Technology is constantly improving and enhancing our business processes. Ben Bennett, Managing Director at mixed reality technology company Luminous Group, outlines just some of the ways XR is set to revolutionise the supply chain.
Cross reality (sometimes called mixed reality, or XR) is a combination of reality and the virtual. You may have seen apps that allow us to use our smartphone camera to add virtual furniture into our rooms and digitally paint our walls — these use XR technology. But, did you know cross reality also has some great uses in business and finance? In this article, I’ll be telling you just some of the ways XR can transform the supply chain and keep costs down.
Improved efficiency in warehouses
XR has the potential to greatly improve the efficiency of warehouse logistics. Processing, picking, and packing can harbour some significant costs, but XR headsets have the power to reduce these by making the processes more efficient.
XR can optimise each process to be as accurate as possible. Often, picking can take time and is open to human error. XR allows users to scan barcodes, objects, and shelf placement to seamlessly navigate warehouses and pick the correct products at a much quicker rate. These XR headsets still allow warehouse staff to manually pick objects, while reducing the risk of human error, which can cost a lot to correct.
Improved transportation of goods
XR can also help to reduce the risk of products going missing during transportation. XR headsets can be used to scan the inside of freight trucks, measuring depth, and scanning the area to work out the number of palettes or parcels present. Staff can then check that the number matches up to how many there should be, and that there are none missing, before sending them on their way. The technology can even give specific instructions on how to best arrange parcels, tailored to the individual situation and making the whole process more efficient. This opens up the possibility for staff to transport larger amounts of products at any one time.
Improve logistics training
Training can take a lot of time and effort, but XR can make learning how to use operations and systems a lot easier. Gone will be the days of unengaging training videos, because this new technology has the potential to create realistic and fully immersive simulations. This means that staff can learn exactly how to act in certain situations, without the need for disrupting the real logistics environment. This is also a lot safer, as the XR technology can create situations for training that you otherwise wouldn’t be able to do without risking harm to your staff.
Incorporating XR into the management of your supply chain could go a long way to making your processes more efficient. From picking, packing, transport, and training, XR is set to streamline each task, reducing the chance of human error and saving you time and money in the process.
AI: CUSTOMER FACING EMPLOYEES’ BEST FRIEND IN THE FINANCIAL SERVICES INDUSTRY
By Ryan Lester, Senior Director, Customer Experience Technologies at LogMeIn
We’ve all heard the old saying “money talks.” Well when it comes to customer loyalty and retention, good customer experience talks much louder, with 30% of customers leaving a brand and never returning due to a bad experience.
The truth is, there are a lot of companies with similar products and services, but that doesn’t mean that differentiation is impossible. So, what’s the solution? For financial services, large and small, customer experience is becoming the key competitive differentiator and the best way to deliver an impactful experience is to empower customer-facing employees to do their best work. Artificial intelligence (AI) is enabling these employees to create remarkably better customer experiences, resulting in customer loyalty, advocacy, and overall growth.
For financial institutions that have been considering new strategies for improving the quality and efficiency of their customer experience, here are a few ways AI can enable them to deliver the “human factor” that good customer experience demands whilst ensuring customer facing employees can provide a more positive experience for customers.
Increase employee productivity
How much of employees’ time is spent searching for answers to questions? Do they ever have to put customers on hold or even step away to get additional help? AI helps provide front-line employees real-time guidance so they can spend less time looking for information and more time solving problems. An AI-powered chatbot, for example, can be listening in the background of a conversation helping point employees to the right data, solutions, and processes to resolve customer issues faster than ever before.
Deliver a consistent customer experience
When banking customers engage with their financial institutions, they measure the speed and accuracy of the service through two criteria. First, how quickly can the system access their account and deliver the correct information? Is it faster than a human could type it in and share it? And second, if they eventually do need to be connected to a live customer support agent, is their information captured and passed along accurately? AI technology takes those general queries off the customer support team’s plate, providing a quick, accurate, and effective response. If a query needs a more in-depth response, AI can hand it off to support staff to address.
Not only this but leveraging a centralised, AI-powered knowledge solution ensures every employee has access to the same, updated information, so no matter who the customer speaks to, they can be assured that employee responses are both consistent and accurate across the board.
Accelerating employee training and onboarding
Like any industry, employee turnover is inevitable and can be costly. But, not training new employees correctly or in a timely manner could be much more costly. When it comes to financial services there is a lot to learn, whether it is something simple like the process for checking an account balance to all the nuances associated with mortgage loans. AI can support on-the-job training by helping new employees answer questions confidently, correctly, and much quicker than they could before.
Improving employee satisfaction
Today’s banking customer has all kinds of new ideas about their banking experience. “The Amazon Effect” has successfully raised consumer expectations to the extent that a consistent, personal, and relevant experience is the new normal. As a customer, how many times have you been told “I’m sorry, I don’t know the answer?” Customers want solutions to their problems and employees want to be able to deliver those solutions as efficiently and effectively as possible. AI assisting in the background helps minimise those negative moments – making employees job easier, less stressful, and overall more enjoyable.
