9 Financial Technology Trends for 2020

Tabb Forum publishes DataArt’s discussion of key trends, including robotic process automation (RPA), big data analytics, and artificial intelligence (AI), that will drive the technological transformations in financial services in 2020.

«Gartner predicts that there will be 224 RPA use cases in the financial sector by 2020, with 72% of controllers leveraging the technology. For example, a growing number of large banks use RPA to streamline onboarding workflows such as client background verification and document gathering.»

«Companies are now re-designing their data architectures and operating principles to power up business intelligence/analytics and leverage data from both structured and unstructured sources. Industry players recognize the role of agile data and analytics in accelerating transformation. Thus, they’re developing modular data architectures that can change dynamically and evolve at the speed of business. The endgame is to enable users to interact with data in near real-time and improve the quality of products/services.»

«As the role of AI in algorithmic trading gets bigger, new ML-powered alpha-generation techniques will emerge. There will be a rise in the use of AI and ML to automate operations and aid decision making in asset management.»

«Also, intelligent business process automation will receive a boost as NLP-driven digital workers help automate front- and back-end office functions in the financial sector. NLP models will increasingly streamline business workflows and enhance user interactions with machine- generated data.»

«We expect to see AI-driven, serverless data warehouses powering advanced data management, optimization, and in-depth analytics in the finance industry. Data lake configurations will be automated too.»

«Also, we’re moving to an open banking world. Integrated information systems will enable financial service providers like banks and personal finance apps to share customer data (with the customer’s approval).»

«Companies are now re-designing their data architectures and operating principles to power up business intelligence/analytics and leverage data from both structured and unstructured sources. Industry players recognize the role of agile data and analytics in accelerating transformation. Thus, they’re developing modular data architectures that can change dynamically and evolve at the speed of business. The endgame is to enable users to interact with data in near real-time and improve the quality of products/services.»

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