MILAN, Oct. 23, 2018 /PRNewswire/ -- ANALYTICS EXPERIENCE -- Artificial intelligence (AI) is helping drive innovation at organizations from Seoul to Liverpool. Powered by AI solutions from SAS®, the leader in analytics, organizations such as Lotte Card, Notilyze, CHU de Montpellier, EDP Portugal and Shop Direct are transforming their businesses and the experiences they create for their customers and communities.
Lotte Card offers an AI-enhanced customer experience with smarter chatbots
For many consumers, a credit card is much more than a piece of plastic – it's accessibility. And in an increasingly cashless world, Lotte Card aims to offer not only exemplary financial access to its customers, but also memorable service. With the largest distribution network in Korea, the credit card company serves millions of customers. To meet the needs of those customers in real-time, Lotte Card turned to SAS for intelligence behind their chatbot solution to better serve customers and automate call-center employee workloads.
When a chatbot is used for a morphologically complex language like Korean, its accuracy often suffers, and it is unable to match many customer queries. Through a combination of machine learning and natural language processing (NLP), Lotte Card's developers worked with SAS to design a smarter chatbot, aligning closely to execute the project from data preparation to production deployment. By taking advantage of its existing unstructured data and a custom thesaurus, Lotte Card used SAS machine learning and NLP capabilities to analyze conversations and greatly improve contextual linguistic rules. This underlying AI technology allows Lotte Card's chatbot to handle more advanced tasks such as updating a customer's personal information, immediate settlement of a customer account, and card application services.
"The AI techniques that SAS offers such as text analysis, machine learning and automation have allowed us to build a more intelligent, more evolved chatbot," says Lim Sung-wook, Big Data Team Leader at Lotte Card. "Since implementing it, our call center team can provide faster customer service with almost no waiting time. Ultimately this gives Lotte Card the advantage of more diverse customer benefits and improved customer satisfaction."
Notilyze and SAS fuel Dutch smart-city initiative with predictive analytics for IoT
The Drecht Cities (Drechtsteden) in the Netherlands have been investing in the Internet of Things (IoT) and smart technologies for more than 15 years. VitrumNet, a digital-infrastructure network of 26 municipalities, schools and healthcare organizations, embodies this smart-city initiative. Through VitrumNet, the Drecht Cities are pursuing a digitally connected region, and Dutch analytics startup Notilyze adds advanced analytics with help from SAS.
Through a customized AI solution that includes visualization, optimization, forecasting and machine learning, the Drecht Cities can analyze streaming data from sensors across the network. Connected residents and businesses can measure water, air or energy with sensors monitoring things like temperature, flow, carbon dioxide and power. The sensor data is then combined with other available data sources to feed the machine learning models.
"The marriage of IoT data and artificial intelligence is powering the Drecht Cities," says Colin Nugteren, Notilyze's founder and CEO. "Our work with SAS allows us to analyze the constant flow of information quickly to better advise the smart city project. We're able to offer insights that once seemed unfeasible – from forecasting future temperature or water quality, to predicting device failure so that the region can ensure preventive maintenance."
CHU de Montpellier accelerates hospital transformation with AI
Data is invaluable in a hospital. As a new patient details her symptoms to a physician, that data is captured – often manually – and needs to be analyzed before diagnosis. In urgent situations, that data is often analyzed by multiple physicians, technicians and other healthcare experts. Centre Hospitalier Universitaire (CHU) de Montpellier is transforming its hospital operations and patient care by making data more exploitable with SAS AI solutions.
Located on the southern coast of France, the long-time SAS customer has used data visualization tools for decades to improve hospital activity reports, patient flow and care pathways, and to assist staff. But the hospital was only capturing structured data for analysis. By implementing SAS machine learning and deep learning solutions, CHU de Montpellier will take advantage of the hospital's previously unused unstructured data, such as medical documents and nurse reports. The goal is to quickly and automatically produce models that can analyze bigger, more complex data and deliver faster, more accurate results. Examples of projects include using clinical notes and medical reports to improve patient screening and to automatically encode diagnoses and treatments using standard classification.
"The hospital housed an enormous amount of data that was simply untapped," said Caroline Dunoyer-Ortiz, Head of the Medical Information Processing Unit at CHU de Montpellier. "Accessing this data and analyzing it quickly with SAS AI solutions will allow us not only to better evaluate and treat our patients, but also to increase our research potential, helping our professionals in their day-to-day activities."
EDP and AI power Portugal
Energias de Portugal, S.A. (EDP) is a global energy utility company and leader in renewables. EDP, with more than 11,000 employees, is Portugal's largest producer, distributor and supplier of electricity.
EDP has relied on SAS analytics and AI solutions across multiple sectors of its business. One of those core companies, EDP Distribuição, is currently building business-intelligence dashboards, predictive-maintenance algorithms, and forecast and revenue assurance models with SAS. The goal of these efforts is to provide more reliable and efficient generation and distribution of electricity in Portugal.
"Some say that data is the new oil, the lifeblood of the global economy," said Yasin Ahmad, Data Analyst at EDP Distribuição. "At EDP, we think that analytics and AI from SAS are the refineries, giving us the tools for transforming raw data into value, thus providing better, more customizable and streamlined service."
Shop Direct offers credit decisions in a snap thanks to AI
With more than four million customers, Shop Direct is one of the leading digital retailers in the UK and Ireland, and home to popular brands like Very.co.uk, Littlewoods.com and VeryExclusive.co.uk. The retailer offers customers many ways to pay for their purchases, including an in-house credit card. With SAS, Shop Direct has added AI to its credit-scoring capabilities, allowing for real-time decisions. By rapidly speeding up the approval or rejection of credit-card applications, Shop Direct delivers quick credit to customers engaged in the buying process, while avoiding unnecessary risk to the company. This builds customer loyalty while improving credit risk management.
"By moving away from traditional credit risk datasets and algorithms to real-time decisions with AI, Shop Direct puts the customer at the heart of everything with personalized credit offerings," said Nick Carrel, Head of Decision Analytics at Shop Direct. "In a fast-paced retail market, SAS plays a crucial role in helping us stay at the forefront of technological and customer-driven change."
SAS and AI
SAS embeds AI capabilities into an array of solutions to deliver more intelligent, automated insights for data scientists and business users alike. From machine learning and computer vision, to NLP, forecasting and optimization, SAS AI technologies support diverse environments and scale to meet changing business needs. SAS was recently named a leader in predictive analytics and machine learning solutions by Forrester.
Today's announcement was made at the Analytics Experience conference in Milan, Italy, a business technology conference presented by SAS that brings together thousands of attendees on-site and online to share ideas on critical business issues.
About SAS
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