This white paper discusses the transformation taking place in asset and wealth management and explains how in-memory computing options such as the GridGain in-memory computing platform can help asset and wealth management firms build the high-performance, scalable, and interoperable infrastructure that they need to successfully power their applications.
The asset and wealth management sector of the financial services industry is undergoing rapid changes. Competition among investment-services providers is growing, with a wider range of providers courting a younger, more tech-savvy client base. These young investors bring with them new expectations and new challenges. To court them successfully, providers must offer the services they demand, including a 24/7 online investment environment with access to a wider range of investment vehicles than the traditional equity and bond funds.
Technology is key for maintaining a competitive edge in this situation. Investors will no longer wait for slow software or browser refreshes, so fast performance against big datasets and streaming data is crucial. Providers also need a scalable solution that interoperates with other systems, so they can offer the full range of digital channels and investment vehicles. Sophisticated analytics capabilities are essential as well, both for meeting increased regulatory requirements and for predicting advantageous investment scenarios.
To achieve this level of performance, scalability, and analytical sophistication, many financial-services providers are turning to in-memory computing solutions. This white paper discusses the increased expectations of investors, the new challenges providers are facing, and how providers can gain the edge they need with solutions such as the GridGain in-memory computing platform.
Modernizing Asset and Wealth Management with In-Memory Computing
As a complete in-memory computing platform, GridGain helps users consolidate onto a single high performance and highly scalable big-data solution for transactions and analytics, resulting in lowered TCO. Advanced SQL functionality and API-based support for common programming languages enable rapid deployment. These features, along with the rapidly decreasing cost of memory, boost ROI for in-memory computing initiatives, enabling asset and wealth management companies to build less expensive systems that perform thousands of times better. Sberbank, Barclay’s, ING and Citi realized such benefits with the GridGain in-memory computing platform.
The key modules of the GridGain in-memory computing platform are that relevant to asset and wealth management use cases are:
- Data grid – Essentially an in-memory key value store that can be queried
- SQL grid - provides the ability to interact with data in-memory using ANSI SQL-99 via JDBC or ODBC APIs
- Compute grid - A stateless grid that provides high-performance computation in memory using clusters of computers and parallel processing
- Service grid - A service grid in which grid service instances are deployed across the distributed data and compute grids
- Streaming – The ability to consume an endless stream of information and process it in real-time
- Advanced clustering – The ability to automatically discover nodes, eliminating the need to restart the entire cluster when adding new nodes
Transforming Asset and Wealth Management with In-Memory Computing
If your organization is developing or trying to improve an asset and wealth management technology solution, please download Transforming Asset and Wealth Management with In-Memory Computing, a new GridGain Systems white paper that takes a detailed look at software and SaaS requirements and how in-memory computing can deliver the performance and scale asset and wealth management use cases demand.