressesJob titlesJob start dates
A year after the breach occurred, it was found that some sensitive data had been posted onto the dark web. This has since been deleted.
This isn’t the first data breach Experian has suffered, with a recent incident in 2022 exposing 15 million users’ sensitive details such as names, addresses, birth dates, social security numbers, driving licenses and passport numbers.
3. 2016 DOS attack on Lloyds, Royal Bank of Scotland and Halifax
During the incident, cyber criminals flooded the banking groups with millions of fake requests, which is known as a denial of service (DOS) attack. While no customer’s personal details were stolen in the cyber incident, each banking group was required to bring their systems to a halt to prevent the incident from escalating.
Similarly, the Royal Bank of Scotland suffered the same type of cyber attack on its online services back in 2015, which lasted for 50 minutes.
4. Tesco Bank
In November 2016, 9,000 Tesco Bank users suffered a financial loss that occurred over a period of 48 hours. The total loss suffered during the cyber incident was £2.5 million but has since been refunded to all impacted customers.
Tesco Bank was fined £16.4 million by the Financial Conduct Authority (FCA) due to the failure to protect its customers from the cyber incident. This was after the FCA analysis of the matter determined the attack could have been largely avoidable.
Data Breaches Can be Daunting
What we can conclude from this article is that there is no doubt that being involved in a data breach can feel incredibly daunting. It can be worrying to think about what would happen to your personal details and particularly more so with financial details, but there are things you can do to protect yourself. For more information, take a look at Forbes’s guide to protecting your sensitive information.
How do you protect your personal data? Let us know in the comment box below.
Please be advised that this article is for general informational purposes only and should not be used as a substitute for advice from a trained legal professional. Be sure to consult a lawyer/solicitor if you’re seeking advice on data breach compensation. We are not liable for risks or issues associated with using or acting upon the information on this site.
Bootcamps are en vogue in all sorts of industries, with the idea being that intensive training over a short period can bring newcomers up to speed with complex concepts in a flash.
This sounds good in theory, and in many contexts, it has a lot of clout. But the field of data science isn’t exactly suited to the quick and dirty approach to employee education.
Here’s why.
The competition is fierce
The first issue is that if you want to apply for positions which require a data science background, then even if you’ve undertaken a bootcamp, you’ll be competing against candidates with much more impressive qualifications.
That’s why bootcamps offer benefits in certain career paths, and not in others. For example, if you complete a front-end developer bootcamp at Altcademy.com, you’ll be in a stronger position to succeed when applying for jobs later on.
Data scientists, on the other hand, tend to have Masters-level education in a relevant subject under their belt, even if the role they are aiming for is on the bottom rung of the corporate ladder.
If you’ve already got a Masters, then a bootcamp could be a great way of refreshing your knowledge and skills. But don’t expect to stand out from a stack of resumes if a bootcamp is the only relevant certification you’ve attained.
The mainstream narrative is deceptive
Another issue facing data science at the moment is that there’s a lot of misinformation out there about how accessible the field is.
Read articles, watch videos or check out training course marketing and you’ll get the impression that this is a specialism that almost anyone can attain. Furthermore, it’s implied that you don’t need to work particularly hard to enter the echelons of data science.
What this doesn’t make clear is that only a tiny proportion of data scientists were able to get a job when starting from scratch in 12 months or less.
The majority spent years earning degrees, gaining experience and cutting their teeth in different roles before finally reaching the point where they could go pro. And so again, a bootcamp will only work wonders for those with a solid grounding in the right skills and knowledge already at their disposal.
The breadth of data science is a sticking point
While the term ‘data science’ is bandied around regularly, it’s worth noting that there’s not a single subset of areas that it covers, but rather a multitude of potential paths to take.
Because of this, no bootcamp or short-term training course can possibly encompass every conceivable facet of what goes into making a data scientist, because there simply won’t be the time.
A true data scientist will need to combine the training they receive with their own, self-guided learning. This has been the way of things for a long time and will remain the case indefinitely.
There are other stepping stones to take
A data science bootcamp can be a little like a get rich quick scheme, in that it promises the world but ends up falling short, and it’s only the fault of the participants if they don’t get where they want to be immediately.
The solution is to think carefully about your existing skills, as well as your circumstances, and see if there are different ways to gain data science-like experience without taking a course.
This might mean getting into marketing analytics, for example, in order to understand some of the tools and techniques which can later be applied to data science training. It’s about having realistic goals and knowing when claims are too good to be true.
Many organizations resist change, whether due to a fear of the unknown or a reluctance to leave the comfort of the status quo. Change is often seen as complicated, time-consuming, and expensive. But organizational change management is a necessary evil. The right approach can allow organizations to improve their operations, become more agile, and compete in the market better.
The first step in successful organizational change management is understanding how change happens. And although many factors contribute to organizational change, it’s safe to say that technology has been the biggest driver of change in recent years. From the rise of social media to the proliferation of mobile devices, technology has also helped adjust how organizations change. Here Are a few key areas where technology has promoted positive change;
Communication
Technology has improved workflow and facilitated and automated workflow by changing how people communicate in modern workplaces. Think of businesses before email, instant messaging, and video conferencing. The time it took to pass along information, receive feedback, and implement change was a slow, treacherous process.
