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< back AI Case Study Yahoo! researchers investigate optimising click-through rates by predicting optimal news story to feature online Yahoo! researchers create and trial a method of trialling main page news stories to optimise clickthrough rate without having to implement them online first, a disruptive and more costly option. Industry Consumer Goods And Services Media And Publishing Project Overview "To draw visitors’ attention, Yahoo! would like to rank available articles according to individual interests, and highlight the most attractive article for each visitor at the story position. This paper studies an offline evaluation method of bandit algorithms that relies on log data directly rather than on a simulator. Common practice is to create a simulator which simulates the online environment for the problem at hand and then run an algorithm against this simulator. However, creating simulator itself is often difficult and modeling bias is usually unavoidably introduced." Recommendation algorithms should be tested before implemented, but directly experimenting on users can cause disruption, and could fail. In order to then test a new recommendation algorithm, the Yahoo! researchers investigate using offline data from previous recommendation algorithms to evaluate how well the new one will work. Reported Results The "evaluation method provides a solution that is accurate (like bucket tests) without the cost and risk of running the policy in the real system. These encouraging results suggest the usefulness of our evaluation method, which can be easily applied to other related applications such as online refinement of ranking results and ads display". Technol ogy Contextual bandits (in this case, the context is user features including age, gender, location). Function Marketing Digital Marketing Background "The Today Module is the most prominent panel on the Yahoo! Front Page, which is also one of the most visited pages on the Internet. The default “Featured” tab in the Today Module highlights four high-quality news articles, selected from an hourly-refreshed article pool maintained by human editors. A user can click on the highlighted article at the story position to read more details if interested in the article. The event is recorded as a story click." Benefits ​ Data "For offline evaluation, millions of events were collected from a 'random bucket”'from Nov. 1, 2009 to Nov. 10, 2009. In the random bucket, articles are randomly selected from the article pool to serve users. There are about 40 million events in the offline evaluation data set, and about 20 articles available in the pool at every moment. We focused on user interactions with the story article at the story position only. The user interactions are recorded as two types of events, user visit event and story click event."

