An aggregation services team at a trusted technology partner can help banks and credit unions assess their technology needs, identify appropriate products and services and connect institutions with domestic and global vendors. An aggregation team can also assist financial institutions with contract negotiation, implementation, project management and other processes, freeing up bank and credit union IT staffers to focus on more customer-oriented projects. Some decisions regarding technology solutions aren’t complicated. For example, if a financial institution needs a piece of hardware or software to fulfill a specific function, and only a handful of products will meet the company’s needs, a buying decision can be straightforward. After reviewing product features and pricing, an internal IT manager can quickly make a decision and place an order.
The standard reply from the industry is that these businesses are investing in growth and could recalibrate to make a profit if they wanted to. Instead, what they want to do is grow as big as possible first, then squeeze money out of all the customers they've captured. But critics say many of the business models are unsustainable and simply being supported by the financial teat of venture capital money. The likes of TransferWise and Revolut can only afford to offer such cheap services because of a plentiful supply of free and easy cash from investors that subsidises prices, so the argument goes, not because of any real technical innovation. Most fintech startups still run on the traditional infrastructure of mainstream banking. They may not have a big staff and branch network to maintain, but things like transfers and direct debits cost them the same as your Barclays or HSBCs.
Fragmentation is the risk of different systems and protocols developing that are not able to talk to each other. Should one system become dominant and not able to connect to other blockchains, regulators would be concerned about the potential for monopolistic behaviour that would potentially counter to the interest of the consumer, he said. Global banks are currently working with various blockchain developers, including R3 CEV, Ripple, Digital Asset Holdings and IBM's Hyperledger. "Interoperability is going to be very important in this," Mr Medcraft said from ASIC's Sydney headquarters. "You want to be able to use different suppliers: as long as they can talk to one another, that works. Fragmentation is one of our big concerns. But if you put your customers first, interoperability makes a hell of a lot of sense."
While EMET is often recommended as a defense layer for zero-day exploits -- exploits for previously unknown vulnerabilities -- it also gives companies some leeway when it comes to how fast they patch known flaws. In corporate environments, the deployment of patching does not happen automatically. Patches for the OS or stand-alone programs need to be prioritized, tested and only then pushed to computers, a process that can substantially delay their installation. With widespread exploits now able to evade EMET mitigations, the tool should no longer be relied on to protect old versions of applications like Flash Player, Adobe Reader, Silverlight or Java until a company can update them. Unfortunately, organizations are sometimes forced to keep old versions of browser plug-ins and other applications installed on endpoint computers in order to maintain compatibility with custom-made internal Web applications that haven't been rewritten in years.
Proper planning may slow things down initially, but it will save substantial amounts of time, energy, and resources, not to mention unnecessary rework later throughout the other project phases. This will also significantly increase the likelihood of meeting stakeholder expectations as well as overall project success in the end. Stakeholders are unlikely to re-hire or refer a PM who demonstrates he or she consistently fails to sufficiently plan. ... With each new project, a PM brings with them experience from all other projects that can either help or hinder the current project. It's important to recognize each new project, company, industry, product, or service, and culture can possibly negate some of those previous experiences. If a PM is unwilling to recognize that this is a possibility, they are in danger of appearing like a know-it-all, and not likely to be well received.
Tolido says it’s time for enterprise architectures to stop trying to make predictions as to what architectures should look like and instead provide the business a digital platform that will allow for a new style of architecting, one that drives continuous transformation rather than requirements-driven, step-by-step change. To do this, Tolido says Enterprise Architects must enable “the art of the possible” within organizations, providing their clients with a catalog of possibilities—a listing of potential things they could be doing to help companies continually transform themselves. This is a huge shift for most IT departments, Tolido says, which are still stuck in the mindset that the business is different from IT and that business requirements must drive IT initiatives, with architecture sitting somewhere between the two. No longer can architects be content to place architectures somewhere in the middle between the business and IT,
“This powerful IoT technology from Cisco and IBM, combined with Bell’s world leading network technology, enables customers to tap into innovative real-time analytics options to maximize performance across their operations, no matter where they are,” said Stephen Howe, Bell’s chief technology officer. “Many of our largest customers operate remote systems, requiring continuous availability and access to data to monitor critical performance factors and avoid downtime. Deploying the unmatched analytics capabilities of IBM Watson Internet of Things and Cisco networking intelligence with streaming edge analytics will help to further accelerate Bell’s leadership in Canadian IoT.” Businesses including Port of Cartagena and SilverHook Powerboats are turning to Cisco and IBM to help address their most complex IT and IoT challenges.
DDoS reflection and amplification techniques continue to be used extensively. These involve abusing misconfigured servers on the Internet that respond to spoofed requests over various UDP-based protocols. Around one-in-four of all DDoS attacks seen during the first three months of 2016 contained UDP (User Datagram Protocol) fragments. This fragmentation can indicate the use of DDoS amplification techniques, which results in large payloads. The four next most common DDoS attack vectors were all protocols that are abused for DDoS reflection: DNS (18 percent), NTP (12 percent), CHARGEN (11 percent) and SSDP (7 percent). Another worrying trend is that an increasing number of attacks now use two or more vectors at the same time. Almost 60 percent of all DDoS attacks observed during the first quarter were multivector attacks: 42 percent used two vectors and 17 percent used three or more.
Given a large enough deployment of sensors, the accuracy of the data they collect will drift over time, as the hardware degrades, he said. In harsh environments, for instance oil field sensors measuring temperature in a hot desert environment, this degradation can happen quite rapidly. These compromised sensors can't easily be replaced "because while the sensors themselves are so cheap they're almost free, the cost of the lost production incurred in replacing them most definitely is not". One way to counter the increasing unreliability of sensor data over time is to corroborate each sensor's data with that of its neighbours, said Wilcox, who suggested creating a "virtual sensor from a neural network of adjacent sensor readings".
Machine learning is proving to be effective at handling predictive tasks including defining which behaviors have the highest propensity to drive desired outcomes, which companies like Apttus use to drive business decisions like discounting or automated approvals. Enterprises eager to compete and win more customers are the applying machine learning to sales and marketing challenges first.... Machine learning's ability to scale across the broad spectrum of contract management, customer service, finance, legal, sales, quote-to-cash, quality, pricing and production challenges enterprises face is attributable to its ability to continually learn and improve. Every time a miscalculation is made, machine learning algorithms correct the error and begin another iteration of the data analysis. These calculations happen in milliseconds which makes machine learning exceptionally efficient at optimizing decisions and predicting outcomes.
Quote for the day:
"Sandwich every bit of criticism between two thick layers of praise." -- Mary Kay Ash