Communication across various levels in organizations has become instant and collaborative. It has also removed the need for face-to-face communication.
Organization and Automation
Technology helps in keeping the business organized. With modern software, businesses can streamline processes that reduce errors, increase speed, quantity, and quality of work, and minimize costs. Today’s innovative software allows product managers to improve workflow and boost efficiency.
Product management software makes it easier for managers to track progress throughout each stage of achieving objectives and maintaining efficiency.
Better Collaboration
Organizational change management requires collaboration actress teams and departments. Technology has completely changed the way companies collaborate and fosters real-time connection anywhere, any time. This flexible connection encourages teamwork and less friction when implementing complex changes across large organizations.
Remote Work
Technology completely transformed the modern workplace. Instant and remote access is now possible because of mobile and cloud technology. As a result, there are now diverse, interconnected workplaces. They are joined by seamless connection, mobility, and virtual collaboration.
With the touch of a button, employees may now operate from any location thanks to cloud technologies. Collaborating with teams wherever they may be feasible, courtesy of virtual meetings.
Beyond the Tech
Technology can be an essential component in organizational change management. As illustrated, technology allows businesses to communicate change, track implementation, and receive feedback faster than ever. While technology has greased the wheels of organizational change management, it is not enough.
Identifying and redesigning processes, hiring the best consultants, and establishing a new system are just a few steps in guiding a business through organizational change. It’s also vital to ensure end-user adoption of the new technology through fully fleshed communication, stakeholder involvement, continuous improvement, and implementation of the new system.
To help you develop a change management plan, here are some essential things to consider:
Planning
Planning is a crucial step towards any change. No matter how small, crafting an actionable plan is the only way to achieve goals—initiating change without first deciding why and how is a sure way to wear out your employees and stakeholders. Taking the time to envision an end with a clear direction will make the change easier to embrace and implement.
Communication
Beyond the tech, there is much more to communication than the tools. There is no perfect way to communicate, but there are some things to remember. When communicating a change, it is crucial that the people on the other end are receptive and can understand the what and the why. Proper communication means keeping it simple and timely. There is such a thing as too much information. No need to overload employees and frustrate your team.
Open communication channels also allow for two-way communication and questions that may arise. Communication is the key to frictionless change.
Inclusion
As a business, while crafting, it is vital to carry employees along. It prevents business owners and stakeholders from making decisions in a vacuum. Employees are the people who will work around the changes made, so their input is crucial to success. Open communication channels create avenues for valuable insight and motivate your employees.
Evaluation:
Change never happens in a straight line. It requires frequent feedback, evaluation, and revision. Before, there should be clear KPIs to measure success and adaptation and establish a simple, pain-free method for collecting and implementing feedback. You’ll likely need to work on and improve the program/system repeatedly until it starts functioning properly.
Continuous engagement and collaboration
Implementing change is like creating a new product. The first version is never perfect. Research, testing, and iteration are necessary in times of change. The organization and not just a select group of personnel produce organizational change. For many business owners, change does not go beyond the key stakeholders. Still, the shift towards integrating change across the board and including everyone involved in the organization is necessary for better adoption and growth.
Every year, businesses lose billions of dollars to cyberattacks. Educating employees on the most common techniques used by hackers is an important aspect of cybersecurity.
The following list includes some of the most well-known ways that hackers try to extract sensitive data from personal devices.
Social Engineering
Cybercriminals know that people are the weakest links in a company’s cybersecurity policies. They exploit the natural tendency to trust or provide assistance to gain access to restricted information.
For example, rather than attempting to enter a business’ encrypted network, hackers will break into an employee’s social media or email account. Once inside, the hacker can masquerade as the individual and send messages that contain viruses or malware.
Hackers also manipulate employees by assuming the identity of a trusted source, which could be a vendor, financial institution, or even a government agency. They will send messages that imply the individual or the business is in trouble or must verify some information. This can be a very successful way to extract password information and personally identifiable data from individuals.
Fighting against social engineering attacks can be difficult, as hackers are becoming increasingly adept at replicating messaging from official channels. Employees on the receiving end of a social engineering attack should verify messages by contacting the company or agency directly.
Browser Malware
Hackers use the internet to advance cyber attacks on unsuspecting users. One of the most common types of attacks installs malware that can control a victim’s browser. The hacker can then force the browser to redirect the user to a different webpage.
For example, a user trying to complete a search on Google may be redirected to a different search engine. However, the site has been manipulated by cybercriminals to install spyware or malware onto the user’s device.
Further, if the user visits any sensitive websites during their session, the hacker may gain access to those passwords and information.
The malware that a browser attack installs onto a computer can significantly slow down the device. One of the most common signs of a browser attack includes lagging, an increase in pop-ups, and unfamiliar tools appearing on the browser or desktop menus.
