How FS can move past the AI hype to gain strategic value from Data Science
Financial institutions collect billions of data points per day, but many of these are not analyzed. This massive growth in data, specifically in finance, enables new insights not previously possible. With more available data, coupled with new maturity in AI and Data Science that is able to create new intelligence from the data, financial services institutions can realize the value of the massive amounts of data being collected in the Financial Services industry and in turn, gain more actionable insights that directly translate into business value.
Synechron is working with financial institutions across banks, asset managers, wealth management and insurance companies to re-think their data strategies, capitalize on the latest and greatest in applied-AI for valuable insight, and future-proof their digital strategies as they re-think their business models in an environment where financial firms are competing against both agile fintechs as well as technology companies like Apple and Amazon making plays in the financial services industry and customers have come to expect digital-first, self-service, intelligent options that look past automation technology toward “Intelligent Automation (IA). Learn more about these trends in our recent infographic, “The Growing Intelligent Automation Market.”
To stay ahead of the curve, we can help you accelerate digital innovation and gain a competitive advantage by employing deep data analytic tools and cognitive machine learning to turn data into meaningful assets to prepare for Data Science models, apply problem solving, and gain consumer insights with Accelerator solutions and an end-to-end delivery capability with real business-value, such as Synechron’s Data Science Accelerator program.
Learn more about drivers for Data Science application in Financial Services and insurance and how you can explore the next frontier of data science to hedge competition in Synechron’s latest whitepaper, “Moving beyond the Artificial Intelligence (AI) hype to get strategic value from data science in financial services and insurance”, which includes more information on:
- How to develop a full-scope data strategy: including sourcing data given the massive increase in data generation, while addressing challenges related to gaps and data scarcity, and leveraging existing, alternative, and synthetic data
- Exploring new approaches across the AI maturity curve beyond AI Automation and simple business process management to more Intelligent Automation (IA) approaches that leverage advanced Natural Language Processing (NLP) expertise powered by Data Science to better understand content, context, intent, and specific financial services language
- How to use AI and Data Science to drive forward business goals relating to customer experience across the entire client lifecycle from acquisition, retention, engagement, intelligent product recommendations, and business intelligence across the digital ecosystem – and how to choose and apply the right models/approaches to achieve these goals with Data Science
- Completing pre-requisites for a full Data Science program, including strategy, operations, and infrastructure requirements like setting up the right team structure best practices, cloud and infrastructure considerations, and addressing regulatory compliance concerns through model auditability, data governance, and model lifecycle management (MLM)
