The global financial services market is expected to reach a valuation of $28,529 billion in 2025 from $22,515 billion in 2021, a growth of 26% during the forecast period, as per the Financial Services Global Market Report 2021. Data management is at the core of financial services. It helps to gain insights and make data-driven decisions. However, data analysis is a challenging task.
Recently, AWS came out with Amazon FinSpace, a data management and analytics platform designed specifically for the financial services sector. The purpose-built analytics service reduces the time it takes FSI organisations to find, prepare, and analyse financial data from months to minutes.
How it works
Amazon FinSpace is tailor-cut for hedge funds analysts, asset management firms, insurance companies etc. The tool helps tamp down the time spent on data collection and organising structured and unstructured data to allow analysts more time to focus on the research part. It further facilitates running analysis on demand across all accessible data, including internal sources such as portfolio management systems, order management systems, and execution management systems, and third-party data like job statistics and earnings reports.
Analysts can make use of a built-in library of over 100 specialised functions for time series data to prepare datasets. They can play and experiment with the available data using the integrated Jupyter notebooks and parallelise these financial data transformations at cloud scale in minutes. Furthermore, the platform offers a system for managing data access, auditing who can access what data and when. It keeps track of how data is used and provides reports on compliance and auditing. Amazon Finspace is based on Apache Spark – an open-source analytics engine for large-scale data processing.
The FinSpace time series framework defines a set of stages to transform data from raw time series data events to the computation of finance-specific analytics such as technical indicators. The FinSpace time series functions are leveraged in different stages. Each stage takes inputs from the preceding stage and serves as an input to the next stage. It’s also possible to slot your own functions at any stage, according to the AWS blog.
The service is currently available in North Carolina, Ohio and Oregon in the US, Canada, and Ireland in Europe and will be available in other regions soon. Moreover, the cost of the service is determined by the amount of data stored, the number of users approved, and the amount of computing power used to process and analyse that data.
Competition
The pandemic breakout has accelerated the digitisation of companies worldwide. Cloud adoption is at an all-time high. The major cloud players have sensed the opportunity in the fintech space and are doubling down on their services to capture the market.
Microsoft Cloud for financial services corrals Microsoft solutions, unique templates, API’s and industry-specific standards, plus multi-layered security and compliance coverage to offer differentiated customer experiences, encourage employee collaboration and productivity, handle risk and modernise core systems. Retail banks can leverage these capabilities to form a 360-degree view of the customer, incorporate digital collaboration into the process workflows to create real-time visibility to the status and streamline hand-offs, enhance insights to help reduce fraud etc. The Loan Manager feature allows lenders to close loans faster by streamlining workflows and increasing transparency through automation and collaboration.
IBM InfoSphere Master Data Management oversees critical enterprise data, irrespective of the system or model, and delivers it to your users in a single trusted view. It provides valuable insights, rapid business value alignment and compliance with data governance, rules and policies across the enterprise. It coordinates your data along the complete information lifecycle with a highly configurable framework.
