These four new solution accelerators help financial services and insurance firms solve complex business challenges by discovering meaningful relationships between events that impact one another (correlation) and cause a future event to happen (causation). Following the success of Synechron's AI Automation Program – Neo, Synechron's AI Data Science experts have developed a powerful set of accelerators that allow financial firms to address business challenges related to investment research generation, predicting the next best action to take with a wealth management client, high-priority customer complaints, and better predicting credit risk related to mortgage lending. The Accelerators combine Natural Language Processing (NLP), Deep Learning algorithms and Data Science to solve the complex business challenges and rely on a powerful Spark and Hadoop platform to ingest and run correlations across massive amounts of data to test hypotheses and predict future outcomes. The Data Science Accelerators are the fifth Accelerator program Synechron has launched in the last two years through its Financial Innovation Labs (FinLabs), which are operating in 11 key global financial markets across North America, Europe, Middle East and APAC; including: New York, Charlotte, Fort Lauderdale, London, Paris, Amsterdam, Serbia, Dubai, Pune, Bangalore and Hyderabad. With this, Synechron's Global Accelerator programs now includes over 50 Accelerators for: Blockchain, AI Automation, InsurTech, RegTech, and AI Data Science and a dedicated team of over 300 employees globally.
China's 19-year-old Go player Ke Jie reacts during the second match against Google's artificial intelligence programme AlphaGo in Wuzhen, eastern China's Zhejiang province on May 25, 2017. Artificial intelligence is firmly embedded throughout the economy. Financial services firms use it to provide investment advice to customers, automakers are using it in vehicle autopilot systems, technology companies are using it to create virtual assistants like Alexa and Siri, and retailers are using artificial intelligence (AI) together with customers' prior sales histories, to predict potential purchases in the future, to name but a few examples. The potential of AI to boost economic growth has been discussed in numerous forums, including by Accenture, the Council on Foreign Relations, the McKinsey Global Institute, the World Economic Forum, and President Obama's Council of Economic Advisers, among others. The most dramatic advances in AI are coming from a data-intensive technique known as machine learning.
This edition of the conference on'Financial Evolution AI, Machine Learning & Sentiment Analysis' by UNICOM Seminars interrogates and explores the implications of AI & ML in the financial services industry. Artificial Intelligence and Machine Learning (AI & ML) and Sentiment Analysis are said to "predict the future through analysing the past" – the Holy Grail of the finance sector. They can replicate cognitive decisions made by humans yet avoid the behavioural biases inherent in humans. Processing news data and social media data and classifying (market) sentiment and how it impacts Financial Markets is a growing area of research. The field has recently progressed further with many new "alternative" data sources, such as email receipts, credit/debit card transactions, weather, geo-location, satellite data, Twitter, Micro-blogs and search engine results.
Without a doubt, 2016 was the year'disruption' became tangible. Events like Brexit, the U.S. election and India's demonetization exercise brought home the reality we are living in a fast-changing global society where a sense of anti-establishment and rebellion is accelerating change. This shows no sign of stopping in 2017, with new technologies allowing banks to offer service levels more synonymous with hospitality than financial services, and with established technologies like artificial intelligence and robotic process automation seeing a resurgence in combination with new voice commerce models, IoT data, and robo advisors to offer more personal, more contextual and ultimately unique banking experiences for each and every one of us. In meeting with decision-making executives from the U.S to Europe, the Middle East, India and Singapore, I have compiled a clear list of trends that are dominating technology investment discussions across the globe's leading banks. In 2016 we already saw several leaders' like DBS, Santander, Wells Fargo and Bank of America roll out their chatbots, but 2017 is the year when the rebirth of this very old technology will come into its own.
Trips to other parts of Tokyo's technology centers helped round out the impression that Japan was becoming a major player--albeit quieter than its neighbors--within the global startup ecosystem. Visiting ZMP Inc. demonstrated the future of mobility, as this company is focused on the goal of being the "robot of everything" driving a more convenient lifestyle for everyone. This means level-four completely autonomous self-driving vehicles (a 2020 goal of Prime Minister Abe and Information Technology Minister Hirai), mass deployment of logistics robots (automated delivery) and focus on the needs of the country's aging society. Spending time with Shift Technology, I saw the well-demonstrated results of its partnership with the Tokyo Metropolitan Government to innovate within Japan's second largest insurance market by leveraging technology to make insurance claims more efficient. Peter Haslebacher of Shift said, "If you succeed in Japan, you can make it in any market", referring to the complexity and homogeneity found within the Japanese ecosystem--a great challenge for any ambitious startup.