Machine learning has moved from the stuff of science fiction to a staple of modern business, as organizations across nearly every industry vertical implement ML technologies. Doctors are using machine learning to more accurately diagnosis and treat their patients, retailers are using ML to get the right merchandise to the right stores at the right time, and researchers are utilizing the technology to develop effective new medicines. That is just a sliver of the use cases emerging, as all sectors -- from energy and utilities, to travel and hospitality, to manufacturing to logistics -- and the various functions within any given organization increasingly put machine learning to work. Machine learning is a subset of artificial intelligence, where computers use algorithms to learn from data, allowing the machines to identify patterns -- a capability that organizations can put to use in multiple ways. Experts said machine learning enables organizations to perform tasks on a scale and scope previously impossible to achieve.
The digital sphere is raining technologies. The influence of artificial intelligence is taking center stage with every possible improvement. Technology is changing almost all industries including banking and finance, healthcare, automobile, telecommunication, manufacturing, defense and military, entertainment and media, education, etc. The sub-domains of Artificial Intelligence such as machine learning, natural language processing, data analytics, and image analytics are also rolling out profitable use cases in diverse sectors. Besides, artificial intelligence is serving the business purpose by leveraging end-to-end automation processes. Therefore, Analytics Insight has listed the top 50 business use cases of artificial intelligence in diverse sectors. Predictive analytics is a gift to healthcare. Sometimes, we come across patients who say they underwent an unnecessary surgery due to a lack of predictions on what was coming. Fortunately, artificial intelligence is changing the fate of such burdensome risks and avoidable surgeries.
From screening and approving loans to managing assets and preventing fraud, machine learning plays a crucial role on many levels in financial institutions. In this blog post, we'll explore some ways that machine learning improves business processes in the financial sector. Machine learning algorithms are far more effective for personalizing your customer experience than entire teams of employees. Simple demographics can't fully explain actual consumer behavior, so financial organizations should use machine learning to segment consumers by their level of sophistication and financial acumen, and then customize products and services accordingly. All relevant customer interaction data is used to train these algorithms, which then automatically builds statistical models that help correlate customers' preferences with their demographic, behavioral, and other characteristics.
There's no doubt that the finance industry is undergoing a transformational change. The recent years have seen a rapid acceleration in the pace of disruptive technologies such as AI and Machine Learning in Finance due to improved software and hardware. The finance sector, specifically, has seen a steep rise in the use cases of machine learning applications to advance better outcomes for both consumers and businesses. Until recently, only the hedge funds were the primary users of AI and ML in Finance, but the last few years have seen the applications of ML spreading to various other areas, including banks, fintech, regulators, and insurance firms, to name a few. Right from speeding up the underwriting process, portfolio composition and optimization, model validation, Robo-advising, market impact analysis, to offering alternative credit reporting methods, the different use cases of AI and Machine Learning In Finance are having a significant impact on this sector.
Artificial Intelligence (AI) has become the semiconductor equivalent of software -- pervasive, intangible, and capable of transforming the fiber of society and business. It is integrated into a growing number of applications and systems today in a manner that is both seamless and transformational. From Amazon's Alexa to self-driving vehicles, the development of AI has been revolutionary to the point that it seems to mimic human features, intelligence, and behavior. Although experts and scientists have warned against the dangers and hazards associated with highly mature AI machines, the market is expected to expand rapidly. According to Forbes, AI is a strategic priority of 83% of businesses today and is expected to drive global sales from nearly $8 billion in 2016 to more than $47 billion by 2020.