banking & finance


How Artificial Intelligence benefits companies and ups their game

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Royal Bank of Scotland (RBS) launched Luvo, a natural language processing AI bot which answers RBS, Natwest and Ulster bank customer queries and perform simple banking tasks like money transfers. Compared to the progress of natural language processing solutions, computer vision-based AI solutions are still in developmental stage, primarily due to the lack of large, structured data sets and the significant amount of computational power required to train the algorithms. Other than online and IT companies, which are early adopters and proponents of various AI technologies, banks, financial services and healthcare are the leading non-core technology verticals that are adopting AI. AI, thus, can go beyond changing business processes to changing entire business models with winner-takes-all dynamics.


Roomba vacuum maker iRobot betting big on the 'smart' home

Daily Mail

All robovacs use short-range infrared or laser sensors to detect and avoid obstacles, but iRobot added a camera, new sensors and software to Roombas in 2015 to give them the ability to map while they clean. So far investors have cheered Angle's plans, sending iRobot stock soaring to $102 in mid-June from $35 a year ago, giving it a market value of nearly $2.5 billion on 2016 revenue of $660 million. So far investors have cheered Angle's plans, sending iRobot stock soaring to $102 in mid-June from $35 a year ago, giving it a market value of nearly $2.5 billion on 2016 revenue of $660 million But there are headwinds for iRobot's approach, ranging from privacy concerns to a rising group of mostly cheaper competitors - such as the $300 Bissell SmartClean and the $270 Hoover Quest 600 - which are threatening to turn a once-futuristic product into a commoditized home appliance. All robovacs use short-range infrared or laser sensors to detect and avoid obstacles, but iRobot in 2015 added a camera, new sensors and software to its flagship 900-series Roomba that gave it the ability to build a map while keeping track of their own location within it.


AI May Soon Replace Even the Most Elite Consultants

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While the financial services industry has already begun the shift from active management to passive management, artificial intelligence will move the market even further, to management by smart machines, as in the case of Blackrock, which is rolling computer-driven algorithms and models into more traditional actively-managed funds. It will be particularly interesting to see how artificial intelligence affects the decisions of corporate leaders -- men and women who make the many decisions that affect our everyday lives as customers, employees, partners, and investors. But AI can also help support more complex decisions in key areas such as human resources, budgeting, marketing, capital allocation and even corporate strategy -- long the bastion of bespoke consulting firms such as McKinsey, Bain, and BCG, and the major marketing agencies. They used this new skill to make resource allocation decisions to different marketing choices, thereby "eliminating guesswork."


The Game-Changing Technology Every Company Needs to Prepare for Now

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You own a small insurance company that sells accident protection and marine policies. Your business is growing quickly but faces one key challenge: There's no electric light. You own a small insurance company, your business is growing quickly, and you have a chance to take advantage of the biggest transformative technology since electricity: artificial intelligence. Fanuc is working on an unsupervised learning system, so A.I.-powered robots can learn skills on their own.


R Clustering – A Tutorial for Cluster Analysis with R

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We calculate Between-Cluster Sum of Squares by finding the square of difference from the center of gravity for each cluster and then adding them. We calculate Within-Cluster Sum of Squares by finding the square of difference from the center of gravity for each cluster and then adding them within in a single cluster. In R, you can easily generate different numbers of clusters for the same data by assigning different values to the centers attribute in the kmeans() command. Here you will use summary statistics for each state, such as average and standard deviation of employment rates and then use these 2 calculated features of monthly unemployment rates as attributes of clustering.


Jobs come, jobs go as digital era transforms workplaces

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Ant Financial Services Group, a subsidiary of e-commerce giant Alibaba, last month introduced an automated system to assess car damage by scanning accident-scene images and calculating payouts on insurance claims. If there it's consolation to human, most pilot projects to date are tapping the capability of machines largely for assistant roles involving repetitive, high-volume and rule-bound tasks. Andy Gillard, Asia Pacific digital operation leader at EY, one of the world's "big four" accounting firms, has looked at the wide-ranging applications of Robotic Process Automation across the securities, banking and insurance sectors. Ant Financial's car damage assessment system builds upon the second level of artificial intelligence called "machine learning."


A Digital Dawn for the Insurance Industry

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Far too often when a broker is sitting opposite a client or has them on the other end of the phone they are unable to draw up a single customer view that shows all the policies that the client has taken out such as for example home insurance, car insurance, business liability insurance, making it impossible for to offer timely and relevant offers. It is, however, possible for experienced system integrators to collect data from these different systems and form a single repository for a complete and organic single customer view. Add to this the contribution of Artificial Intelligence and companies will be enabled to further improve strategy and decision making across the business in an over-arching Business Intelligence framework. It is therefore highly cost effective to engage with a third-party consultant to help provide a roadmap of the process of improving user experience via greater digitalisation and to help implement or entirely outsource the process.


How firms are using artificial intelligence to up their game

#artificialintelligence

Royal Bank of Scotland (RBS) launched Luvo, a natural language processing AI bot which answers RBS, Natwest and Ulster bank customer queries and perform simple banking tasks like money transfers. Compared to the progress of natural language processing solutions, computer vision-based AI solutions are still in developmental stage, primarily due to the lack of large, structured data sets and the significant amount of computational power required to train the algorithms. Other than online and IT companies, which are early adopters and proponents of various AI technologies, banks, financial services and healthcare are the leading non-core technology verticals that are adopting AI. AI, thus, can go beyond changing business processes to changing entire business models with winner-takes-all dynamics.


How the rise of artificial intelligence will affect the FS industry

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Machine learning isn't a brand new concept and when we look specifically at the financial services (FS) sector, its noticeable that it has always been one of the lead drivers of new technology trends with data analytics, mobile banking and new payment methods. Banks and financial service providers have undergone sweeping change over the last decade with numerous challenges around regulation, customer experience, start-ups and market volatility. Larger volumes of data and information allows financial services firms to create more accurate models to generate a better fit for different FS products. Whether its supporting customer experience or automating regulatory compliance, FS organisations need to embrace developments in the AI space and plan for how they can support and improve their business in the future.


Automation Will Lead to Collaboration Between Man and Machine

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Instead, we should focus on the challenges and opportunities presented by new technology trends, including artificial intelligence, machine learning, and Big Data analytics. He added: "The development of automation enabled by technologies, including robotics and artificial intelligence, brings the promise of higher productivity (and with productivity, economic growth), increased efficiencies, safety, and convenience, but these technologies also raise difficult questions about the broader impact of automation on jobs, skills, wages, and the nature of work itself." It's tempting to view machine learning's evolution as a slam dunk for the robots As machine learning-based skills approach those of human beings, it's tempting to view their evolution as a slam dunk for the robots. And over time machine learning and other advanced technologies will create new growth opportunities and jobs for workers with updated skills.