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How Predictive Analytics is Changing Risk Management

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How Predictive Analytics is Changing Risk Management


Predictive analytics can determine future performance based on current and historical data.

Every task involves some amount of risk, and companies focus on managing these risks in a way so that they can avoid these threats and minimize the lossesthat ensue. Businesses are transforming risk management to avoid these losses.

What is Predictive Analytics?

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Predictive analytics is the use of data, statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. The goal is to go beyond knowing what has happened to providing a best assessment of what will happen in the future.

Transforming Risk Management with Predictive Analytics

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Big data technologies has achieved unprecedented power and focuses on handing over information to organizations and assists them in the maintaining company’s growth. As big data provides intuitive insights to an organization, decision making becomes easy, and organizations can progress in the right direction.  Risks associated with an organization’s workflow are innumerable and inevitable at times. These risks are manageable if businesses have prior information about the likelihood of a disaster. The information helps companies in decision making. Predictive analytics is a process that aids an organization in deciding on adequate precautionary actions to prevent or minimize the losses incurred. Predictive analysis is transforming risk management as it helps organizations by informing what is arriving in the future. 

Mapping Changes in Any Industry

Predictive analytics is the process of analyzing current and historical facts that lead on to make predictions for the future. With predictive analytics, working with machine learning and data mining is crucial as both of them hold importance in improving the quality of predictions. Predictive analytics holds significance in business because of their primary goal to provide organizations with the best assessment and estimation of what would happen, based on a machine’s understanding of what has happened in the past.

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Predictive analytics is a powerful resource because of its ability to provide organizations with actionable insights that can help tin ascertaining what would happen under given circumstances. One of the few reasons that predictive analytics is resourceful is because of its ability to assist an organization to detect fraud, while the other reasons are that predictive analytics’ presence helps companies in optimizing marketing campaigns and improving operations by providing them actionable information.

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Analyzing Behavioral Patterns

Using predictive analytics has become a norm for companies across the globe. As every organization focuses on reducing risks associated with its workforce, predictive analysis comes into action and proves to be a solution for this requirement.

One of the reasons why predictive analytics has gained popularity is because of its ability to scan through thousands of data sets and past trends and its ability to identify and detect vulnerabilities. Predictive analytics holds power to map changes that brought transformations in the industry. When the head of a company contains such immense power, he is liable to take the correct decision when the company is in the midst of a risky situation. Predictive analytics in risk management helps organizations in minimizing risks that can damage brand value or result in losses.

As predictive analytics helps the company in finding a solution to a problem created by an employee, authorities can be notified about the same and can be assisted to come to a conclusion related to the problem. When a company faces an issue, managers often focus on the cause of the problem or mishap; when they have predictive analytics, managers can be informed about the reason behind the catastrophe and can be assisted in applying preventive measures so that something similar to the accident would not occur again.

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Apart from providing information and increasing sales in an organization, predictive analytics proves to be useful for humanitarian purposes. When agencies provide such crucial information, security authorities are better armed with data from the past. This information can help governments in deciding how structures are to be built to protect the population.

Organizations are adding analytics to their arsenal to empower themselves against imminent threats by learning from mistakes made in the past. Predictive analytics can prove to work wonders if applied appropriately. Apart from telling the organization how to reach somewhere, predictive analytics holds the ability to provide us with the best way to reach there.



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Artificial Intelligence in the 4th Industrial Revolution

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Artificial Intelligence in the 4th Industrial Revolution


Artificial intelligence is providing disruptive changes in the 4th industrial revolution (Industry 4.0) by increasing interconnectivity and smart automation.

Industry 4.0 is revolutionizing the way companies manufacture, improve and distribute their products. 

What Makes Artificial Intelligence Unique?

Artificial intelligence (AI) makes it possible for machines to learn from experience, adjust to new inputs and perform human-like tasks.

It allows computers to think and behave like humans, but at much faster speeds and with much more processing power than the human brain can produce.

AI offers advantages of new and innovative services, and the potential to improve scale, speed and accuracy. 

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There are 3 types of artificial intelligence:

  • Artificial narrow intelligence (ANI), which has a narrow range of abilities.

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  • Artificial general intelligence (AGI), which is on par with human capabilities.

  • Artificial superintelligence (ASI), which is more capable than a human.

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Artificial intelligence can also be classified as weak or strong. 

Weak AI refers to systems that are programmed to accomplish a wide range of problems but operate within a predetermined or pre-defined range of functions. Strong AI, on the other hand, refers to machines that exhibit human intelligence.

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Artificial intelligence has several subsets:

Most AI examples that you hear about today – from chess-playing computers to self-driving cars – rely heavily on deep learning and natural language processing.

What is the Fourth Industrial Revolution?

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The Fourth Industrial Revolution is the current and developing environment in which disruptive technologies and trends such as the Internet of Things (IoT), robotics, virtual reality (VR) and artificial intelligence (AI) are changing the way modern people live and work. The integration of these technologies into manufacturing practices is known as Industry 4.0. 

The first industrial revolution used water and steam power to mechanize production.

The second used electric power to create mass production.

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The third used electronics and information technology to automate production.

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The fourth Industrial revolution is characterized by a fusion of technologies that is blurring the lines between the physical, digital, and biological spheres, with rising emerging technologies, as real AI, Narrow AI/ML/DL, robotics, automation, materials science, energy storage, the Internet of Things, autonomous vehicles, 3-D printing, nanotechnology, biotechnology, neurotechnology, cognitive technology, and quantum computing. It implies radical disruptions to everything, industries, jobs, works, technologies, and old human conditions. In its scale, scope, complexity, and impact, the AI transformation will be unlike anything humankind has experienced before.

The Role of Artificial Intelligence in the 4th Industrial Revolution

Artificial intelligence is making companies make the best use of practical experience, even displacing traditional labor and becoming the productive factor itself. 

It offers entirely new paths towards growth for manufacturing, service, and other industries, reshaping the world economy and bringing new opportunities for our societal development.

As AI begins to impact the workforce and automation replaces some existing skills, we’re seeing an increased need for emotional intelligence, creativity, and critical thinking.

Zvika Krieger, co-leader of the World Economic Forum’s Center for the Fourth Industrial Revolution.

Deploying AI requires a kind of reboot in the way companies think about privacy and security, As data becomes the currency of our digital lives, companies must ensure the privacy and security of customer information.

Businesses will need to ensure they have the right mix of skills in their workforce to keep pace with changing technology. 

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