As more and more financial service companies ride on the trend of digital transformation and data solutions, the trend will be the turnkey to differentiate client’s business from others. According to McKinsey, companies across different industries have begun successfully using external data from a variety of sources. Most of financial firms plan to leverage AWS machine learning services, such as Amazon Comprehend and Amazon Sagemaker, combining and analyzing external datasets with internal ones such as public data, business and consumers’ data and web-harvested data, to create more valuable insights for business decisions.
Amazon Comprehend is a natural-language processing (NLP) service that uses machine learning to discover valuable insights and connections in text. A common scenario in the financial industry is that it makes good use of external data crawled from online forums such as Reddit, Facebook, and other social media, with the use of Amazon comprehend, to analyze the buzz of the market and public opinions.
Another powerful AI tool for machine learning on AWS is Amazon Sagemaker. Amazon Sagemaker allows data scientists and developers to train and deploy machine learning models in quick and easy way. Enterprises can leverage various data such as credit card using history, geolocation data, or users’ income to create recommendation engines for financial-based scenarios. In the insurance scenario, enterprises can predict the type of insurance that customers may possibly purchase with well-trained recommendation engine and ultimately lead to more successful deals.
An international equity investment startup has a great amount of stock and investment data need to be process, however, it’s lack of data scientists and domain know-how on AI. After consulting the business purposes and understanding the dataset, eCloudvalley data experts used Glue ETL jobs to clean, prepare and manipulate data. Afterwards, they built NLP model with Amazon SageMaker Studio and AWS Comprehend to detect sentiment on market issues and trends. What’s more, to present the data into insights, eCloudvalley configured Amazon Quicksight, a cloud-native, serverless BI service on AWS, to extract required information and predict stock marketing trends with customized dashboards.
To sum up, AWS services serve powerful IaaS, PaaS and SaaS for data solutions that drive success in financial industry. Combined the self-owned data with external dataset, the data journey of the financial enterprises will start in much easier way and release the business value, last but not least, that make financial service companies excel and differentiate themselves from others.