When digital disruptors squeezed their way into financial services industry, one could think banks were doomed. Fintechs are luring customers away with better online service, lower fees, and cheaper transfers. Consider a huge cost of digital transformation for banking corporations and you see legacy players can have a hard time catching up with the newcomers. Apparently, the banks were not going to simply give up. Over the last five years, they spent tens of billions of dollars setting up innovation hubs, buying competitors, and changing operations.
Solving business problems with blockchain ensures efficient functioning of an enterprise. When an organization suffers a loss or a specific problem that manages to disrupt its rhythmic flow , authorities frantically search for options that can help them solve the problem. Blockchain is a technology that focuses on increasing transparency and introducing decentralization that will allow the technology to enable everyone on the network to view information stored on ledgers. Blockchain has many applications that contribute to its popularity amongst people. Here are four common business problems that can be solved using blockchain.
There are only two cardinal rules of cryptocurrency that arise directly from public key cryptography. As you probably know, modern cryptography is based on paired keys, a public key and a private key. Because of the blockchain, public keys and incidentally wallet addresses should be verified before sending. Due to the principle of immutability and the lack of a trusted intermediary, there’s no way to contest or reverse a transaction once it’s been made.The second law is simply that the owner of the private key is the owner of the wallet and all the funds therein.
Data clustering is the classification of data objects into different groups (clusters) such that data objects in one group are similar together and dissimilar from another group. Many of the real world data clustering problems arising in data mining applications are pair-wise heterogeneous in nature. Clustering problems of these kinds have two data types that need to be clustered together. In an industrial setting, despite collecting data from tens of thousands of sensors, less than 1% is actually utilized. We can move rapidly into Industry 4.0 by combining subject matter expertise, data collection methods and next-generation data science tools, beyond many of the "me too" products.
Business units need to work together, and companies need to know their consumers. By integrating data across teams, enterprises make it easier to analyze consumer information and complete marketing tasks. Big data and data-driven marketing is the new status quo. Marketers need the reports generated by big data to find new business, optimize campaigns and help companies make a profit, and each business has its own needs and its own way of making the most of big data technology. Big data technology, cross-functional integration and social media adoption are powerful and effective ways to reduce costs, discover new opportunities and launch new services and products.
Banking runs on a set of regulatory guidelines and deals with numbers, it was only about time that it would board the AI bus. Secondly, there is this deviation angle. As we fully realize the fact that anything handled by a human is prone to deviation or personal discretion; so to be vigilant, all inputs are to be taken with a generous pinch of salt. In other words, everything must undergo a reviewing pair of eyes. How about implementing a system that can auto-understand and auto-function and auto-verify without or with minimal human intervention barring some very delicate cases?
Few industries will see as big an impact from the internet of things as the insurance sector. Indeed, IoT has the potential to touch nearly every facet of insurance, with the promises of both benefits and risks for carriers as well as their customers. IoT will impact how insurance underwriting and pricing are done for markets including transportation, home, life, healthcare, workers’ compensation and commercial. And it will transform the way insurers gather information about customers and their environments to process claims, determine risks and calculate costs.
Are you taking your social media strategy as seriously as you should? Your customers are driven to your social media pages—but once they get there, they don’t find 24×7 empathy-building communication or proud, positive brand representation, and a fast, solution-focused approach. Instead they are faced with thread after thread of negative customer feedback and lacklustre product support. Simply put, you’re doing it wrong. Think smart about your social media strategy, and start with understanding the three ways today’s fashionable feedback tool can make (or break) your CX
In the near future, digital assistants will help with all kinds of mundane work tasks -- from setting up conference calls to replenishing office supplies. The majority of these digital assistants use voice recognition technology as their primary interface, which means they are always listening, even when they are not in use. With hacker activity and state-sponsored surveillance also on the rise, will digital assistants become the proverbial Trojan horse that allows attackers to sneak past our defenses unnoticed? While digital assistants are all very convenient, will using them be at the expense of our privacy and security?
While some things are easy to measure, intelligence is not one of them. Intelligence is a very abstract and complex thing to measure. How do we, people, perceive artificial intelligence and what are our expectations from it? It seems when people judge AI’s ability, we are harsh. We want AI to be perfect. We do not show the flexibility we provide to human mistakes proportionally to AIs. We want AI to be “like a human”. Whatever the reason is, it is a common pattern. We expect artificial intelligence to be comparable to human intelligence.
Blockchain technology alone cannot provide freshness, safety, provenance, and recall capabilities. That requires data and capabilities from outside the blockchain. It seems that the best emerging approach will be a hybrid consisting of 1) a centralized networked SaaS platform providing economical scalability and deep algorithmic and process capabilities, combined with 2) blockchain and smart contracts for transparency and validation. Blockchains are attractive because of their ability to create a shared, trusted single-version-of-the-truth between trading partners. However, a networked SaaS platform can provide a shared, trusted single-version-of-the-truth at a much lower cost.
If you have a single data scientist and you already think they should be delivering more to your bottom line than they are news flash: "They suck" and you hired the wrong caliber individual for the job. You may still be able to keep them if they are good, but you need to bring in a type-E rockstar to cement your data arm and redirect the unstoppable ship. A type-E individual doesn't settle anywhere. If you ask an individual where do you see yourself in 5 years and they respond "Not working here" you have found a real winner.
