What are IT pros concerned about in the new normal? Security and flexibility
What's also interesting is, despite this workload increase, the majority (77%)
feel they have been very effective at supporting employees working from home.
This is great to hear, and not entirely surprising, as these companies rely on
SaaS to run their businesses. On the flip side, laggards running legacy
infrastructures have seen productivity go to zero. This is definitely a
tipping point for the adoption of SaaS. Our survey also reinforces this
sentiment, as 47 percent of respondents said they will increase the use of
SaaS as a result of the pandemic. ... IT teams at every company we work with
have had to implement new processes to support the entire employee base,
leveraging and adjusting methods, tools and processes to enable business
continuity with nearly 100% work-from-home workforce. Work from home is not a
new concept, but supporting traditional remote laptop users is not the same
challenge as supporting desktop users that may not be using corporate-issued
devices and computers. Companies were forced to immediately implement new
processes for the entire employee base, leveraging methods that were effective
for laptop users who were already effective remote users.
Singapore banks set to fast-track digital transformation due to COVID-19
As banks re-evaluate their digital strategies, it only makes sense to ensure
compliance is automated in order to easily and efficiently adhere to all AML,
KYC and CTF regulations. Regulation technologies, which use Artificial
Intelligence (AI), are particularly valuable when it comes to automating
compliance. AI can help mine huge volumes of data, automatically flagging
risk-relevant facts faster than humanly possible. AI technology dramatically
speeds up the onboarding phase. The technology helps to automatically identify
illicit client relationships and alert financial institutions to the
possibility of criminal or terrorist activity. With regulatory requirements
being constantly updated, it can be difficult for banks to keep on top of
these changes via manual processes alone. By implementing AI technology,
financial institutions are better able to identify gaps in customer
information, with the technology automatically prompting them to perform
regulatory outreach to collect the outstanding information – a far more
streamlined and hands-off approach to what many banks in Singapore are
currently using.
Top ten myths of technology modernization in insurance
Modernization simply means replacing the core platform with the best-in-class
option. The reality: Core-platform replacements often have higher up-front
investment costs than in-place IT modernization, as they require both software
and hardware, experts’ time, and extensive testing. Furthermore, migrating
existing policies and their implicit contracts to a new platform is often
expensive—these additional costs need to be factored into any decision—and
time consuming. One big reason for high modernization costs is the age and
quality of the policy data and rules—poorly maintained policies are expensive
to refresh and modernize to work in a new system. Product types and geographic
context are also considerations. For instance, US personal property and
casualty (P&C) policies are generally issued annually and thus have
up-to-date policy data and rules; this makes migration efforts more
straightforward. By contrast, in countries such as Austria or Germany,
policies are refreshed annually to adjust premiums for inflation, but policy
data, rules, and terms only change when a customer switches to a new
policy—which may not happen for many years. Therefore, policy rules need to be
carried over to the target system or customers need to switch to a new policy
during modernization, rendering it time consuming.
Microsoft Defender ATP now rates your security configurations
Microsoft promises the data in the score card is the product of "meticulous
and ongoing vulnerability discovery", which involves, for example, comparing
collected configurations with collected benchmarks, and collecting
best-practice benchmarks from vendors, security feeds, and internal research
teams. Defender ATP users will see a list of recommendations based on
what the scan finds. It contains the issue, such as whether a built-in
administrator account has been disabled, the version of Windows 10 or Windows
Server scanned, and a description of the potential risks. For this
particular risk, Microsoft explains that the built-in administrator account is
a favorite target for password-guessing, brute-force attacks and other
techniques, generally after a security breach has already occurred. Defender
ATP also provides the number of accounts exposed on the network and an impact
score. Users can export a checklist of remediations to be undertaken in
CSV format for sharing with team members and to ensure the measures are
undertaken at the appropriate time. An organization's security score should
improve once remediations are completed.
Working with Complex Data Models
Physical data models present an image of a data design that has been
implemented, or is going to be implemented, in a database management system.
It is a database-specific model representing relational data objects (columns,
tables, primary and foreign keys), as well as their relationships. Also,
physical data models can generate DDL (or data definition language)
statements, which are then sent to the database server. Implementing a
physical data model requires a good understanding of the characteristics and
performance parameters of the database system. For example, when working with
a relational database, it is necessary to understand how the columns, tables,
and relationships between the columns and tables are organized. Regardless of
the type of database (columnar, multidimensional, or some other type of
database), understanding the specifics of the DBMS is crucial to integrating
the model. According to Pascal Desmarets, Founder and CEO of Hackolade:
“Historically, physical Data Modeling has been generally focused on the design
of single relational databases, with DDL statements as the expected artifact.
Those statements tended to be fairly generic, with fairly minor differences in
functionality and SQL dialects between the different vendors. ...”
