The treasure trove of data can devise new improved ways to mitigate risks.
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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Global risks are burgeoning; companies of all sizes are seeking the perks of risk analytics and management. Smart companies are realizing the change is coming from people as well as recent technological breakthroughs, including Big Data and AI. And CEOs are improvising their risk teams, and transforming them into perceptive strategic advisors to address budding dangerous threats like cybercrime.
Modern risk analysts have accurate knowledge about risk, artificial intelligence and cyber security – so, it’s time they get an opportunity to show a greater presence in the stoic boardrooms as strategic advisors. AI, the cutting-edge risk analytics tool surfaced out to enhance the inexorable march of big data. As such, their importance in the organization in assessing risk has greatly increased.
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Last year, Britain opted to leave the European Union – and that created spiking fluctuation and acute market uncertainty across the globe.
Most of the investors out there know investment involves risks and rewards, just like head and tail in a coin and so do the analysts. Higher the risk, better are the chances to gain potential rewards. As a result, it is critical for both an investor and analyst to understand the true nature of market risks that influences the market conditions and controls the shooting volatility and the ways to manage those risks.
Relevant market risks depend largely on the nature of investment as well as geographic boundaries. Some of the key market risks are as follows:
Well, you can’t control the market risks from taking a front seat in your financial life, though you can take some steps to manage and mitigate them.
As globalization seeped through all leading economies and market segments, a majority of fintech institutions started realizing the criticality of an enhanced operational risk, especially related to cyber-security, IT failures and data theft. Amid this, cyber risks and data theft issues posed key challenges, followed by IT failures and outsourcing issues. The revolution of digitization did many goods to our society, but the moment banks got dependent on single computer networking setups, the vulnerability of confidential customer data leakage multiplied. As a result, the need for data analysts and market researchers spiked up – they are the trained souls who possess both the experience and expertise to tackle diverse investment portfolios for clients in the best way possible to fetch maximum profits.
For that, affluent market risk courses in Delhi are available around – train your mind well, before taking the big leap in the big field of data analytics. Once you are done, reach DexLab Analytics – their comprehensive Market Risk Modelling using SAS courses are top-of-the-line courses in the industry at present.
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Want to get to the core of understanding risk within various business frameworks? The answer is Risk Analytics. This new breed of data analytics facilitates organizations in precisely defining, recognizing and managing their risk, and its need is going to increase in the coming few years. New developments in risk analytics are gaining limelight and bringing a notable transformation in the market, while enhancing its overall capability.
Recently, a team of analysts had eureka moment – they introduced a new concept of real-time risk analytics – it is nothing but a modern, more advanced version of traditional risk analytics methods. Here, the prediction is based on real-time data – it processes, examines and determines risk all on a real-time basis – hence top notch financial institutions are putting real-time risk analytics to best use to manage and mitigate associated risks. Several asset management, portfolio management and hedge fund firms, and investment banks are relying on this mode of risk analytics to modify their operating principles to play in accordance with investment and market shifts.
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Risk analytics tools boost operational efficiency. But do you know what tools to implement to derive the best results?
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.
Continue reading “Market Risk Analytics: How Top Notch Companies Are Assessing Intricate Risks”
Many factors are constantly shaping and reshaping the structure of risk management today – including global geopolitical inconsistency, macroeconomic headwinds and increasing number of cyber activities – which is extensively damaging and recurring. All this is leading to elevated risk perceptions.
The nature of risks has changed over the years too, as well as the manner of addressing them. Today, to mitigate risk issues, technology plays a crucial role. Headwinds like global and Asian accelerating debt levels, lower projection of productivity growth, increasing levels of policy uncertainty and constant increase of US interest have created a lot of prominent macroeconomic challenges, especially in export-oriented Asian economies. Topping that, budding risks from technological advancements are on the rise, exposing industries to newer challenges like cybersecurity and data fraud.
