Disruptive forces playing in the market economy will enforce organizations to re-invent 4 quarterly rolling planning/ bi-weekly CEO reviews. IA is set to principally change what we do, just as process automation (RPA) did when it was introduced into the world of customer experience, employee experience, business ops, applications, infrastructure, and data. Collaboration between intelligent automation technology and AI is a movement meant to spotlight and anthropomorphize the system to ALT
“Adopt,” “Learn,” “Think.”
This is helping us develop smarter, more customized BOTs, improve the performance of global operations (business ops, application, infrastructure, and data) and enhance customer experiences and new revenue in many industries.
Things are looking promising: Virtual assistants adapted to our needs Cosbots (conversational robots) that provide smart, specialized advice Semantic search engines that can chat with us. Autonomous or semi-autonomous objects that can adapt to uncontrolled environments (from cars to garage doors and vacuum cleaners to A380 airplanes) Increasingly realistic augmented reality universes
But, there is still a long way to go before we have systems that do better at decision-making, display emotional and ethical capabilities.
First Wave, Second Wave, Third Wave of IA Continuum Organizations continue to invest much time and effort into “systems that do,” such as RPA, but they are really eager for “systems that think and learn” to add a more pragmatic element to our daily lives.
DO: RPA works best with structured inputs and hardcoded business rules as the primary automation capability if a system is able to execute and decide autonomously.
Think: IT service automation systems are able to analyze a user-generated request or trouble ticket for a keyword or other event triggers, based on embedded algorithms and logic, programmatically thinking and making decisions. Their performance even improves over time as a comprehensive history of resolution data grows to help programs improve logic and future decision-making.
Learn A range of fast-evolving AI technologies to transform systems to analyze vast amounts of dynamic and unstructured input and execute processes that are highly dynamic and non-rules based. In a sense, these learning systems apply rules based on context and make optimized adjustments for it. This improves the human side of an organization’s operations, with people more empowered to think creatively. The speed of advances in automation through Artificial Intelligence is phenomenal and certain. Coforge Tech is uniquely equipped to develop a system with a smart and humanistic approach to IA.
Where does the rubber hit the road with this delicate balance?
In the US the Fed has cut Fed Funds rates and pumped in excess of $1.5 Trillion into liquidity relief for banks to keep them viable. Other central banks including the European Central Bank have infused liquidity in similar ways, but ultimately consumers will only care about how this affects them. We feel that this consumer sentiment will be a key indicator of which financial service.
Why is IA part of our daily lives today?
IA, part of our daily lives In the French banking sector, IBM’s Watson solution has been rolled out in Credit Mutual to almost 20,000 customer advisers. The aim is again to optimize employee productivity, suggesting answers that advisers can offer on questions about savings and insurance products and processing emails more quickly thanks to customizable replies. 8Drone saves 2 Australian swimmers in the world first. (BBC) Rwanda’s drone to increase blood delivers to 400 new destinations. (KT PRESS) Special operators are getting a new autonomous tactical drone. (Defence One) Meet Branch, the ‘Branchless bank’ for emerging markets. (Bloomberg) Amazon opens a supermarket with no checkouts (BBC)
The current wave The development of new algorithms, described as machine learning, put AI back on the menu in the 1990s. Then, in March 2016, deep learning – a variant of machine learning – became a buzzword in the wake of AlphaGo, AI developed by Google subsidiary DeepMind, beating one of the best players in the world at a strategy game called Go. AI is now focusing on specific areas, such as medical diagnosis, bank fraud detection, assisted driving, and the development of personal assistants. It has become a driving force behind some highly practical, and commercially exploitable, innovations. 80,000 developers have had access to Watson’s various APIs since 2013, through what IBM has called “self-service artificial intelligence”. While Microsoft offers over twenty “cognitive services”, such as image recognition (“computer vision”) and speech recognition. Amazon, meanwhile, is developing the AWS catalog with a machine learning predictive analytics service In May 2016, Google announced it was opening up three APIs – translation, natural language processing, and speech-to-text in 80 languages. Open Source: Google, Apple, and Facebook have opened up their respective platforms – TensorFlow, DSSTNE, and Technet. Mention should also be made of the OpenAI research project – open to everyone – launched by Elon Musk with support from big web names such as Peter Thiel, CEO of Palantir, and Reid Hoffman, who created LinkedIn.
Key points Organizations need to prepare for the massive wave of change in job roles that IA will bring. Intelligence-as-a-Service capabilities are making IA available for organizations. IA can enhance the work that humans do and improve customer service and satisfaction levels through a self-driven business model.
How Coforge can help? Experts by your side, worldwide. The best digital tools for your innovation needs. A human understanding of your employees and customers. The result.