Anti-virus software can scan and remove malware from an infected device. Browser developers also frequently update their security features to prevent the most common types of malware.
Website Spoofing
This form of cyberattack combines tactics from social engineering and browser malware. In this scenario, the hacker takes advantage of the credibility of a legitimate organization or business by copying their web address and web domain.
For example, a hacker may create a replica of the popular site eBay. The web address and page may look very similar to the official site. Unsuspecting users may not realize the website is spoofed and enter sensitive information.
While hackers can mimic many of the visual aspects of a website, there are some features that are impossible to replicate. Since all domains must be unique, spoofed websites often contain a typo or letter replacement. Additionally, spoofed sites generally do not have an SSL certificate, which secures the site against unauthorized access.
Man-in-the-Middle Attacks
Unlike the previously mentioned techniques, man-in-the-middle (MITM) attacks do not rely on the user to install malware or interact with a compromised entity. Instead, a hacker gains access to the information being transmitted between two legitimate parties.
For example, when a user purchases an item from a legitimate eCommerce site, they send their encrypted payment information to a payment processor to complete the transaction.
The hacker is able to eavesdrop on the interaction and gather personal information. In some cases, the hacker actually intercepts the information and funnels the user’s data onto their network.
Public wifi connections are some of the most common ways hackers set up MITM attacks. They may spoof legitimate free wifi networks, or simply wait for someone to log into their network. Any information that is sent during the session will be visible to the hacker. More sophisticated MITM attacks interfere with the SSL certificate.
Keylogging
Hackers deploy malware or spyware using one of the above methods. The program then monitors and records the user’s keystrokes. Hackers may also take screenshots to match login information with specific websites.
It can be particularly difficult to defend a business’ network from keylogging attacks as recording keystrokes is a common function in legitimate software. For example, many employee monitoring tools have keylogging capabilities.
To reduce the risk of illegal keylogging, employees should opt for two-factor authentication whenever possible. This means that in order to log into an account, the website will request authorization through a second device, usually a smartphone.
When two-factor authentication is enabled, hackers will not be able to access an account even if they have obtained the password.
There are a number of amazing AI companies. You may want to create an equally successful one. However, you won’t be able to do this without the best experts at your side.
There are a lot of factors that you have to take into consideration when hiring a company to help you develop AI applications. There is a huge lack of qualified AI developers, as a recent report from ZDNet recently showed.
Many companies will outsource their AI development projects, since they have trouble finding qualified experts on their own. Fortunately, this process can be a lot easier when you work with the right agency.
However, large companies and enterprises must be especially careful when outsourcing software development services to handle their AI projects. The right IT services & staff augmentation can make all the difference in the product you produce, which affects your bottom line.
With this in mind, let’s take a look at some key criteria when hiring a custom software development agency to help you make your AI startup succeed.
How Do You Find the Right Software Development Agency for Your AI Startup?
AI startups need the most qualified experts to help them create new applications. Unfortunately, choosing the best AI software development agency is easier said than done. The good news is that the process will be a lot easier if you follow these guidelines.
Choose The Right Service Type
There is a huge difference between ‘outstaffing’ and ‘outsourcing’ that many hiring agents do not fully understand until it is too late. Outstaffing means hiring employees housed under another company. Outsourcing is the more commonly used technique, which involves hiring independent contractors. Both are viable methods of IT staffing augmentation; deciding which to use is usually a function of the following metrics:
Decide On The Budget
Your budget will be one of the deciding factors in whether you outstaff or outsource. Outstaffing, because you are hiring employees, is much more expensive than outsourcing. Depending on the budget, outstaffing may be outside of your wheelhouse, and the software development staff augmentation decision could be make for you!
If you have a choice of whether to outstaff or outsource, then you may want to pay more attention to the other metrics below. However, most companies that hire out for IT staff augmentation services do prefer to outstaff for long-term needs. Although employees cost more, the benefits far outweigh the costs of having to re-teach company culture and projects to new people over and over again.
Rates & Business Goals
Developing AI software applications is not cheap. You want to make sure that you aren’t skimping on rates. However, you also want to make sure that you aren’t overpaying for a service either.
What are the reasons that your business is in need of staff augmentation? Does the work require highly skilled or low skilled labor? Does the scope of work involve deep dives into sensitive material that your company needs to keep private? If you are looking for highly skilled labor or the work involves company secrets, then you may want to consider outstaffing over outsourcing.
All told, what is the productivity of work that you are getting for the money you are outputting? When you consider rates, you may want to consider not only the wages you are paying, but the potential cost of insurance and education. Education is a cost that many companies do not consider. The learning curve that every new hire must take on, where (s)he is learning and low on productivity, is a real cost of business. There is an opportunity cost here of dealing with long term employees that also must be deeply considered.
Reputation
You want to make sure that the software development team that you hire understands the best practices. This includes ensuring that they know the relevance of agile development when developing AI applications.
