It can be difficult to design and develop artificial intelligence systems to meet specific quality standards. Often, AI systems are designed to be "as good as possible" rather than meeting particular targets. Using the Design for Six Sigma quality methodology, an automated insurance underwriting expert system was designed, developed, and fielded. Using this methodology resulted in meeting the high quality expectations required for deployment.
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.
Global banks that have a large mortgage business are facing pressure internally and externally to upgrade their operating model to save money, decrease processing times and enhance the customer experience – today it can take more than 60 days to complete a mortgage transaction. The pressure is particularly strong with FinTechs like US online lender Rocket Mortgage and UK digital mortgage broker Trussle creating a completely digital experience for prospective home buyers. Banks, therefore, are exploring everything from mature technologies like Optical Character Recognition (OCR) to more leading edge and high-tech solutions based on blockchain and artificial intelligence. While some of these solutions could dramatically impact day-to-day business for lenders and their brokers and customers, blockchain has the potential to completely transform the entire mortgage financing industry. The financial services industry is all about trust – whether relationship based, reputational, authoritative (legal) or transactional – banking today is built on trust.
Thank you, Mark [Carney], for that kind introduction, and thank you to the Bank of England for inviting me to this wonderful event. This is a moment to celebrate 20 years of independence during which the Bank of England has been a stabilizing force for the U.K. economy, inspiring others in the world of central banking--not least because of your guidance, Mark. This is also a moment to learn from our experiences, build on the progress made so far, and look into the future--to the next 20 years--as our journey continues. This morning, I came up Fleet Street, which always feels like a journey through history. In the Middle Ages, that street was an important center of commerce, much of which has now moved online. By the 19th century, the street was home to ticker machines and reporters racing each other to make the evening papers.
Custom DU is an automated underwriting system that enables mortgage lenders to build their own business rules that facilitate assessing borrower eligibility for different mortgage products. By means of the user interface, lenders can also customize their underwriting findings reports, test the rules that they have defined, and publish changes to business rules on a real-time basis, all without any software modifications. The user interface enforces structure and consistency, enabling business users to focus on their underwriting guidelines when converting their business policy to rules. Using Custom DU, lenders can create different rule sets for their products and assign them to different channels of the business, allowing for centralized control of underwriting policies and procedures--even if lenders have decentralized operations.