As a result, the regulatory scenario of the world is also changing, especially after the global financial crisis. With a wide array of regulations introduced, the issue of risk management has started getting the desired prominence. These increasing regulations have compelled banks to accelerate their compliance activities, while giving increasing pressure on risk-management policymaking. The risk management teams now need to be constantly on a lookout for newer uncertainties – the key to address this concern remains productivity gains, but for that technology needs to be employed to the vast extent.
Advanced data analytics, contemporary data and NLP coupled with process digitization offers new robust opportunities for effective market risk management. The technological opportunities can be realized throughout various key functions and levels, but it is the duty of the risk professionals to chalk out a more affordable and fruitful approach to address risk-related issues.
Data – Data is the new powerful combat weapon. Financial institutions consist of huge piles of data, where internal and external sources of data continuously pour in at an accelerating rate. Data, in every form – including transaction, social media, and other sources helps discover real-time customer insights and generate dividends thereafter.
Analytics – Nowadays, machine learning, NLP, advanced analytics and self-learning algorithms are widely available and at achievable prices. The best example to show how advanced analytics is boosting risk management is improving debt collection.
As per conventional debt repayment collection procedure, a lot many calls were asked to make, out of which very few turned out to be successful. But now, with advanced analytics, a set of high-end predictive models are developed to fire up decision-making process. After this, an improved insight about customers can be curated, which can further be developed with better prediction quality.
Processes – With digitization, one gets the opportunity to automate and design risk-monitoring processes to mitigate emerging risks. Nowadays, several financial institutions are implementing machine learning and transaction data to automate monitoring of conduct risk.
Subject to the extent of digitization, the change in factors for risk organization is proposed – in the beginning of digitization, one expects 15-20 percent efficiency gains, while a 60-70% improvement is to be expected in case of a fully digitized risk function, which is quite a show!
Do you want to know more about market risk modelling techniques? Drop by DexLab Analytics; being a one-stop-destination for Market Risk Modelling using SAS, it boasts of superior training and well-researched study materials.
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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.
Continue reading “Explaining the Everlasting Bond between Data and Risk Analytics”
Cybersecurity attacks are the new potent threat to businesses. Diligent professionals and big mouth board members have started reviewing their company’s cybersecurity frameworks, while establishing better security controls and discerning deeper insights about the business impact of cybersecurity attacks: what kind of risks are they exposed to? Are they expending too much and need to curtail down? What amount of risk can be reduced using the proposed info security budget? Cyber-insurance, will it fetch better results?
This is the epic question that has triggered the development of Value-at-risk models, especially in the domain of information security. Also known as Cyber VaR, these models are a game-changer. They offer a sound base for quantification of information risk coupled with infusing discipline into the whole process.
Enterprises powered by VaR models for cybersecurity make complicated decision-making as easy as pie. They trigger risk-related discussions, where risks become more consistent, and business-goal driven.
In the world of finance, value-at-risk modeling is the statistical methodology to appraise the level of financial risk that a firm is exposed to over a specific period of time.
The VaR is ascertained using these three variables:
Probabilities are effective to evaluate likely losses from the cyber attacks during a specific time period. Top notch global organizations, like World Economic Forum and several regulatory bodies, like The Open Group are revolutionizing the concept of cyber VaR models.
VaR was initially developed in 1990’s to boost the investment banking sector, wherein managers were to identify the risks that popped up daily in multiple market reports. From the name itself, you can understand, it is more likely a measurement tool to analyze the financial impact of risky events within a particular time frame.
The most beneficial effect of VaR is that it not only quantifies risk but also pens it down in economic terms that are easily understood by all. It also assists in mitigating long-term challenges by aggregating cyberrisk with various other operational risks within an enterprise risk management system.
CISOs, Chief information security officers decipher what exactly VaR offers in terms of cyberrisk management. This hi-tech concept is too good to help with crucial decision-making, like addressing cyberrisk appetite and defining the optimal allocation of cyber risk management resources.
Market risk analytics is a new concept in the make. Many organizations have realized its crucial importance, while many are yet to decipher. For the best enterprise risk management certification, drop by DexLab Analytics. They are a leading economic capital model training institute offering state-of-the-art courses to the candidates.
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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.
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.