Improve customer experience with supercomputers

Editor's Notes

• #3: Crédit Mutuel: After a successful pilot, the use of Watson technologies has been extended to 20,000 employees across 5,000 branches to continue to strengthen customer relationships. This marks the first commercial use of Watson by a financial institution in France to assist its professionals. The bank’s customer advisors have been using Watson services in French for the past year, integrated in their business applications, as Crédit Mutuel and IBM have partnered to train and improve Watson’s French language capabilities. The Email Analyzer will help the advisors of these branches to manage the more than 350,000 customer e-mails they receive each day. The solution allows the Bank to identify the most frequent requests, determine the level of request urgency and help its client advisors execute faster or delegate associated tasks, allowing them to accelerate and enhance responses provided to their customers. Two Virtual Assistant applications will use Watson technology to help the advisors rapidly provide customers with information on a comprehensive set of offerings, starting with complex domains such as car and housing insurances, and the whole range of savings and investments products. After one year of intensive training with the business experts of the bank, and after a successful pilot with 150 client advisors in 20 branches, both solutions were strongly endorsed by the pilot’s users. Working with Watson-based solutions trained with internal business knowledge has helped them free up time; improve the speed, relevance and accuracy of responses to queries; and ultimately reinforce relationships with their customers, providing more personalized attention. Client advisors are able to find the right answers to most of their customer questions more than 60 percent faster using the Watson-based Virtual Assistant.
• #4: Intro to cognitive/AI: This is AI for business. The consumer plays are being rolled out differently… when we’re talking about AI, we’re talking about systems that speak the language of your industry to help you gain critical insights from your data. But what can these do for enterprise? What can AI do for your enterprise? Let’s take a look…
• #5: Data is transforming every profession. Every industry is faced with turning increasing volumes of structured and unstructured data into new, easily accessible insights. There is an acute need to become an expert in your domain – and leverage your expertise. This explosion of data is outpacing our ability to capture it – and even more important, to make sense of it Companies must continually improve and personalize customer experiences and applications by infusing AI Additional data points: 80,000,000 MRIs taken every year, up from 3,000,000in 1980 600,000,000 forms of malware - with close to 400k variations introduced daily 2,200,000,000 locations generating hyperlocal weather forecasts across the globe every 15 minutes 10,000 new software vulnerabilities recorded in 2016, up 30% since 2011 500 hours of video uploaded to YouTube every minute 102,000,000 wearables were shipped last year 100,000 new cancer articles are published annually The AI market is now estimated at $32 billion, up 16x over the last four years Capturing this data is just the first challenge… making sense of it all – and gleaning insights from it – is critical. Let’s take a closer look at what we mean by AI systems, and what they can do for enterprise…
• #6: Accelerate research and discovery Watson helps you conduct more thorough research faster, uncovering insights and new opportunities by combing through diverse data sources and extracting the information you find most important. Recommend with confidence Watson can help you make more confident, targeted recommendations by drawing from a broad set of information and understanding the nuances of your current context. Enrich interactions Watson can understand and communicate with your customers and employees 24/7, responding to their needs with personalized, adaptive experiences. Detect liabilities and mitigate risk Watson understands the written language of regulations, reports, and new findings (and the visual language of quality control), ensuring that your business stays up to date and protected. Anticipate and preempt Watson monitors your systems and immediately alerts you if any issues arises that could lead to bigger, more expensive problems down the road. Scale expertise and learning Watson elevates the expertise of every employee by collecting individual know-how from across your organization, combining it with the latest lessons learned in your industry, and making all of that knowledge available to all of your employees on-demand. We are accumulating more data than ever before, and most of it is locked away in silos and inaccessible to traditional computing systems – it is unstructured and in natural language. 80% of it is dark – it isn’t understandable by the systems we’ve been operating with operating on for decades. This data, then, becomes the critical currency of business today. Insights derived from it will produce value, and cognitive systems can produce those insights. We expect cognitive to be built into virtually every digital thing – applications, products, processes… AI is best understood as “augmented intelligence” – platforms and solutions than enhance our expertise and help us be more productive, make better decisions, and see the bigger picture in the work we do. AI systems in enterprise are about adding value for knowledge workers. AI will do more than improve offerings and redefine how professions and entire industries do business – it can help us tackle some of societies biggest challenges, from population health to education AI solutions must be conceived as “human + machine.” This is about augmenting our intelligence, not replacing humans in the workforce. Look for a rise in “new collar” jobs that are compatible with the emerging digital economy. AI is at work in many industries… Take a look at how AI is at work in many industries… Manufacturing: Predictive manufacturing on factory equipment in a facility Insurance: Automation of consumer car insurance filing claims; up-to-the minute knowledge of condition of liabilities available through AI systems Pharmaceuticals: Optimization of R&D resource allocation for a portfolio of drug candidates in a clinical trial Financial services: Automated customer interactions with retail banking chatbots in natural language Healthcare: Oncologists and researchers can harness enormous volumes of clinical trial data, patient history, genomic research, and drug specifics to provide targeted care, at scale Successful enterprises are incorporating some of these technologies we’ve discussed. Let’s take a look at a few more - and why they’re important…