Finance AI Case Studies British Telecom Accounting And Reporting Telecommunications British Telecom saves an estimated £100M a year using the automated contract analysis platform RAVN Read More Dell Accounting And Reporting Technology Dell reduces costs while ensuring contractual obligations are met with contract analysis automation Read More Stecklein & Rapp Accounting And Reporting Professional Services Stecklein & Rapp law firm increases productivity by 20% through automation of billing tracking Read More Deutsche Bank Accounting And Reporting Financial Services Deutsche Bank automates 30 to 70 percent of back- and mid-office processes using robotics process automation Read More UK Train Operating Companies Accounts Payable And Receivable Transportation UK Train Operating Companies automates 93% of claim processing and detects fraudulent payback claims for trains delayed by more than thirty minutes with 70% accuracy using machine learning Read More EY Accounts Payable And Receivable Professional Services EY develops embedded audit analytics system, Helix, to automate auditing complex transactions Read More Bank of NY Mellon Corp. Accounts Payable And Receivable Financial Services Bank of NY Mellon reduces processing and trade entry turn around time by 88% and 66% respectively using robotic process automation. Read More Scotiabank Accounts Payable And Receivable Financial Services Scotiabank improves payment collections of credit card customers using deep learning Read More Gullivers Travel Associates Accounts Payable And Receivable Consumer Goods And Services Gullivers Travel Associates reduces average transaction costs and invoice processing time by 74% and 86% respectively with machine learning Read More ASOS.com Accounts Payable And Receivable Consumer Goods And Services ASOS eliminates the risk of inaccurate data entering finance systems by implementing a machine learning solution for invoice handling Read More Government of the United Kingdom Audit Public And Social Sector The UK government identifies welfare and state benefits fraud with artificial intelligence Read More ANZ Bank Audit Financial Services ANZ bank identifies high risk loans and predicts customer defaults with deep learning Read More Google Budgeting And Forecasting Public And Social Sector Google predicts river floods and their severity using AI based forecasting models Read More United Nations Budgeting And Forecasting Public And Social Sector The United Nations, World Bank and ICRC aim to eliminate famine using machine learning Read More IBM Research Budgeting And Forecasting Public And Social Sector IBM Research build machine learning model to analyse migration factors for prediction with low error rates Read More The New York State Department of Taxation and Finance Budgeting And Forecasting Public And Social Sector New York State increased its collections from delinquent revenue by 8% using reinforcement learning Read More The Government of Karnataka Budgeting And Forecasting Public And Social Sector The Government of Karnataka will help small farmers with crop price market predictions by using machine vision to analyse satellite images Read More Castle Ridge Asset Management Budgeting And Forecasting Financial Services Castle Ridge Asset Management identifies and rebalances portfolio investments among diverse asset classes using machine learning Read More Overbond Budgeting And Forecasting Financial Services Overbond predicts yields for new bond issues with less than 0.02 percentage point inaccuracy by using machine learning Read More Deutsche Bank Budgeting And Forecasting Financial Services Deutsche Bank implements AI trading platform for predicting equity prices and volume Read More Wells Fargo Budgeting And Forecasting Financial Services Wells Fargo demonstrates 88% short-term and 58% longer term recommendations accuracy using machine learning to predict stock price movements Read More Otto Budgeting And Forecasting Consumer Goods And Services Otto predicts with 90% accuracy what products will be sold within 30 days driving automated purchasing and reduction of annual returns by 2M Read More Lennox Budgeting And Forecasting Consumer Goods And Services Lennox improves service levels by 16% and increases inventory turns by 25% with machine learning powered demand predictions Read More Danone Budgeting And Forecasting Consumer Goods And Services Danone increased product demand forecast accuracy to 92% with a 55% improvement in net uplift from promotional events using machine learning Read More ScriptBook Budgeting And Forecasting Consumer Goods And Services ScriptBook produces financial forecasts for films based on their scripts using machine learning and natural language processing Read More Big River Steel Budgeting And Forecasting Basic Materials Big River Steel is predicting the availability of scrap steel using a predictive AI engine Read More SunSelect Budgeting And Forecasting Basic Materials SunSelect enables greenhouse farmers to more accurately forecast their future harvests with machine learning Read More TellusLabs Budgeting And Forecasting Basic Materials TellusLabs aims at providing accurate prediction of natural resources and agricultural yields with machine learning Read More "NITI Aayog (National Institution for Transforming India), Government of India" Budgeting And Forecasting Basic Materials The National Institution for Transforming India partners with IBM to develop a crop yield prediction model using AI Read More "US Department of Natural Resources and Environmental Sciences at the University of Illinois," Budgeting And Forecasting Basic Materials The US Department of Natural Resources used deep learning vision analysis of satellite imagery to predict the size of soya and corn crops well before harvesting Read More 1 2 1 ... 1 2 ... 2

< back AI Use Case Identify and sell new mass market insurance consumer products Identify and sell new mass market insurance consumer products - these may use the advanced data processing and risk pricing capabilities of AI to deliver low-cost niche products, e..g drone insurance, cracked mobile phone screens or specific use case products Function ​ ​ Benefits Revenue - New product,Revenue - Pricing optimisation Case Studies ZhongAn~ZhongAn prices insurance products using AI to reach more customers through large online vendors Potential Vendors ​ Industry Financial Services Insurance Data Sets Structured / Semi-structured AI Technologies ​