You have to make sure that they actually have a good reputation for doing a good job in these regards. You should really only deal with companies that have been marked as a top rated software development agency. Software is an intense industry that obfuscates a great deal of itself from the outside world. If you are not an insider, you can get taken for a lot of money and time before you find the right fit, because everyone knows the lingo that makes the agency sound good. If you aren’t a tech person by trade, you can easily be fooled into thinking an agency can get you the right people when they are really not of the specialty you need.
The reputation of a software agency is essential to consider. This is the way that you, as a tech outsider, can know how effective an agency is in creating true synergy between the employees who will be helping you and your core staff. This synergy is essential in getting work done in a productive way.
Communication
You may not think that communication is a big deal when you are dealing with employees or contractors that you do not expect to make a part of your core staff. Nothing could be further from the truth. In order to generate successful projects in a productive way, you must have good communication between your new hires and your core staff.
If your core staff does not have a tech background, it is essential that your software agency bring you people who know how to explain what they are doing in a non-technical fashion. After all, the products that you come out with as a group most likely need to be usable to a non-technical audience. Why not start with you?
Even if your software agency is creating software for internal use, the communication aspect of the process is still a huge part of success. Your employees need to know what the new software can do in layman’s terms so that they can make best use of it when the software developers are not on hand. This is especially true if you are making remote hires — these people will not be in the office, and may not even be in the same time zone to ask questions of.
Troubleshooting capabilities
There is no software project that goes perfectly from the very beginning. A few hiccups here and there should not upset you or make you believe that you have hired the wrong team. You should look at how the team responds to the inevitable bugs in the system, however.
Where to Find the Best Software Development Agency for Your AI Startup?
When you are running an AI startup, word of mouth is the best way to find a software development agency that you can trust. You may also take a look at successful products that come from your competitors. If you can find out who built their software, then you may have a great candidate for your own.
Make sure that you take the appropriate time to go through the entire hiring process for a software agency. You may take a bit more time up front, but this due diligence will definitely pay off in the end. It is much better to spend a bit of money and time looking for that perfect fit than it is to hire quickly and face communication issues or a team that cannot handle troubleshooting.
Even worse is if you outsource when you should have outstaffed and vice versa — make sure that you understand the goals of your company inside and out before making this crucial decision. Keep this in mind, and you can help your company immensely with the right staff augmentation!
Are you launching a new AI startup? You will discover that there are a number of opportunities and challenges of creating a company that develops new AI algorithms to solve problems.
The demand for AI technology has surged in recent years. One analysis indicates that 90% of companies have made investments in AI and 37% actively deploy it. AI startups have a burgeoning market that they can serve.
Unfortunately, they also have challenges, such as choosing the right business model for their AI startup. One of the biggest issues that AI entrepreneurs must deal with is finding the right employees. Unfortunately, they find this is easier said than done.
Of course, the skill shortage doesn’t just apply to AI developers. There is also a shortage of skilled marketers, financial professionals and other experts that AI startups depend on.
Despite the skill shortage, it is essential for AI companies to find the right employees to operate effectively. They will need to know what skills to look for when building a pool of talented employees to serve their business.
Seek Applicants with the Right Skills for Your AI Startup
As an entrepreneur striving to find employees for your AI startup, you will have to read many applications and find the most suitable candidates for certain positions. You can’t waste time overthinking and overanalyzing CVs and cover letters.
Here are some useful suggestions to understand what to focus on when scanning an applicant’s resume and message. Read more about what personal and technical skills you should be looking for in a candidate in the following guide that New Millennia helped create.
Personal Skills
Many AI entrepreneurs and founders of other tech companies make the mistake of putting all of their emphasis on technical skills. This is a huge mistake, because even technology companies need employees with soft skills as well. In fact, one expert points out that 85% of the success in the technology sector can be attributed to soft skills like good communication. AI companies are no exception.
Personal skills are soft skills that people either possess naturally or develop and improve over time. They refer to personal qualities that are transferable to any type of role. This skillset helps an individual to perform better at work. Read the following examples of such personal skills you should search for in an applicant to understand why they’re necessary.
Motivation
The AI sector has become very competitive. Entrepreneurs in this sphere need employees that are self-motivated and ambitious to help them succeed.
A motivated employee has an internal drive to perform well at work. These employees help save time and money, as they require less guidance. They have a greater level of independence regarding their duties and projects, which is highly productive and effective for the company. A self motivated employee will inspire their colleagues to do their best when it comes to their roles, as well.
Communication
Communication is what helps to convey factual and complex information in a clear and concise manner. People that showcase a great level of skill regarding communicating with others can use many channels, like phone, email, and face-to-face talks, to send their message across. A good communicator is someone who understands how to listen actively.
Flexibility
Flexibility is another key skill that means being able to adapt easily. Be it new duties, positions, or obstacles, a good employee should know how to adapt to various situations quickly. As a recruiter, you should always look for applicants that can respond to complex scenarios in an efficient manner. What’s more, a positive attitude helps showcase the candidate’s ability to adapt, so keep this aspect in mind when you’re interviewing somebody.