• #7: Video: https://www-01.ibm.com/common/ssi/cgi-bin/ssialias?htmlfid=BKV12367USEN “Our belief is that people and technology have to go hand in hand… And now we can reach satisfaction levels of higher than 85%. Believe it - the hype is true. Watson exceeded expectations.” — Luca Cavalcanti, Director of Digital Channels, Bradesco Bank Bradesco is the largest personal banking institution in Brazil. One of Bradesco’s primary challenges is to deliver cutting-edge customer support to a young a vibrant and young Brazilian market. Bradesco customer support receives 30,000 calls per day related to customer support (that’s 3750 calls per hour, 60 calls per minute). These calls come from personal bankers and customers alike. In order to better service customer Bradesco tuned to Watson and now uses a number of our generally available Watson services (Natural Language Classifier, Dialog, Document Conversation and Retrieve and Rank) along with custom cognitive assets to enable their call center agents and branch employees to answer banking portfolio questions. Bradesco is the first bank in Brazil to leverage Watson and the first company in the world to teach Watson Brazilian Portuguese. Bradesco’s Watson solution currently allows branch employees to answer general and complex questions related to 59 products of Bradesco’s retail banking portfolio. Its Watson use case covers 6,500 bank branches, more than 60,000 employees and is developed in 100% Brazilian Portuguese Cognitive banking: https://www-935.ibm.com/industries/banking/the-cognitive-bank/ Dimensions of the cognitive bankDeeper contextual engagementNew analytic insights Enterprise transformation
• #8: Internal Community: https://w3-connections.ibm.com/wikis/home?lang=en-us&spMailingID=27798847&spUserID=MzIzMTUzNjA1Mjg3S0&spJobID=981490755&spReportId=OTgxNDkwNzU1S0#!/wiki/W9d6c1069a159_40a3_a3ec_187b00f55c3f/page/Watson%20and%20H%26R%20Block%20Partnership https://www.ibm.com/watson/stories/taxes.html https://www.ibm.com/blogs/cloud-computing/2017/03/watson-hr-block-engaging-customer/ NYT: https://www.nytimes.com/2017/02/01/technology/ibm-watson-tax-return.html?_r=0 74,000 pages of tax law in the U.S.: Complex and difficult to understand for individuals, changes yearly Clients may be eligible for deductions and incentives that they weren’t aware of, and the tax professional might not be aware to ask about All this makes it ideally suited to Watson’s strengths Block has 70,000 tax professionals working at 10,000 offices nationwide. In 2015, they helped to prepare 24.2 million returns. With Watson, Block now offers a new cognitive experience for filers offered this tax season at H&R Block retail locations. The solution uses cloud-based Watson services to understand context, interpret intent and draw connections between clients’ statements and relevant areas of their return. As Watson learns more about navigating the tax code from H&R Block tax professionals, those learnings will stay with H&R Block and improve the value it delivers to tax filers.
• #9: Data sources and quality Data sources and data quality are crucial – data diversity, how it’s curated are key Managing BIG data The volumes of data needed to train AI systems and gain insights require new strategies of data curation and management. Cloud solutions are a must. The most valuable curating and training is not done by your IT staff, but rather by the experts in YOUR field. It matters where the data lives It matters where the data resides and who controls it – this is at once an IP concern, a security problem, and an institutional challenge to corral their own data. Data is a valuable resource. Training vs. programming AI systems need to learn the vernacular of the topic at hand. They need to learn the relationships among the different elements of that topic. And they must learn how to understand intent based on context. Cloud/cognitive Cognitive and cloud are not separate phenomena – they are two sides of the same coin Overcoming human biases AI solutions that can ingest and understand vast quantities of data help overcome human biases that exist in literally every industry – esp. key in cancer/healthcare, law, banking etc. Cognitive systems ingest, understand, and recommend; the human knowledge worker decides. Creating value What value can AI systems create for the enterprise? They want valuable business outcomes. Can they get increases in productivity, reduction in cost, higher revenue, better customer care, etc. from the right AI solutions? Managing data at the scale of AI solutions is a new problem – and requires new solutions Cognitive and cloud are two sides of the same coin AI solutions can overcome human biases AI systems must create value Skill positions Solution Architect: Enterprise architect that develops and creates architecture, models and integrated enteprise solution Cognitive Consultant: Ensure that the application and deployed process is suited for the business problem and the end user Cognitive Engineer: Develops and trains the cognitive system Data Scientist: Focused on the data - development, curation, maurity, evolution SME: Expert on the process, content, domain Process Owner: Owner of the process being transformed End User: Real end user that will use, leverage the application being built