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Digital Transformation Calls for Wider Security Transformation!

Digital Transformation Calls for Wider Security Transformation!

Going Digital is the buzzword – conventional businesses are getting transformed, thanks to digital bandwagon! Each day, it’s developing some new ways to engage clients, associate with partners and strike better operational efficiencies. Today’s business houses are using digital power to enhance revenue and reduce cost, and we can’t agree more.

Digital business is generally the implementation of digital technologies to support business models through user behavior evolution and considerable regulation support. For an instance, let’s look at Uber:

  • New Technology – Transportation technology platform
  • Business Model – Driver-partners and riders model
  • User Behavior Norm – Acceptance of non-traditional transportation method
  • Regulation Support – Cities and countries modify regulation to strengthen models

Today, cyber security and technology risk-management are treasure keys to future business growth and prosperity – security industry has evolved a lot over the years in terms of risk mitigation measures. Digital transformation has made way for security transformation, and in this regard, below we’ve whittled down the elements used for security transformation:

Digital Technologies – Smart watches, smart cars, health bands, voice assistants and smart home devices are some of the latest digital technologies clogging the present industry. These devices are to be supported by robust application platforms using AI, Machine Learning and Big Data.

Business Models – Risk management techniques are perfect for determining information risks emanating from business processes. In digital businesses, dynamic processes are common and evolving. Traditional risk models can’t handle them.

Evolving User Behaviors – Consumers are king in the digital world. The users are empowered with tools to make their own choices. On the contrary, traditional security processes used to treat users as weak links.

Regulation Support – To manage risk, security and privacy, regulations around the globe are changing and control standards are being updated or modified. For effective adaptability with the relevant changes, compliance assurance and sustenance need to be modified.

2

A Few Fundamental Design Principles for Control Framework for Security Transformation

Business Accelerator – Only security is not just good enough for smooth digital transformation. Security has to take the role of an accelerator since the fundamental premise of going digital is to be fast in the market and enhance customer satisfaction.

Example – Biometric Authentic – it improves user speed and experience.

Technology Changes and Agile Design – The stream of technology is evolving – AI, ML, Blockchain, Virtual Reality, Internet of Things, etc. – every domain of technology is undergoing a robust transformation. Therefore, security controls have to be adaptable and agile in design.

Customer-oriented – Known to all, customers are the most important element in digital business. In the new digitized world, users are the ones who decide. Two-decade ago rule, ‘deny all, permit some’ is now changed into ‘permit all, deny some’ rule – and we are truly excited!

Automate and Digitize – It’s time security goes digital – automation is the key.

In the near future, risk management through security transformation is going to be the utmost priority for all risk managers –if you are interested in Market Risk Analytics, drop by DexLab Analytics. They are the best in town for recognized and reputable Value at Risk Model online training. For more, check out their official website.

 

The blog has been sourced from www.forbes.com/sites/forbestechcouncil/2018/09/27/the-digital-transformation-demands-large-scale-security-transformation/#64df7fc41892

 

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Risk Analytics: How to Frame Smarter Insights with Organizational Data

Companies are launching cloud-based data analytics solutions with an aim to aid banks improve and manage their risk efficiently and streamline other activities in the most cost-effective ways.

Risk Analytics: How to Frame Smarter Insights with Organizational Data

Risk analysis is a major constituent of banking circle. Analytics-intensive operations are being run in almost all banking institutions, including cyber-security, online data theft and third-party management. The concept of risk is not something new. For years, it has been the key responsibility of C-suite professionals, but the extravagant amount of awareness and recognition associated with risk analytics was missing then. Also, the regulatory and economic landscape of the world is changing and becoming more intense – hence, risks need to be managed adequately. The executive teams should make risk analytics their topmost agenda for better organization functioning.

Why risk analytics?

The first and foremost reason to incorporate risk analytics is to measure, quantify and forecast risk with amped certainty. Analytics help in developing a baseline for risk assessment in an organization by working on several dimensions of risk and pulling them in a single unified system for better results.

What are the potential benefits of risk analytics?