< back AI Case Study Coca-Cola achieves 6 percent additional revenue with 15 percent fewer restocking trips by identifying the right product and placement using intelligent vending machines Using Hivery's AI solution, Coca-Cola has been able to identify the right product, the right space-to-sales ratio and the right promotional activity for products to be placed in each vending machine. The software also optimises physical product placement in the vending machine. It also analyses sales to predict demand. Coca-Cola estimates intelligent vending machines have helped drive 6% of the revenue increase. Industry Consumer Goods And Services Food Beverage And Drugs Project Overview "Vending Analytics is an AI solution that increases returns and reduces restocking in vending machines by recommending the right product mix, the right space-to-sales, and the right price for each individual machine in the fleet. Hivery's cloud-based retail software identifies the right product, the right space-to-sales ratio and the right promotional activity for products in every one of Reyes Coca Cola Botting's 19,000-plus vending machines and generates a planogram — a visual diagram that details the placement of every product in the machine — in two minutes as opposed to the 20 minutes The tool also does a "what if" analysis for a product the company might consider placing in a machine. There is no need for the company to actually test the product to determine how it will perform in the field. It optimises based on specific occasion and consumer set. The Hivery AI tool was also able to more accurately determine the best times to service the machines, which made restocking more efficient." Reported Results According to the company: * ROI delivered within 6 weeks * 6% additional revenue * 15% fewer restocking trips Technol ogy "The Hivery AI solution makes use of robotics, sensors, natural language processing, speech recognition, text-to-speech, computer vision, machine learning, machine reasoning, decision making, deep learning, neural networks, business analytics and data services." Function Marketing Merchandising Background Coca-Cola becomes the first company to implement AI in beverage vending. Benefits ​ Data ​

< back AI Case Study Capgemini improves software development productivity and quality by using machine learning driven "low-code development" Capgemini uses Mendix's AI powered low-code development platforms to manage enterprise software development visually, using it for development, deployment and maintenance. The platform uses machine learning algorithm trained on 5 million application flows built across 15 industries to predict the next steps with 90% accuracy and assist development. Industry Technology Software And It Services Project Overview "Low-Code is a visual development approach to application development enabling a spectrum of developers of varied experience to create applications for web and mobile using drag-and-drop components and model driven logic through a graphic user interface. Low-Code platforms relieve non-technical developers from having to know traditional programming languages and support professional developers by abstracting tedious plumbing and infrastructure tasks required to stand up and maintain applications. Working together, developers in the business and IT create, iterate, and release applications in a fraction of the time it takes through traditional development methods." Reported Results POC; Results not yet available Increases developer productivity and decreases defects Mendix Assist claims 90% accuracy on identifying the next step while building enterprise application Technol ogy "The platform was built based on a machine learning analysis of more than 5 million anonymized application flows built with Mendix across 15 industries." Function Information Technology Development Background Mendix Assist is the first AI-assisted low-code application development platform. Benefits ​ Data "More than 5 million anonymized application flows built with Mendix across 15 industries."

< back AI Case Study Cambridge Analytica claims to have targeted voters by modelling voter propensity to persuasion through a variety of emotional state approaches The marketing claims by Cambridge Analytica to have developed an approach to influencing public opinion by driving individualised messaging targeting key emotional states and life approaches has been somewhat walked back in the face of media and, subsequent, regulatory investigation. The role of this in key recent political campaigns including the Cruz and Trump Presidential campaigns remains a matter of dispute. Industry Professional Services Consultancy And Business Services Project Overview According to Wikipedia: "The company claimed to use 'data enhancement and audience segmentation techniques' providing 'psychographic analysis' for a 'deeper knowledge of the target audience. The company uses the Big Five model of personality. Using what it calls 'behavioral microtargeting' the company indicated that it can predict 'needs' of subjects and how these needs may change over time. Services then can be individually targeted for the benefit of its clients from the political arena, governments, and companies providing 'a better and more actionable view of their key audiences.' According to Sasha Issenberg [a journalist with extensive experience of political campaigning techniques], CA indicates that it can tell things about an individual he might not even know about himself." Reported Results Political scientists and campaigners have been highly sceptical about the actual effective impact of CA's online data tools in campaigns. Technol ogy ​ Function Strategy Data Science Background Political campaigns are increasingly using micro-targeting of messages to individual (or heavily segmented) voters to persuade them to vote for their candidates - or not to turn out for opponents. Benefits ​ Data ​