Problem Solving
Problem solving refers to the ability to find solutions to any issues in quite a timely manner. Organizations need employees with problem solving skills to evaluate situations and come up with strategies in order to fix the issue. It’s important to find candidates that can see any situation in a complex way, from more than just one perspective, as well as think of the best tactics to handle the problem.
Technical Skills Such as AI Programming
Developing AI technology requires decent programming skills. You obviously need to hire developers that understand the programming languages that help create AI applications. Python is one of the best languages for data science and AI, so it is a good idea to find Python programmers for your AI startup.
Technical skills are hard skills that people can only learn from experience. People can develop technical skills through courses, various forms of education, and actual work expertise. This skillset is typically particular to certain jobs and fields. Read examples of some key technical skills candidates should showcase in order for you to consider them for the role and get a better understanding of their importance.
Industry Specific Skills
Below are a few examples of job specific skills you should look for when you read applicants’ CVs and cover letters, depending on the role you’re hiring for:
Data Analysis
As far as Data Analysis is concerned, potential employees should have an extensive knowledge of quantitative research, quantitative reporting, compiling statistics, statistical analysis, data mining, and big data.
Marketing
The old adage that you can build a better mousetrap and the world will beat a path to your door doesn’t hold up. Even when you are developing stellar AI applications that blow your competitors out of the water, you need to have a sound marketing team by your side.
In the marketing industry, some key technical skills you should look for are expert knowledge of different social media platforms, a good understanding of Search Engine Optimization (SEO), copywriting, and the ability to operate Content Management Systems (CMS).
Graphic Design
Regarding Graphic Design, it’s essential for applicants to be familiar with branding, Adobe Suite software, user modelling, responsive design, print design, and typography. Graphic design skills are essential for many Internet-based AI startups, since they need to make sure that their interface is easy to navigate and aesthetically appealing.
Software Development
In the Software Development field, it’s important for candidates to know coding, algorithms, applications, design, security, testing, debugging, modelling, languages, and documentation. This is essential for AI startups.
Technical Support Skills
People in charge of technical support are vital in every company, as they ensure the safety of computer systems, by being able to troubleshoot any issues that may arise. These skills are also essential when configuring new hardware, performing regular updates, and assisting other employees in creating accounts, resetting passwords, and dealing with any difficulty regarding the online system. Technical support teams help restock equipment and maintain records of software licenses, as well. This is why anyone with this type of skill is a great asset to any organization.
Project Management Skills
Being able to manage people, budgets, and resources in an efficient manner is one of the most important technical skills a candidate can have. Applicants with project management skills are always in high demand in different fields, such as construction and digital marketing, for example. A few key project management technical skills you should look for are project planning, task management, budget planning, risk management, and knowledge of project management software.
When working in-house, recruiters often have several other duties, aside from reviewing CVs, which requires a great deal of attention in itself. Such responsibilities cover various aspects, including the finances of the recruitment agency. For smaller recruitment agencies, there are outsourcing options available to save time and resources, so that recruiters can focus on reading applications properly.
Find the Right Skills for Employees When Growing Your AI Startup
AI companies need the right employees to thrive. You will have an easier time growing your startup if you follow these guidelines to hire the best talent.
Positive customer experience sits atop the most valuable things critical to the longevity of any business. It helps build brand reputation, enhances a company’s visibility, and encourages customer loyalty, which translates to increased revenues.
Statistics show that 93% of customers will offer repeat business when they encounter a positive customer experience. For these reasons, fintech companies actively seek opportunities to nurture better customer experiences.
Big Data is the collection and processing of huge volumes of different data types, which financial institutions use to gain insights into their business processes and make key company decisions.
This article focuses on big data in financial industry, its role, and how it helps fintech companies protect their customers and improve the customer experience.
The Role Of Big Data In Fintech
We have witnessed huge advancements in the financial industry’s service provision, thanks to big data.
Big data in fintech plays a vital role, providing crucial content that impacts service delivery. Through big data insights, financial institutions can offer personalized services as well as predict consumer behavior. They can also anticipate industry trends, assess risks, and make strategic steps to elevate the customer experience.
How Big Data Helps Fintech Companies And Startups To Better Serve And Protect Their Customers
Fintech analytics helps businesses in the financial and banking industry offer satisfactory services by:
Enhancing View Of Customer Profiling
Big Data provides data that fintech companies can leverage to build customer profiles. Through segmentation, these institutions can easily understand customer wants, needs, and expectations. They can also use this information to analyze consumer behavior and create tailored services.
Improving Risk Assessment
Data analytics fintech provides crucial information financial institutions need to build a robust risk assessment strategy. This allows businesses to identify potential risks fast and avoid them or immediately find the appropriate mitigation strategies.
Improving Security
Fraud is a cause for concern in the banking industry, especially now that mobile banking takes a center stage. However, fintech businesses can use big data and machine learning to build fraud detection systems that uncover anomalies in real time. They will detect illicit activities such as suspicious transactions, logins, and bot activity.