How will IA evolve? Types of learning “do” systems have in use: Supervised learning uses data labeled by humans, which is expensive. A data set is presented to the learner system, such as the photo of an object or an animal with its category, and the system is able to use its ability to generalize to correctly categorize a new image. This is the most common method currently. In unsupervised learning, data is not labeled beforehand. The learning phase has to be supervised by an expert in the field. In reinforcement learning, the machine receives a signal, a sort of reward, including whether the response was correct or not. This form of learning, which requires a high number of trials, was successfully used by DeepMind’s Go program, AlphaGo. Intelligent virtual assistants have become a core part of customer service delivery. This is helping to address consumer expectations for 24/7 support while reducing operational costs. Voice-Enabled Ancillary Services Voice-Enabled Portfolio Manager Voice/Chat Assistant in Insurance Voice/Chat Enabled IT Tickets Assistance Voice/Chat Enabled HR Assistant Assistance in Assets Management
For e.g, our HR virtual assistant bots have a CV, an HR file, and even a telephone number in the Coforge Tech internal directory. They have the capability to deliver a first contact resolution rate of 78%, the next 13% requests with help from colleagues and the last 9% are through only human intelligence. Predictive analysis to anticipate the future, log in using biometrics, and receive support from intelligent virtual assistants to reduce operational cost with better quality & better experience involving: Flight Turnaround for Airport Ops Customer Churn Prevention Credit Card Fraud Detection Disruption Management & Planning Price optimization and management Smart Email Assistant Coforge Tech Business Ops Bots have a microservice, a composable architecture, and even a choice of cloud provider (MAG) footprint within our IA platform. They deliver an accuracy rate of 83% and the next 16% with precision help from human colleagues for deep learning. 1% is the error rate.
Customer services make possible other activities beyond answering questions, such as the simplification of identity authentication processes through face or voice recognition. Customer Onboarding Cheque Fraud Detection Cognitive Claims Processing in Insurance Identity Verification Health Personal Assistant Visual Assistant in Public Transport
Coforge Tech Business Ops Bots have a microservice, a composable architecture, and even a choice of cloud provider (MAG) footprint within our IA platform. They deliver an accuracy rate of 83% and the next 16% with precision help from human colleagues for deep learning. 1% is the error rate.
Key points Self-service FAQ and chatbots on websites are now accepted by consumers, complementing human advisers for complex queries. Data from email, online chat, IM, and social network channels is vital to train AI tools in customer service tasks. AI can relieve pressure on customer advisers and help to reduce very high staff turnover in contact centers.
How Coforge can help? Our IA Platform “Tron”, consists of API-driven Bots, Coforge Tech BOT Store, and AIR Framework – a self-driven business model. Implementation of intelligent tools to our shared service center customers and lab to market-ready AI domain 250 use cases. Strong partner ecosystem
Can IA revolutionize? The claim experience journey [insurance carrier] Business Process: Insurance Claim Processing Used For: Core Legacy System - Claim Fulfillment Used By: Business Process specialists Use Case: In the Claim request fulfillment process, the information received is unstructured that might be because of the availability of information with respect to a situation, ineffective conversations with agents, and legacy and/or new systems. Agent handed over the information regarding the claim by a back-office agent where Claim Management entered the unstructured information incorrectly. The claiming team made a mistake during the claim lifecycle by selecting the wrong/incorrect product/charges as the user needs to process the component manually.
Business KPIs can be Improved % Claim Fulfillment TAT % Revenue Leakage/Loss due to incorrect data % Customer churn due to incorrectness We at Coforge believe that there is no simple or short-term answer. This is a life and business altering crisis, the likes of which we have never experienced in our lifetime. Use these bullets as the foundation for your decisions, and your organization will be well prepared for whatever comes next: Continually monitor the crisis and be ready to change course at a moment’s notice as the situation evolves. Communicate frequently and be brutally transparent– your organization will be respected for it. When making decisions, remember to have humanity, we are all in this together, and only collectively will we emerge healthily.
Fully leverage machine and human collaborations
IA Case Study: Customer Experience, Cost Reduction The claim experience journey [insurance carrier]
Client overview: Our client, one of Australia's largest airlines initially started offering seven return flights a day between Brisbane and Sydney and this has since been expanded to cover all the major Australian cities and many holiday destinations
Drivers/Challenges: Transforming Digital and Emerging Technology to support the Group’s Vision - ‘Changing Aviation For Good’ by delivering consistently great customer experiences, accessible anywhere, anytime via any device. What if a user is in busy traffic instead of a quiet place. What if a user wants to re-plan/change which is like a better experience (end-to-end) What if a user hangs up due to voice identity mismatch
Key points #IA Coforge Tech offers full automation potential assessment in 5 days with a drill through a framework, business case creation, and implementation roadmap. An intent of transforming with smart outcome-based engagement models.
The Coforge Tech differentiators Gen I - Capabilities & intent to have half the workforce digital and helping customer unlock budgets for collaboration innovation and co-creation innovation and move to leaner, efficient, and integrated with emerging technologies 41% - Average Saving in ITOPS Committed and passed on to our customer (five year period) 3 – Industry-leader Microsoft, IBM, and Google and Analyst Firms HFS, Nelson Hall, and Everest recognized Coforge Tech IA Platform “Tron” 33 - Average of operational efficiency saved across Business and IT translated into customer new revenue and experiences for customers and employees 2 - Of five-year-plus existing customers proactivity migrated to “Intelligent Generation” in last quarter