Industry 4.0 promises to combine digital technologies — such as big data, data analytics, artificial intelligence and machine learning — with all-pervasive internet connectivity to produce vast quantities of valuable data. Companies mine, analyze and convert the information into a wealth of insights and then use the knowledge to boost factory productivity, increase supply chain efficiency and make substantial cost savings. As always, new trends bring about new security challenges. Though connecting industrial machinery to the outside world can be risky, the deployment of virtual private networks (VPNs) can ensure that Industry 4.0’s data treasures stay hidden from unwelcome observers.
Only a fraction of the population of this planet has a skill set considered essential to business and technology today. Solving tough A.I. problems is not like building the flavor-of-the-month smartphone app. In the entire world, fewer than 10,000 people have the skills necessary to tackle serious artificial intelligence research. The path to success is to first start with a problem that would be a good candidate for machine learning, and then be prepared to experiment with training sets comprised of your own data.
The IIoT is the digitization of industrial assets and processes that connects products, machines, services, locations/sites to workers, managers, suppliers, and partners. The IIoT creates a universe of sensors that enables an accelerated deep learning of existing operations. These data tools allow for rapid contextualization, automatic pattern, and trend detection. Furthering this for manufacturing operations will finally allow for true quantitative capture of formerly “expert” qualitative operations. The question is whether or not we can leverage analysis on a continual basis to have continuous machine health monitoring and preempt catastrophic failure. This is what is known in IIoT as predictive analytics.
The key question is what is so different about the latest wave of RPA? The answer lies with the maturity of both the technology being used as well as the business processes that it is being applied to. RPA is transforming organisations across all industries, leading experts to believe that it is one of the most transformational tools in current times. In this article we explore the benefits of RPA and why it is so transformational, along with an analysis of where it can be applied within the financial services sector.
A blockchain may contain smart contracts that trigger and execute at key handoffs and decision points for each pallet or case of produce flowing throughout the end-to-end supply chain from farm to consumer. These can be used to automate key transactions and decisions. Until we see further technology breakthroughs, the cost of executing smart contracts makes them prohibitively expensive for providing 100% of the automation required in a produce supply chain. Here we discuss the division of labor between on-chain contracts and off-chain backend automation systems.
There’s no single or straightforward answer for solving the major security issues with IoT, but that doesn’t mean it’s impossible to achieve. To start, we need to focus on improving the security for IoT altogether. As for you — a business owner, executive, or IT professional working in the industry — it’s time you get serious about the problem and come up with some ways to bolster your own security before it becomes a Pandora’s box. Deploying a real-time monitoring solution to the backup of a machine learning or an AI platform is a great start.
When IoT developers consider blockchain, they should first sit back and ask themselves the basic question we ask about any new technology – “what problems will it solve for us?” If the answer is “nothing we can think of” then it is probably safe to put blockchain on the back burner, at least for now. However, blockchain could hold some potential for the IoT, particularly in relation to applications involving peer-to-peer transactions. If there are technological innovations that make blockchain more effective or increase its benefits, it might become more relevant to the IoT – but that day is not here yet.
Recording the various transactions, HACCP steps, and temperature readings onto a blockchain can add trust and additional capabilities to the system. The data about orders, prices, transactions, shipments, and so forth needs to be kept private to the parties involved. Consensus may be met with just a small number of checks being made to validate the data being written on the blockchain. Here we describe specific capabilities blockchain brings to a produce supply chain, such as tamper-resistance, automation/smart contracts, settlement, and record of soft claims, auditability, and enabling uber-like spot markets. We also touch on why a permissioned blockchain is needed.
How to use an intranet to engage employees? A corporate intranet can help win employees’ loyalty, and HR managers should always be on the lookout for ways to improve it. A finely tuned intranet can help your employees find the information they are looking for easily, follow their activities and performance, stay tuned into corporate life and keep connected to their peers, thus getting support from the professional community and feeling more satisfied with the working process. Read this article to learn how to use an intranet to engage employees.
Today, you don’t have to work in the office every single day, especially if your setup allows you to tap in remotely via an internet connection. When a team is spread out like this, it can be difficult to organize certain aspects of your business. Communication and collaboration, for instance, can be sub-par if you don’t have the appropriate tools and protocols in place. Another aspect of your managed systems and networks is cybersecurity. How, then, do you better protect your remote personnel? What are some precautionary measures and strategies you can deploy in the age of distributed teams?
The most valuable improvements for the produce supply chain come from increasing freshness and safety. Growers and retailers are always looking to reduce waste and spoilage in the supply chain and provide produce that has a longer post-purchase shelf life, with superior freshness. Improving freshness and reducing spoilage requires a number of additional data elements and capabilities, beyond those needed for traceability for provenance and recall. Companies can implement their own policies in a smart contract or off-chain. All data such as test results, events, etc. can also be stored in a blockchain if stronger proof of non-tampering is required.
Microservices have become dominant over the last few years, so much so that it is hard to imagine encountering a modern application built with a SOAP API. The wide spread usage of stateless microservices has allowed for modern applications to be easily and quickly deployed horizontally and directly on the edge. The lightweight nature of REST APIs due to their statelessness, have allowed for applications with less overhead, quicker integration times, and a much more enjoyable programming experience. Microservice adoptions at both the application and middleware layer have driven much of the advances in edge computing.