< back AI Case Study JPMorgan's new AI program for automatically executing equity trades in real-time out-performed current manual and automated methods in trial JPMorgan has trialled its AI program LOXM which automates equity trading in real-time, optimising speed and price for vast quantities without causing market disruption. Industry Financial Services Investment Banking And Investment Services Project Overview "The bank has been testing its AI program, LOXM, since Q1 2017 in Europe, and plans to roll it out across its Asian and US operations in Q4 after trials proved successful. It is being applied directly to trade execution. JPMorgan claims it is the first major bank to apply AI technology to real-time trades, as opposed to applying the technology only to post-trade allocations like many of its peers. Although LOXM will be applied to trade automation initially, it may later be trained to thoroughly familiarize itself with individual end clients to take their behavior and reactions into account when executing a trade, says Daniel Ciment, head of global equities electronic trading at JPMorgan. He adds that delegating such customization to a machine means personalization can be achieved more efficiently and at a larger scale." Reported Results "LOXM delivered significant savings and far outperformed both manual and automated existing trading methods in trials, according to JPMorgan." Technol ogy "LOXM was trained on billions of historic transactions to enable it to execute equities trades at maximum speed and at optimal prices, and to offload large equity stakes without causing market swings." Function Operations Trading Background "Financial institutions (FIs) are increasingly looking at how to deploy AI to reduce their operational costs as the technology becomes increasingly adept at crunching vast amounts of data and learning from its experiences. And as more of these players reduce their outlays, the pressure on their peers to do the same is intensifying. That a player as powerful as JPMorgan — the world's biggest investment bank in revenue terms — has committed so heavily to the technology will now make the situation even more critical for its rivals." Benefits ​ Data Historic transactions

< back AI Case Study Small Robot Company is a vendor which hopes to deploy robots to reduce chemicals and emissions while increasing farm profitability Small Robot Company is a vendor aiming at making farms more profitable by maximising their yield and efficiency. The company offers a service which comprises of small robots instead of tractors for top and soil monitoring, precision spraying and laser weeding, precision drilling and planting as well as an operating system based on AI-driven neural network. The company claims it will reduce chemical usage and cultivation energy in arable farming by up to 95%. Industry Basic Materials Agriculture Project Overview "Wilma: The brains behind the robots. Back at the farm, running the show, is Wilma. Wilma is the beating heart of the FaaS operating system. She extracts the information from our crop data model, and in combination with our AI software, helps you make decisions. Wilma uses precise, up to date data from Tom and converts it into crop care instructions that can be verified by you and implemented by Dick and Harry. Wilma takes in the sum of all farming knowledge, and applies it to the information gathered about the crop. She gives you peace of mind that they are being given the best advice and making the best decisions. You can look at the data as it comes in from the field to make decisions, decisions which will take into account agronomy, soil science and market conditions." (smallrobotcompany) The monitoring robot is in trial now, and the company is collecting data to train the neural networks. The planting robot will be ready for commercial trials in October 2018, while the full service will come on line over the next three years. Reported Results Pilot; results not yet available Technol ogy Wilma extracts the information from our crop data model, and in combination with our AI software, helps you make decisions. Function Strategy Strategic Planning Background "The company will make farms more profitable, and increase yield and efficiency, through using small robots instead of tractors. Its arable farming robots Tom, Dick and Harry will enable farmers to be kinder to soil, kinder to the environment, more efficient, more precise and more productive." (smallrobotcompany - press release) Benefits ​ Data crop data gathered by the Tom robot

