Along with the usual external threats that apply to any industry of competition, regulartory compliance, and security, financial institutions also face rigid legacy systems, incompatible data formats, and gathering existing data in an easily consumed form for applications and users.
Many financial institutions have created SOAs for their core systems. Decoupling application components has made development and maintenance much more straightforward. Service oriented approaches have eased integration with legacy systems and enabled better access to data stored by existing applications, but neither SOA, business process management (BPM), nor other integration architectures like enterprise application integration (EAI) alone can overcome data integration challenges.
Enterprise Enabler, dramatically improves the time-to-value of integrations by reducing complexity and leveraging data federation and virtualization. Most integrations need to make copies of the data for ETL-type activities.Data Virtualization bridges this gap with software that brings data live without making . This reduces risk and inconsistencies becuase the data no longer has to be duplicated over and over. Operations teams can now use data in the cloud without actually having to move it physically to the cloud, meaning less security threats. Imagine being able to leverage data federalization and Data Virtualization to combine data live from multiple disparate systems and upload it or query it. From dashboards to actionable consoles to secure data exchange with business partners, Enterprise Enabler makes it easy to configure the framework behind the scenes.
Financial institutions usually engage in some type of merger and acquisition activity as a business model to drive organizational growth. This presents multiple integrations challenges; data needs to be validated, may be in different disparate locations such as a single employees laptop, and if companies are competitors getting access to some data can be extremely complicated.
Enterprise Enabler simplifies all of this by creating a Data Virtualization entities that map data to the respective sources. The process is then reversed, mapping the entities to the newly acquired data in order to easily complete validation. After the acquisition is complete, data can be moved physically or virtually to anywhere it is needed. The result is more consistent data, more accurate trades and transactions, and improved accounting and risk management. All required data is provided to end users as consistent, current information with required performance and scalability.