Forecasting Future Market Trends
Start-ups and established fintech companies can use big data to understand the changing financial industry. With access to previous data, these companies can monitor purchasing behavior and predict future trends. As a result, they can make crucial decisions that elevate customer experience, based on these facts.
Personalizing Assistance With Chatbots
Businesses in the Fintech industry can harness the power of big data to personalize chatbot customer service. AI-powered chatbots will access raw data, allowing them to answer customer questions accurately and straight to the point.
Ensuring Friction-less Multi-channel Experience
Changing consumer preferences and the need to capture market share drove financial institutions to embrace multi-channel service delivery. To ensure their customers have a satisfactory experience, financial businesses will use big data analytics to tweak their services across various platforms to suit a customer’s needs. They will also use historical and real-time data to identify possible customer challenges.
How Can Big Data In Fintech Influence The Customer Experience?
Data science in fintech has influenced customer experience in more ways than one. Thanks to it, the financial industry can now:
Analyze customer behavior to propose new products
Customer likes and dislikes shift depending on need. Historical financial big data helps businesses scrutinize evolving customer behaviors, allowing them to come up with invaluable products and services that streamline banking processes.
An excellent example is how the Oversea-Chinese Banking Corporation (OCBC) designed a successful event-based marketing strategy based on the high amounts of historical customer data they collected.
Better UI/UX based on A/B testing
Thanks to big data, Fintech businesses can access real-time data that shows how users interact with their products, the average time spent on the portal/system/app, and the most-used features.
With such information, these businesses can assess two product versions to see which offers a superior UI/UX design. Additionally, they understand in-depth the differences between the products and how they affect the customer experience.
Analyze customer satisfaction survey results.
Big data evaluates customer satisfaction rates from survey results. For instance, it helps financial institutions identify the rate of and reasons for customer churn, helping them devise newer ways to keep their audience interested in their services. Also, it has been used in the management of product and feature requests, as well as in analyzing customer support ticket trends.
Scoring
Financial companies can provide accurate credit ratings based on the number of missed or delayed payments, how much money a customer owes, and how promptly they make payments.
Fraud detection
Big data for financial services in conjunction with digital technologies such as machine learning has proved fruitful in the detection of suspicious activities. They prevent various types of sophisticated fraud and elaborate hacking attempts.
Deutsche Bank is one such financial institution that is taking advantage of big data analytics to identify techniques used in money laundering, secure the know-your-customer processes, and prevent credit card theft.
Measure the ROI from delivering a great customer experience
With insights from big data, fintech companies can measure the success of their efforts geared toward providing a positive customer experience. By measuring ROI, they can identify where to improve and what to focus on.
The Fintech Sector is Exploding Due to Big Data
Big data is, without a doubt, a tech advancement revolutionizing the Fintech industry. It allows access to large data volumes that can be used to improve a customer’s user experience in retail banking, online trading, and other financial processes. However, to take full advantage of big data’s powerful capabilities, choosing BI and ETL solutions cannot be over-emphasized.
ETL and Business Intelligence solutions make dealing with large volumes of data easy. They support system integrations, helping create reliable data pipelines that deliver actionable insights. Additionally, they help fintech companies predict market trends, driving profitability.
Machine learning technology has become invaluable in many facets of the IT sector. A study by Markets and Markets shows that the market for machine learning technology is growing over 44% a year.
One of the biggest factors driving the demand for machine learning technology is a growing need for cybersecurity solutions. Cyberattacks are becoming more common each year. Fortunately, machine learning advances have made it easier to stop them in their tracks.
One of the biggest applications of machine learning in cybersecurity is with stopping digital attack surfaces. In order to appreciate the benefits of machine learning in this application, it is important to understand the nature of these cyberattacks and the best ways to prevent them.
How Can Machine Learning Technology Stop a Digital Attack Surface?
With organizations expanding their digital footprint to reach more customers on more devices across more countries, their exposure (attack surface) to both internal and external threat actors increases. To make matters worse, a number of cybercriminals are using AI technology to conduct more devastating cyberattacks than ever before.
The good news is that cybersecurity professionals an use machine learning as well. There are a growing number of ways that they are able to fortify their defenses with machine learning. This includes using machine learning to stop digital attack surfaces.
But what are digital attack surfaces and what can machine learning really do to stop them?
Overview of Digital Attack Surfaces
It might seem like an increasing attack surface is simply a recipe for disaster where security breaches are inevitable. Luckily this is not the case. Many organizations join hands with attack surface mapping and monitoring specialists to quantify their risk and introduce remedial steps to protect against breaches.
The term digital attack surface refers to the sum of all the possible attack vectors your organization has exposed to threat actors, that could be utilized to launch a malicious attack against your organization. Simply put, what technologies can threat actors utilize to gain access to your organization?
At first glance, it might seem to be an easy assertion to simply list all networked nodes. As soon as a closer inspection is done though you will soon find many possible vectors that you did not previously consider as vulnerabilities.
The most common kind of attack surface vector is those nodes that we know of. This would include all the organization’s managed technologies. From the workstations and servers to the outward-facing websites and web services hosting public APIs.