'Machine' examines Artificial Intelligence and asks, 'Are we screwed?'
These AI systems are trained on huge amounts of data and you'll find bias
when, say there's facial recognition. If all your facial recognition data set
is Caucasians, it's going to have trouble identifying people by their races.
And being misidentified by facial recognition is not a good thing when it
comes to law enforcement, other things like this. So, we're finding, even
through the course of making the film, this technology moves so fast, but
we've seen a lot being done to address the problem of bias in data sets since
we started. And they're finding that more diversity within these data sets
actually has helped reduce bias in a lot of these algorithms, which is a
positive sign. But at the end of the day, I think we're still at the point
where we don't want to give these algorithms too much control. I think there
needs to be humans in the loop that understand ethics and not everything in
life boils down to zeros and ones, and Xs and Os. So, I think it's good to
have humans in the loop and also society in the loop, not just the people
designing these technologies, but society as a whole should be hip to what's
going on. Because if not, you're going to wake up in 20 years and going to be
living in a very different world, I think.
Pandemic reveals opportunities for 5G connectivity
Because 5G technology can now be cloud orchestrated—that is, use
software-defined principles to manage the interconnections and interactions
among workloads on public and private cloud infrastructure—the behavior of the
5G network can be changed to accommodate specific applications for specific
uses. Roese shared a dramatic example of this by describing a telehealth
scenario in which suspected stroke victims could be diagnosed and receive
initial treatment while en route to the hospital. This would be accomplished
by using the continuous collection and streaming of patient data. “In order to
do that, a whole bunch of conditions had to be true,” said Roese. “You had to
push the code out to an edge, so it can operate in real time. You had to
execute a network slice to guarantee the bandwidth and give this a priority
service.” If such allocation were done manually, it might take three hours or
more to reconfigure the network. One thing that makes mobile triage possible
is strength at the edge of the cellular network. That is also crucial for
innovation—as well as for the average 5G user. “What that means is you’re
walking around in a city and if you constantly get 100-to-200 megabits per
second, the peak rates might be five-to-10 gigabits per second,”
Design Patterns — Zero to Hero — Factory Pattern
Before moving into the explanation part we need to have a clear understanding
of concrete class. A class that has an implementation for all of its methods
is called Concrete class. They cannot have any unimplemented methods. The
concrete class can extend the Abstract class or an interface as long as its
implements all the methods of those too. Simply, we can say that all classes
which are not Abstract class are considered as Concrete classes. Actually,
according to Head First Design Patterns, Simple Factory is not considered as a
Design Pattern. Let’s get started understanding the Factory Pattern varieties.
The Simple Factory Pattern describes a way of instantiating class using a
method with a large conditional that based on method parameters to choose
which product class to instantiate and then return. Let’s dive into the coding
example where the Simple Factory Pattern comes into play. Imagine a scenario,
where we have different brands of smartphones. You need to take the
specification details of the respective brands where the brand name is passed
as a parameter through the client code.
Evolution of Voice-activated Banking
Instead of having to call up customer care representatives and waiting to
get their queries resolved, consumers should be able to quickly get relevant
information simply by asking. The financial services industry is addressing
the one-click, on-the-go behaviour of consumers by launching various
innovative solutions, such as mobile wallets, which have become a highly
convenient method of payment; and chatbots, which have become very popular.
Banks are constantly looking to enhance customer experience by providing
ways to customers to get the desired information as and when they want. The
opportunity lies in integrating all branch transactional activities with
voice technology. Currently, voice assistants handle basic customer queries,
such as checking account balances, making payments, paying bills and getting
account-related information. The simple nature of these requests enables
institutions to instantly provide the right information at the right time;
however, this is unlikely to provide a competitive advantage in future.
Companies that reimagine the customer journey across channels, products, and
services with end-to-end integration, will emerge as winners.
Fintech In Banking: New Standards For The Financial Sector
Distributed leader technologies, widely known as blockchains, have already
moved from the shade of public interest and now are treated as
paradigm-changing technologies that turn the interaction between Fintech and
banks upside down. The research held by Accenture shows that 9 in 10
executives are considering the implementation of blockchain technology into
their financial services. Blockchain aims at boosting mutual benefits and
reducing business risks from collaboration and mutual Fintech investment
banking. Using a decentralized database, banks receive an opportunity to
work together on a common solution, keeping their own data security and
opening certain pieces of data only when they want to interact and trade. It
ensures complete transparency and real-time execution of payments what
significantly minimizes the possibility of cyber-attacks as the information
doesn’t exist in a centralized database anymore. Blockchain technology is
also very helpful in KYC (Know Your Customer) Compliance. In traditional
banking, it usually causes delays to banking transactions, entails
substantial duplication of effort between banks and third parties, and ends
up at high costs.
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