Artificial Intelligence

WHY AI FOR FINANCE SERVICES?

• 39% of the world population are Internet users
• More than 25% of the main banking firms have developed a Big Data Platform Project, providing competitive advantages of success. 

This is one of the sectors that manage a greater volume of confidential data and therefore is subject to greater scrutiny by regulatory bodies, which translates into problems with data governance and security. 

By means of AI, it is possible to detect and manage the increase of fraud and financial crimes, develop competitive prices, manage risk and compliance, as well as make strategic business decisions, but they are also taking advantage to develop new and customized products and services through a better segmentation and analysis of the clients.

WHERE AI IN FINANCE SERVICES?

• Risk management
• Analysis and control of fraud
• Data Governance
• Segmentation
• Cross Selling and Up-Selling
• Campaign optimization
• Solvency assessment
• Process automation
• Loyalty
• Omni-channel
• Dynamic pricing

WHY AI IN MANUFACTURING?

In this sector the heterogeneity and volume of the data collected by all types of sensors is relevant, which has an impact on the use of Big Data architectures.

In addition, with the great data integration needs, both the opportunities that allow the analysis and interpretation of the big data and the benefits derived from IoT are combined. 

WHERE AI IN MANUFACTURING?

• Predictive Maintenance
• Intelligent control of stocks
• Propensity of purchase
• Optimization of supply and demand
• Automation of strategic processes
• Automation in manufacturing

WHY AI FOR HEALTHCARE & LIFE SCIENCES?

• 30% to 40% will be strengthened medical diagnoses by the use of AI.
• 50% less in treatment costs.
• 90% of US hospitals will use AI
• China resorts to the AI in the shortage of doctors (MIT Technology review)

• 3.4% are the growth forecasts in this sector for 2035 motivated by the application of AI.

These are sectors in which the great variety and volume requires Big Data infrastructures, while the AI has been fully involved in automatic diagnostics, predictive analysis, identification of diseases, research, pattern detection.

Artificial Intelligence, Robotics, Big Data or Blockchain should help develop and accelerate the innovative process of companies in the pharmaceutical sector in terms of R&D, since it has the potential to improve the accuracy, precision and timelines of the patient diagnoses.

WHERE AI IN HEALTHCARE & LIFE SCIENCES?

• Alerts and diagnostics in real time
• Identification of patterns
• Diagnosis and image analysis
• Sentiment Analysis.
• Segmentation
• Personal assistants
• Optimization of treatments
• Intelligent control of stocks
• Demand optimization

WHY AI FOR ENERGY & UTILITIES?

• 80% of the data is NOT structured in a smart grid, (weather forecasts, documents, etc.)
• The diverse sources and volume of the data collected by all types of sensors is relevant, which has an impact on the use of Big Data architectures.
• There are important data integration needs, which creates opportunities that combine the analysis and interpretation of big data and the benefits derived from the insights provided by IoT devices.

WHERE AI IN ENERGY & UTILITIES?

• Performance management
• Predictive maintenance
• Production operations optimization
• Forecasting
• Commodities price management
• Risk Management
• Settlement monitoring
• Trading and Market Abuse Regulation
• Analysis of emissions
• Personal assistants

WHY AI IN TELCO?

• 68% of the world population has a mobile phone.
• 52% of the world's population will have Internet coverage by 2020.
• Currently, the number of mobile phones connected to the internet exceeds 112% of the world's population.
• 3 out of 4 purchases are made by mobile.
• Compared with other sectors, Telco has clearly been strengthened by Big Data and AI. The volumes of information handled by telcos exceed 800 Exabytes per month, and they also manage consumer information such as: personal information, packages and usage patterns of the contracted services, their location in real time, their sources of dissatisfaction when contacting them.

All this provides a wide range of possibilities to apply AI in this sector.

WHERE AI IN TELCO?