  • Risk analytics help in turning guesswork into meaningful insights by using a number of tools and techniques to draw perspectives, determine calculable scenarios and predict likely-to-happen events.

  • An organization stay exposed to risk. Why? Because of a pool of structured and unstructured data, including social media, blogs, websites available on both internal and external platforms. With risk analytics, you can integrate all these data into a single perspective offering actionable insights.

  • Risk is a largely encompassing concept, spilling across several domains of organizational structure that at times it can really be hard to know how to manage risk and pull out meaningful insights. In such situations, risk analytics play a pivotal role in ensuring organizations develop foresight for potential risks and provide answers to difficult questions so as to create a pathway for action.

Things to do now:

Ask the right questions

Analytics means research. It ushers you to ask questions and dig deeper into risk-related stuffs. But framing random questions don’t help. To have a real impact, conjure up a handful of questions that hits the real topic.

Understand interdependencies

Risk pierces into organizational boundaries. And analytics work by offering cross-enterprise insights, by inferring conclusions throughout the business. That makes it effective to tackle far-reaching issues.

Streamline productive programs

Analytics help decision-makers introspect and evaluate risks, as well as rewards – related to operational and strategic decisions. Adding insights into pre-determined actions to determine and curb risks yield sustainable value for the program, which in the end improves overall program performance.

Let’s Take Your Data Dreams to the Next Level

In the end, risk analytics seem to be quite a daunting subject to take up, but the truth is, some organizations are really doing well in managing their risks. If you are frustrated somehow and this whole concept of risk analytics baffles you more, take up SAS risk management certification. DexLab Analytics, a premier market risk training institute offers incredible market risk courses for data-hungry aspirants.

 

The article has been sourced from – https://www2.deloitte.com/content/dam/Deloitte/global/Documents/Deloitte-Analytics/dttl-analytics-us-da-oriskanalytics3minguide.pdf

 

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Quantum Computing Going Commercial: IBM and Google Leading the Trail

Quantum computing is all set to make a debut in the commercial world – tech bigwigs, like IBM and Google are making an attempt to commercialize quantum computing. Julian Kelly, a top notch research scientist at Google’s Quantum AI Lab announced with a joint collaboration with Bristlecone, a quantum processor that offers a testbed for various research activities on quantum technology and machine learning, quantum supremacy can be achieved and this could be a great stepping stone for building larger scale quantum computers.

QUANTUM COMPUTING GOING COMMERCIAL: IBM AND GOOGLE LEADING THE TRAIL

After Google, IBM is also making significant progress in commercializing quantum computing technology by taking it to the cloud in 2016 with a 5 qubit quantum computer. Also, last year, November they raised the bar by declaring that they are going to launch third generation quantum computer equipped with a 50 quibit prototype, but they were not sure if it will be launched on commercial platforms, as well. However, they created another 20 qubit system available on its cloud computing platform.

Reasons Behind Making Quantum Computing Commercialized:

Might lead to fourth industrial revolution

Quantum computing has seeped in to an engineering development phase from just a mere theoretical research – with significant technological power and constant R&D efforts it can develop the ability to trigger a fourth industrial revolution.

Beyond classic computing technology

Areas where conventional computers fail to work, quantum computing will instill a profound impact – such as in industrial processes where innovative steps in machine learning or novel cryptography are involved.

Higher revenue

Revenues from quantum computing are expected to increase from US$1.9 billion in 2023 to US$8.0 billion by 2027 – as forecasted by Communications Industry Researchers (CIR).

Market expansion

The scopes of quantum computing have broadened beyond expectations – it has expanded to drug discovery, health care, power and energy, financial services and aerospace industry.

From cloud to on-premise quantum technology

To incorporate quantum computing into the heart of the business operations’ computing strategy, the companies are contemplating to add a new stream of revenue by implementing quantum computing via cloud. In the future, it’s expected to see a rise in on-premise quantum computing – because the technology is already gaining a lot of accolades.