The second kind of attack surface vector is all the managed technologies that have fallen outside of the organization’s direct reach of influence. Whether risks have been introduced without the knowledge of the IT team, like shadow IT, for example, or whether there are online resources that have been forgotten about.
And thirdly, if the areas mentioned above are not enough, organizations still need to deal with threat actors who can create resources of their own. From malware and social engineering to resources specifically created to masquerade as your organization to harvest credentials and other sensitive information.
How Can Machine Learning Stop Attack Vectors?
There are a lot of benefits of using machine learning technology to stop cyberattacks. Some of them are listed below:
Machine learning helps cybersecurity professionals automate certain tasks that would otherwise be very repetitive. This frees their time to focus on more essential threat analysis tasks.Machine learning technology can be trained to recognize threats that would otherwise be difficult to detect. For example, it can perform risk scoring analyses on emails that might be used for phishing. Machine learning helps identify weak points in the cybersecurity infrastructure, such as outdated firewalls. It can ping the cybersecurity team to make appropriate modifications.
As a result, machine learning is invaluable in stopping attack vectors of all types.
Five common attack vectors that machine learning must be taught to fight
There are a number of different attack vectors that cybercriminals use. Machine learning technology must be trained to address them. The biggest are listed below.
User and cloud credentials
Account restrictions and password policies are among the most neglected security mechanisms and pose a great risk to organizations, globally. Users get into the habit of reusing their organizational credentials on their social media profiles, and unintentionally supplying their credentials during a data leak. The other dimension is where administrators do not apply the principle of least privilege. The combination of these vectors can result in devastating data breaches.
Third-party APIs and web applications
APIs are an attractive target for hackers because they allow attackers to get access to otherwise secure systems and exploit weaknesses. APIs are frequently vulnerable to similar vulnerabilities as web applications, such as failed access controls, injections, and security misconfigurations because of the automated nature of their users. Newer machine learning driven cybersecurity tools are trained to recognize these threats.
Email Security
Email security is too often overlooked. You might be more appreciative of the need to train your machine learning tools to stop phishing attacks if you realize that one out of every 99 emails is a phishing attempt.
Security policy frameworks and similar email authentication measures need to be in place to protect against email spoofing from threat actors. The second major risk introduced by email is malware. Servers that are not configured to scan eliminate high-risk attachments open the door for external threat actors to gain access through social engineering and malicious attachments.
Shadow IT
The use of computer systems, hardware, applications, and resources without express IT department authority is known as shadow IT. With the popularity of cloud-based apps and services in recent years, it has risen at an exponential rate. While shadow IT can potentially boost employee productivity and promote innovation, it can also pose major security concerns to your organization by leaking data and potentially violating regulatory compliance standards. You need to make sure that machine learning tools are trained to recognize the weak points in your shadow IT system.
Unmanaged tech assets
As cloud technologies advance, organizations may still have connections to legacy systems and vice versa. These could have also been approved connections from enterprise applications to decommissioned third-party suppliers. They could also be internal linkages to firm IP addresses or expired storage domains. These unmanaged assets are almost always running outdated software with known vulnerabilities that have never been fixed, making it easy for skilled threat actors to exploit.
Machine Learning is Crucial for Stopping Digital Surface Attacks
To take back control of your digital attack surface, holistic attack surface visibility must be acquired. Machine learning technology makes this task much easier. This will allow you to efficiently identify and manage the risks they pose. Cyber security visibility can be rapidly attained by partnering with an industry security specialist who can provide real-time monitoring tools to remediate risks before breaches occur.
One of the biggest benefits of big data in healthcare has been in the field of virtual healthcare. Demand for virtual healthcare services exploded during the pandemic. Big data technology is helping make this new field even more promising.
Big Data Technology is Driving Major Advances in Virtual Healthcare
Doctors and other healthcare professionals often treat patients in person in a location like a hospital, clinic, or medical office. However, thanks to developments in digital technology, medical practitioners may now digitally diagnose, treat, and manage the care of their patients.
Doctors have used different types of big data technology to make the most of the services that they offer to their clients. One of the biggest ways that they have helped improve patient care is by offering telemedicine.
They can evaluate data from IoT devices and use it to forecast healthcare trends and identify individual patient needs. IoT is incredibly important in healthcare and is even more helpful in telemedicine since doctors need more diagnostic tools to treat patients.Big data helps doctors make sure patient electronic records are complete. This makes it easier to make more informed diagnoses.They can use big data to improve patient outcomes by taking advantage of all extraneous data on major healthcare trends.Big data makes it easier for doctors to leverage the benefits of healthcare apps.
Now that you understand the benefits of using big data in virtual healthcare, you might want to visit some of the benefits of telemedicine.
Reasons More Healthcare Providers Take Advantage of Virtual Healthcare With Big Data
Virtual healthcare, or telehealth, witnessed unprecedented growth during the COVID-19 infections and has now gained laudable recognition in the healthcare sector, adopted by many. That is because while the pressures on the healthcare ecosystem have increased with the pandemic, telemedicine has aided with the social distancing measures put in place and continues to make it accessible, affordable, and possible to treat patients with mobility issues. Fortunately, big data has made virtual healthcare more feasible than ever, as stated above.