Identify knowledge gaps
Do you know all the questions employees are getting asked? Do you know what’s easily answered and what’s not? Real-time insights allow knowledge managers to keep up to date on frequently asked questions and gaps in current resources. This allows them to strategically improve or add content where needed.
Augmenting customer service
Whether talking with an AI chatbot or a personable customer service team member, the modern banking customer has high expectations for convenience, speed, and security. Which means that the technology you choose to deploy and how you deploy it is now just as important as who you hire and how you train them.
Today’s AI solutions won’t replace customer service agents or get in the way of the human factors that drive the customer experience. On the contrary, they augment it, allowing the business to do more without adding human resources. The higher the quality of a AI chatbot solution, the better it will be at taking the routine requests off the plate of customer service agents—giving them more time to provide a personalized and positive experience for customers.
BEFORE THE INK IS DRY: CORRECTING BIOMETRIC SPOOFING MYTHS
Eric Setterberg, System Design Engineer at Fingerprints
Biometric authentication is highly robust, and the latest solutions offer considerably greater security than their authentication predecessors: PINs and passwords.
But as biometrics moves into new areas such as payments and access control, privacy and security concerns are rising. Biometrics has long been subject to scrutiny, with many elaborate examples of people working to trick biometric sensors to crack devices in the media and online.
To ensure the continued adoption of biometrics, it is important to shine a light on the reality of biometric spoofing.
The Evolution of Biometric Solutions…
The first use of fingerprints as forensic evidence was in an Argentinean court case in the late 1800s. With the technology still in its infancy, this was done manually and by eye, comparing latent residual prints lifted from crime scenes to charts of inked fingerprints obtained from the suspects at arrest.
A few decades later, the FBI began collecting fingerprints of criminals and civilians. They also introduced the automated comparison of fingerprints by computers in the 1970s. These “traditional representations” have now been standardized by ISO and ANSI.
… and their Spoofs
The earliest and simplest of these matching devices were easy to spoof. Really, all you needed was a photocopy or a good image of a fingerprint to make a successful spoof.
But as biometrics moved to more advanced technology, the game for biometric ‘spoofers’ has changed and the task of crafting fake fingerprints is considerably more difficult.
The biggest boost for biometric security, however, came with its introduction into mobile phones.
How Mobile Changed the Game
Before the widespread integration of fingerprint sensors in smartphones, the technology underwent significant evolution. No operator wanted to use large biometric sensors in modern phone designs. Sensors had to become much smaller to reach the perfect price and design point for the mobile world, but this meant needing to capture data from a smaller surface area of the finger.
To maintain the security of these smaller sensors, algorithms evolved significantly in order to utilize a greater amount of data per unit area. These mobile-driven hardware and software changes resulted in the optimized image capture of modern touch sensors.
As a result, tricking these systems now requires a considerably higher level of detail to be reproduced correctly for a match to be successful, far beyond rudimentary gummi bear spoofs and photocopies…
Setting the Perfect Spoofing Scenario
Compromising fingerprint authentication via spoofing can still be done, even with all the technological advancements. However, it now requires considerable care, skill, money, and time. And to start, a good latent print…
To retrieve a latent print that’s high quality enough to work, you either need a willing volunteer to lend you their finger, or the commitment to stalk a victim until a viable fingerprint can be retrieved. Even with a decent latent print, modern spoofs then require advanced photoshop skills and/or a lab to successfully convert latent prints into effective moulds.
So – what about those articles boasting how easily they have hacked the latest smartphone device’s fingerprint sensor?
In fact, there are only two instances of fingerprint spoofing seen in the media nowadays: proof of concept and cooperative spoofs. Lay enthusiasts and media go through the effort of setting up a lab to create spoofs with latent fingerprints either from themselves or cooperative volunteers. Even the most successful of these take months of work, a highly skilled team, and the perfect scenario of circumstances.
Put simply, the effort required for spoofing modern fingerprint sensors cannot be applied at any scale. Each biometric spoof needs to go through the same laborious process and clinical conditions. So, if you can bring together a willing group of spoofing enthusiasts, tricking a biometric device could earn you fifteen minutes of fame on the internet, but it is likely to be conducive to a successful criminal business plan…
A “How” Without a “Why”
Spoofing biometrics remains technically possible, and there will always be those up to the challenge of trying to hack the latest technology. But the reality is that modern biometric solutions require more time, skill, and frankly, luck, to successfully spoof than ever before. Not to mention that tireless R&D work is continuously strengthening spoofing resistance. And, as use cases start to combine multiple biometric authenticators, such as combining fingerprints with face or iris to perform an authentication, spoofing will only become more complex.
By comparison, hacking PINs and passwords is considerably simpler and more scalable, making it far more lucrative. And, criminals generally take the path of least resistance.
For the average consumer, greater use of biometric authentication is not only a means of simplifying authentication, but dramatically improving the security of their devices, applications, and personal data. With PINs and passwords still the most common authentication method outside of mobile, it is imperative that the true security and advanced nature of modern biometric authentication solutions are understood.
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