Better growth forecasts

In the current scenario, the quantum enterprise market is still at a nascent stage with a large user base in the R&D space. But by 2024, it has been forecasted that this share would be somewhere around 30% and the powerful revenue drivers will be industries, like defense, banking, aerospace, pharmaceutical and chemical.

IBM or Google? Who is a clear winner?

In the race to win quantum supremacy, IBM is a sure winner and has made stunning progress in this arena, even though it is receiving stiff competition by Google recently. Google’s new quantum processor Bristlecone has the ability to become a “compelling proof-of-principle for building larger scale quantum computers”. For this, Julian Kelly suggested, “operating a device such as Bristlecone at low system error requires harmony between a full stack of technology ranging from software and control electronics to the processor itself. Getting this right requires careful systems engineering over several iterations.”

 

As last notes, quantum computing has come out from being a fundamental scientific research to a structural engineering concept. Follow a full-stack approach, coupled with rapid testing and innovative practices and establish winning control over this future tool of success.

In this endeavor, DexLab Analytics can for sure be of help! Their business analytics certification online courses are mindblowing. They also offer machine learning using python courses and market risk training – all of them are student-friendly and prepared after thorough research and fact-finding.

 

The article has been sourced from – https://analyticsindiamag.com/why-are-big-tech-giants-like-google-ibm-rushing-to-commercialize-quantum-computing

 

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Now Navigate Through Risks with Better Data, Improved Analytics

The treasure trove of data can devise new improved ways to mitigate risks.

 
Now Navigate Through Risks with Better Data, Improved Analytics
 

How to reduce the range of risks and better grasp the reins of the business? Though data is being gathered, and pushed through the highly advanced risk analytics tools, how do the risk insurers utilize these insights to boost improved decision-making procedures that affect the business future and potential losses?

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Market Risk Analytics: How Top Notch Companies Are Assessing Intricate Risks​

Risk analytics tools boost operational efficiency. But do you know what tools to implement to derive the best results?

 
Market Risk Analytics: How Top Notch Companies Are Assessing Intricate Risks
 

With the burgeoning demand for big data all over the world, major corporate houses are taking risk analytics – the process of collecting, analyzing and measuring real-time data to forecast future risk for improved decision-making – to a new high.

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Explaining the Everlasting Bond between Data and Risk Analytics

Explaining the Everlasting Bond between Data and Risk Analytics

 

The use of data analytics is robustly expanding in the financial sector – and the risk landscape is changing pretty fast. Every day a new innovation in the field of risk analytics is making its way, and sometimes some new risks and its respective strategies are popping up just around the corner. The rise of big data, artificial intelligence and advanced analytics helps companies gain valuable cognizance from data. Computing power, the Internet of Things, drones and machine learning are some of the latest new-age tools to assist companies in taking better decisions, hence increase future profitability. Alike, risk managers implement market risk analytics and big data to manage their day-to-day work activities, while identifying, ascertaining and mitigating risks.

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Here’s All You Need to Know about DexLab Analytics’ Market Risk Modelling Live Demo Session

DexLab Analytics brings Market Risk Modelling training to India. Internet has helped people become technology-driven. Digital transformation is evident all around us. No more, gaining knowledge is a task like moving mountains – right from the confinements of your home, you can now get access to a plethora of information and knowledge, thanks to online learning. Several professionals and students are opting for e-learning method of education, owing to its flexibility and ease of access. And India is not lagging behind in this. Several online classes and sessions are being organized by premier data science learning institutes in India, and DexLab Analytics is one of them. 

 
Here’s All You Need to Know about DexLab Analytics’ Market Risk Modelling Live Demo Session
 

DexLab Analytics is here with an intensive live demo session on Market Risk Modelling Online for free. The online workshop is taking place on 25th October, 2017 from 10:00PM IST onwards, and will solely focus on how Market Risk Analytics has grown to be the new in-demand analytics course for the financial sector. Our in-house trainers will extensively explain the nitty-gritty of MRM, including its importance, major components, and why is it a must-to-have skill for the future. The interested candidates are asked to register as soon as possible by penning down a mail to DexLab Analytics, mentioning they would attend the workshop on the specified date and time.