As this sector continues to expand, important technological use trends have evolved that will positively influence the future development of virtual healthcare services. Some of the benefits of using big data to improve telemedicine are listed below.
1. Improved Treatment of Chronic Conditions
Worldwide, chronic diseases like diabetes, heart disease, lung disease, Alzheimer’s, and kidney disease affect 1 in 3 individuals. Most of the time, people may avoid and treat chronic diseases by altering their lifestyles and receiving preventative treatment. The majority of these patients, however, do not complete their treatment, do not take their repeat prescriptions or renew them, and do not show up for their scheduled follow-up sessions to assist them in managing their symptoms.
This disregard for a treatment plan increases the severity of illnesses and costs the healthcare sector billions of dollars annually. Telehealth can increase patient participation and adherence to a treatment plan while simultaneously lowering the care plan’s cost.
2. Increasing Acceptance of Virtual Healthcare
Virtual healthcare, or telemedicine, which was once widely embraced as a method to reduce the amount of community transmission during the peak of COVID-19, is now seen as a financially viable first line of therapy for follow-up and non-urgent consultations for many patients.
Today, many patients utilize telemedicine to have prescriptions renewed, get ready for a visit, examine test results, or get information. This expansion is apparent since telehealth usage has stabilized above pre-pandemic levels. We may anticipate seeing healthcare providers and insurance companies collaborate to increase telehealth’s accessibility and availability.
3. Increased Attention to Mental Health Wellbeing
When the pandemic hit, mental health services were interrupted. Individuals already getting treatment found their support groups disbanded, their clinic visits canceled, and their options for coping with their symptoms severely restricted.
Many therapists, counselors, and medical professionals have rapidly started using video conferencing to help their patients. Thus, teletherapy and telepsychiatry were developed. With the advent of virtual care settings like Ravkoo Health, which offer a wide range of services from online consultation to at-home labs to lifestyle support to prescription delivery, it is now possible to meet everyone’s essential needs.
4. Improved and New Data Sharing
It is nothing new that telehealth systems provide more user-friendly and practical data exchange, resulting in an upward growth curve. For example, several telehealth applications integrate with and connect with fitness apps to acquire data such as step count and heart rate directly from a person’s devices. When combined with electronic medical records, this offers medical providers a complete image of a person’s lifestyle and aids in painting a clearer picture of their present health.
Telehealth applications’ notion of integrated data sharing is motivated by interoperability, which is the capacity to access, share, integrate, and jointly utilize data in a coordinated manner inside and across multiple organizations. The future of telemedicine lies in this, and medical professionals must realize that to optimize patient advantages, they must move beyond merely presenting and documenting information.
5. Remote Patient Monitoring and Wearable Technology
Telehealth is becoming important for those with chronic diseases, which brings us to the next trend for the future: wearable technology. These gadgets have made it simple and effective for the healthcare sector to start remote patient monitoring. They let medical professionals observe their patients’ activity levels, heart rates, blood pressure, sleep patterns, and glucose levels in real time.
By integrating these devices with a secure telemedicine platform and electronic health records, members of care teams can take action at the first hint of a problem. So long as patients have faith in the security and privacy safeguards in place, wearable technology and the sharing of data produced by these devices with healthcare practitioners are certain to expand.
6. Convenient Pediatric Virtual Care
A sick child is never easy to monitor. Children are frequently good at hiding their symptoms, struggle to communicate, and frequently exhibit shyness or fear while speaking to medical professionals. When they require long-term monitoring, this becomes very challenging. However, childcare monitoring in Ravkoo Health can make it more comfortable for parents and lower the cost of high-quality care.
The use of pediatric telehealth will increase over the next several years thanks to the next generation of parents, who are more accustomed to utilizing virtual technology than prior generations.
7. Growing Technology Investments
Lastly, telehealth cannot exist without the necessary technological foundation. The acceptability of virtual healthcare services is made possible by the development and widespread usage of digital health technologies, such as COVID-19 tracing applications, wellness trackers, telemedicine, and virtual health apps, all of which can be used from the comfort of home. Further knowledge and technological investments will make telehealth projects and applications more successful.
The pandemic brought to light the labor crisis that has existed for some time and the lack of healthcare personnel. However, the workforce will experience even less stress due to investments in technology that supports the expansion of telehealth, and they may even be able to provide better care.
Big Data Leads to Massive Breakthroughs in Telemedicine
Big data has led to some tremendous changes in the healthcare sector. One of the most important has been the evolution of virtual healthcare services.
Some noticeable trends have become evident since the widespread adoption of telehealth services. The healthcare sector benefits greatly from telehealth, and we will use this ground-breaking technology well into the future.
Leading platforms like Ravkoo Health have demonstrated that telehealth services make healthcare more accessible to people and can improve public health, increase access to treatment, lessen the strain on the medical staff, and ease the financial strain.