< back AI Use Case Automate cybersecurity systems Utilise learning systems to effectivel and swiftly respond to security threats, many of which may have been delivered with machine learning support. This is a game where every innovation in defence triggers the next innovation in attack - and vice versa. Function Information Technology Security Benefits Risk reduction - Reduce data theft risk,Risk reduction - Malware reduction,Operational - Increased machine uptime Case Studies Metropolitan Pathologists (MetroPath)~MetroPath mitigates cyber threats using Darktrace's network monitoring and machine learning,Quickplay (AT&T)~Quickplay safeguards its data and interconnected systems with Darktrace’s AI-enabled cyber security product,The Scottish Government~The Scottish Government is protecting its sensitive data against cyber threats using machine learning,DNK~DNK protects its system from cyber threats and proactively defends it with a self-learning threat detection solution,United World College of South East Asia~United World College of South East Asia is providing security to its digital education by tackling cyber threats using machine learning,United Service Organizations (USO)~USO predicts cyber attacks using machine learning to analyse activity at network end points,Servizi in Rete~Servizi in Rete detects cyber-security threats in real-time using unsupervised machine learning to classify every action in the network,British Telecom~British Telecom improves network security by using machine learning to detect real-time cyber threats,"Giunti~Giunti, an Italian publishing house, detects cybersecurity threats in real-time using machine learning",NovAtel~NovAtel plans to reduce hacking risk through its GPS services to vehicles through deploying Darktrace's AI-enabled security software,Tencent~Tencent detects malware on Android phones in real-time using deep neural networks Potential Vendors Darktrace,Darktrace,Darktrace,Darktrace,Darktrace,Cylance,Darktrace,Darktrace,Darktrace,Darktrace Industry Public And Social Sector Security Data Sets Structured / Semi-structured,Time series AI Technologies Machine Learning (ML)

< Back Sales Sales management can see that high volume sales channels, traditionally call centres or online, may start to migrate to new AI-powered tools like text chatbots or conversational agents. These offer the potential of delivering sales at lower cost and potentially higher reliability; but that the tools resistance to be being “broken” will depend on further NLP development. The data to watch will be on conversion rates and ticket size. This is placeholder text. To change this content, double-click on the element and click Change Content. Want to view and manage all your collections? Click on the Content Manager button in the Add panel on the left. Here, you can make changes to your content, add new fields, create dynamic pages and more. You can create as many collections as you need. Your collection is already set up for you with fields and content. Add your own, or import content from a CSV file. Add fields for any type of content you want to display, such as rich text, images, videos and more. You can also collect and store information from your site visitors using input elements like custom forms and fields. Be sure to click Sync after making changes in a collection, so visitors can see your newest content on your live site. Preview your site to check that all your elements are displaying content from the right collection fields. Previous Next

< back AI Use Case Enhance doctors surgical skills with robotics Using AI-powered robotics to enhance surgical operations. This will assist greater precision, reduces risks created by manual fatigue and ensures tight oversight and recall of the task in hand. Function ​ ​ Benefits Operational - Robotic Process Automation,Operational - Lower error rates Case Studies Intuitive Surgical~Intuitive Surgical enables precise surgeries with smaller and more accurate incisions using robotics by translating surgeon's hand movements into the instruments,Huashan Hospital~Huashan Hospital develops a robotics based radiosurgery procedure to treat inoperable intracranial tumour sizes achieving 55% reduction on average Potential Vendors Intuitive Surgical,Accuray Industry Healthcare Healthcare Providers And Services Data Sets Structured / Semi-structured,Time series AI Technologies Machine Learning (ML),Traditional AI,ML Task - Action Selection - Reinforcement Learning ,Product Type - Robotics

< back AI Case Study Spotify increased service subscribers by 33% through customised music recommendations Spotify introduced Discover Weekly which generates a customised playlist weekly for Spotify subscribers. In-house algorithm developed to curate playlist based on subscriber listening habits. Industry Consumer Goods And Services Entertainment And Sports Project Overview Spotify "keeps track of what you listen to. Then it uses algorithms to see which other playlists contain the same songs—and other songs that are on those lists but not on yours. Then it feeds you those new cuts in a personalized playlist, Discover Weekly, which is refreshed every Monday". Reported Results Increased monthly users by 33%, revenue generation undisclosed Technol ogy In-house, details undisclosed Function Marketing Digital Marketing Background Music streaming platform Spotify looks for ways to increase and retain users at a time when it "is being challenged by Apple Music, the rival streaming service, and when artists such as Taylor Swift and Beyoncé are withholding their work from Spotify because they say it’s stingy with royalties. The more Spotify steers people to independent artists, the more negotiating power it has with the labels and music-publishing companies to which it currently pays 70 percent of its revenue in royalties." Benefits ​ Data Album, song and artist data previously streamed by users.