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Market Risk Analytics: What It is All About

Market Risk Analytics: What It is All About

With time, firms need more efficient, versatile and highly functional analytics tools to address new, complex issues related to market risk. Market risk analytics involve a comprehensive set of integrated, scalable and productive solutions for wide-range risk management across various verticals of asset classes.

A New Course Alert! DexLab Analytics Launches Market Risk Analytics and Modelling – @Dexlabanalytics.

Why Risk Analytics?

Risk analytics basically help organizations realize the existence of risks lying under business activities – by facilitating enterprises to identify, determine and manage their company risk. In lieu of this, the pressing need for risk analytics is going to increase across industries in the coming few years. New developments, like real-time risk analytics, which is an advanced form of traditional risk analytics process that calculates risk on a real-time basis, are influencing the entire market, while accentuating its mitigating abilities.

DexLab Analytics Introduces Market Risk Analytics and Modelling Online Session – @Dexlabanalytics.

What the Course Offers?

Many top notch education-providing companies are now offering Market Risk Analytics and Modelling online course to better alleviate and handle risks. Increasing needs to address particular risk-induced challenges and excessive focus on the financial market sector is driving the risk analytics market in India. Hence, learning and honing your skills on market risk is indispensable – DexLab Analytics brings Predictive modelling of market risk using SAS to India. The course module will address key issues, like the different types of risks faced by banks, the 1990’s financial crisis, sources and scope of market risk, theoretical probability distributions, volatility forecasting and clustering models, value at Risk Modelling, quantitative models of market risk and description of key financial products.

Some of the most common types of risks that banks are exposed to are Credit risk, Market risk, Operational risk, Liquidity risk, Business risk, Reputational risk, Systemic risk and Moral hazard. All banks need to establish separate risk management departments to manage, monitor and mitigate such high-flying risks. The concept of probability distributions sheds light on investing options – stock returns are expected to be distributed normally, but the reality may vary. They are mostly used in risk management to determine the probability of an event as well as the proportion of losses that it would strike based on a distribution of historical returns. Clustering models is another branch of risk analytics that helps in identifying groups of similar records and marking the records in accordance to the group in which it belongs. These models are also known as unsupervised learning models. Apart from this, other valuable concepts will be addressed during the online live sessions.

Closing Thoughts

Emergence of real time risk analytics is boosting the market of risk analytics. Technology being the driving factor for real-time analysis trades data to the organizations to balance market volatility. Leading service providers are on their quest to design and develop dynamically configurable risk analytics frameworks for clients. And why not, risk analytics boasts of widespread applications, starting from fraud detection to liquidity risk analysis, credit risk management and product portfolio management – various industries are nowadays looking up to market risk analytics, including banking, financial services, government, healthcare, insurance, manufacturing, transportation and logistics, consumer goods and retail, energy and utilities, telecommunication and information technology (IT), media and entertainment, and many others.

Reach us at DexLab Analytics for over-the-top SAS risk management certification course. Their courses are truly remarkable and perfect to take a step into the world of analytics.

 

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A New Course Alert! DexLab Analytics Launches Market Risk Analytics and Modelling

We are back again with some great news! Technology enthusiasts and hardcore industry professionals got another reason to cheer for DexLab Analytics, as we feel extremely delighted to announce our new Market Risk Analytics and Modelling online live sessions. We welcome hundreds and thousands of young, aspiring data enthusiasts from various parts of the country who are driven by hunger, passion and robust dreams of a data-friendly future to get enrolled in our online course on Market Risk Analytics using SAS. In our quest for expanding our horizons, these types of analytics course play a significant role.

 
A New Course Alert! DexLab Analytics Launches Market Risk Analytics and Modelling
 

Recently, Market Risk Analytics have gained a lot of prominence – a lot of tech pundits and industry practitioners have repeatedly emphasized on the importance of having sound market risk management policies and strong internal controls. Especially, since the global financial crisis, the critical aspect of risk management analytic has doubled.

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