• Optimization of routes and increase of service quality through real-time analysis of network traffic.
• Real-time analysis applied to call data records, which allows to identify fraudulent behaviors at the time of occurrence.
• Possibility of personalizing and reconfiguring call plans at any time, gaining flexibility and profitability, just by contacting the customer service center.
• Creation of totally customized marketing campaigns for each individual client, based on geographic criteria and technologies based on social networks.
• Increase in operational efficiency.
• Use of Deep Learning techniques to make decisions in real time.
• Increase efficiency in marketing campaigns.
• Creation of innovative business models.
• Improvement of the customer experience.
• Monetization: sale of valuable information to contact networks to increase the effectiveness of their offers based on data that allows them to better understand the behavior of customers and their usage habits.
• Network Analytics
• Location-based services.

WHY AI IN RETAIL?

• 70% of global retailers will invest in Internet of Things (IoT)
• 68% will adopt machine learning technologies or cognitive platforms
• 57% will automate your processes
• 40% of retailers will develop a customer experience architecture based on AI strategies
• 25% increase in profits thanks to the use of chatbots + IA in the relationship with customers.
• The growth of electronic commerce and digital platforms have been strengthened by the knowledge generated by Advanced Analytical and Artificial Intelligence techniques.
• Analysis and prediction of consumer trends, enrichment of data from potential buyers, supply chain redesign, the improvement of the relationship and response between brand / consumer can be all improved by artificial intelligence.

WHERE AI IN RETAIL?

• Predictive inventory planning.
• Recommendation engines
• Marketing of large sales and cross-channel.
• Segmentation and market segmentation.
• The return on investment of the customer (ROC) and its value of useful life
• Facial detection
• Wifi Analytics (Customer Intelligence)
• Interactive assistants
• Client analysis, omnichannel client detection
• Risk management
• Loss prevention
• Inventory control
• Customer's buying behavior
• Use of apps and / or virtual assistants (chatbots) for Interactive purchase, complaints, support, …
• Determine the optimal communication channels to reach customers
• Make smarter decisions about product offerings
• Develop optimal promotional strategies that maximize revenue

WHY AI IN TRAVEL & HOSPITALITY?

Artificial Intelligence could improve the customer experience by helping to facilitate personalized prices during the booking process or use AI techniques for voice and face recognition upon arrival at the establishment or even provide a 24x7 specialized service.

WHERE AI IN TRAVEL & HOSPITALITY?

• Aircraft scheduling
• Dynamic pricing
• Social feedback from consumers and interaction analysis.
• Resolution of customer complaints
• Traffic patterns and congestion management.
• Booking of rooms or trips through personal assistants.
• 24x7 availability in interactions with customers.
• Recognition of patterns in clients.
• Facial recognition.
• Automation of strategic processes.
• Recommendation engines.
• Prediction of demand.
• Data enrichment.
• Improve efficiency in advertising campaigns

WHY AI IN GAMING?

Artificial intelligence is dominating the gaming sector, from board games to interactive fiction games. They are providing complex environments for decision making with which AI can experiment. The ability of games to provide interesting and complex problems, offering creativity and expression, has made them one of the most popular and significant domains for AI researchers, and every day there is more proliferation of game as a service.

On the other hand, the volume of data generated (> 50TB / day) has been multiplied, in games, games, users, interactions, graphic quality, ... and also the variety of data with sounds, images, text, this has clearly marked a movement towards Big Data platforms.

WHERE AI IN GAMING?

• Improve interactions with users
• Build the model of decision making in video games (Markov model, Fine State Machine-FSM, ...)
• Application of decision algorithms to anticipate movements with Artificial Neural Networks (ANN), Support Vector Machines (SVM) or Decision Tree Learning.
• Deep Learning applications in behavior and interaction with players.
• Development of virtual worlds, maps, characters, …
• Testing
• Predict future trends and support both the game design processes - development of new features, product design - and marketing - micro segmentation of players, analyze differences by geographic regions, etc.