Maximizing the benefits of their own data - companies in the financial sector are also facing this digitization challenge. However, the daily flood of information is a major obstacle, as are potentially existing application and data silos that prevent direct insight into and immediate access to all relevant data. Accordingly, many banks bemoan their data quality and availability, both critical criteria for the industry's digital transformation. According to a new study by Enterprise Strategy Group (ESG) and InterSystems, almost half of the companies surveyed (48%) across all industries are struggling with the existing quality of their data. As a result, the financial services sector requires modern data management that meets all the business needs of the day and ensures compliance with regulatory requirements and mandates.
Linking individual silos
Fundamentally, companies in the financial services industry need to break down all application and data silos internally to create greater transparency across all departments. These silos are created when banks each store their information separately in multiple databases, applications and services. Often, the situation is historical: acquisitions of other companies and mergers increase the number of separate data sources owned by the bank. The crux is that silos prevent the linking of all theoretically available data. In this respect, many financial service providers currently lack the foundation to successfully implement data-driven business models or innovations.
A proven solution for this is the architectural concept of the (enterprise) data fabric, a structure of connections between the individual data sources that ensures interoperability. It allows all historical and current data from internal and external sources to be merged, cleansed and harmonized. This not only increases data quality, but also enables real-time access to all information. With the Data Fabric, data silos are a thing of the past. That's why market researchers at Gartner have already named the approach as an important technology trend and the future of data management in 2019. Since the Data Fabric builds on the existing IT infrastructure, the company's own technologies, applications and services remain usable. A complex and costly redesign, a so-called rip and replace, is not necessary. Companies can therefore continue to derive added value from their previous investments. The Data Fabric is also characterized by free and flexible scalability. This helps to absorb peak loads at short notice and to expand or reduce capacities as needed. Other tools can also be integrated quickly and easily thanks to the open system architecture.
As a result, the Data Fabric offers a central view of all data in the company, a so-called Single Source of Truth (SSOT). In addition to data discovery and data lineage, this insight also enables an informative cockpit or dashboard display of all processes in a company.
Performing analyses in real time
Taking the concept a step further is the Smart Data Fabric, which has additional built-in capabilities for analyzing data, visually displaying it in dashboards for business intelligence (BI), and using artificial intelligence (AI) and machine learning (ML). With them, financial industry organizations easily and quickly gain new insights to make informed decisions and better forecast events. Large volumes of transactional data can be ingested and analyzed simultaneously. This is based on Hybrid Transactional/Analytical Processing (HTAP), which guarantees exceptionally high performance and efficiency for multi-workloads in real time in every use case. This is exactly what matters with regard to many financial services, such as split-second transaction processing or automated credit checking and fraud prevention.
Making BI even more accessible
In the interest of better and more timely business decisions, it is also in the interest of banks to involve more employees in data analysis processes. As the study by ESG and InterSystems shows, only seven percent of companies across industries have an IT infrastructure in which more than half of the employees have access to a platform for analyzing data. The Smart Data Fabric can change that by enabling individual access to a common data model, providing the basis for self-service BI. To do this, it inserts an intermediate layer between a data platform and common tools for BI, AI and ML. The layer is used to develop a semantic data model in the form of a virtual cube. This cube can be used to organize data, define consistent metrics across existing silos, and uniquely label data fields. Employees access it with a tool of their choice, such as Microsoft Excel, Power BI, Tableau or Qlik. This is always done independently of the tools' respective query dialect, so specific queries are always answered identically. As a result, more employees are able to independently perform interactive and multidimensional analyses based on the same dataset across the company and create or modify dashboards.
Mastering digitization with Healthy Data
Immediate access to comprehensive, trusted data combined with built-in analytics and AI/ML or BI capabilities enables better and more timely business decisions. Employees immediately gain a comprehensive view of the current market situation, any risks, and emerging business opportunities. As a result, they can always find detailed answers to dynamic market developments and react quickly and appropriately even in crisis situations. The decisive factor here is above all the large amount of clean data, so-called Healthy Data, which becomes available through the successful implementation of the Smart Data Fabric approach. With this accurately processed and always up-to-date data, better results can be achieved in analyses. Healthy data is also an indispensable prerequisite for the successful use of AI and ML. In terms of companies in the financial sector, this includes use cases such as fraud detection or the automatic transaction of securities in real time. In addition, the Smart Data Fabric significantly reduces the complexity of a company's IT infrastructure. This not only simplifies operation and maintenance, but also reduces the costs involved. At the same time, the modernization and higher automation of data management cleans up any inefficiencies in the workflow.
Meeting compliance requirements
Of particular note is how the Smart Data Fabric impacts meeting compliance requirements. For financial services providers in particular, there are a number of regulatory requirements and mandates, which demands a lot of attention from them. None of them wants to risk a costly or even reputationally damaging breach. This is another area where Smart Data Fabric pays off: because the solution ensures high data quality and clearly traceable data provenance, it makes it easier to fulfill compliance tasks. In addition, data management is performed and controlled centrally, which reduces the risk of violating legal regulations and specifications or internal company guidelines. Other helpful features include real-time provision of information required for regulatory reports and the creation of models for in-house risk management. The rapid availability of data also makes it easy to implement ad hoc publications for (inter)national banking supervision and stress tests by the European Banking Authority (EBA) and the European Central Bank (ECB).
Remaining competitive and fit for the future
The financial industry is currently undergoing a period of dynamic change with numerous new, innovative and data-driven market participants. Therefore, there is a strong need for a solution that can successfully address the complex challenges of digitization. When banks invest in innovative technologies such as the Smart Data Fabric, they remain competitive and fit for the future. On its basis, they manage to derive maximum benefit from their own data and further develop their financial services. There is no shortage of concrete use cases. They range from decision support and scenario planning to risk and liquidity management, asset management and regulatory compliance. The Smart Data Fabric is the key to making a company agile, optimizing all business processes and achieving sustainable growth.
Linking individual silos
Fundamentally, companies in the financial services industry need to break down all application and data silos internally to create greater transparency across all departments. These silos are created when banks each store their information separately in multiple databases, applications and services. Often, the situation is historical: acquisitions of other companies and mergers increase the number of separate data sources owned by the bank. The crux is that silos prevent the linking of all theoretically available data. In this respect, many financial service providers currently lack the foundation to successfully implement data-driven business models or innovations.
A proven solution for this is the architectural concept of the (enterprise) data fabric, a structure of connections between the individual data sources that ensures interoperability. It allows all historical and current data from internal and external sources to be merged, cleansed and harmonized. This not only increases data quality, but also enables real-time access to all information. With the Data Fabric, data silos are a thing of the past. That's why market researchers at Gartner have already named the approach as an important technology trend and the future of data management in 2019. Since the Data Fabric builds on the existing IT infrastructure, the company's own technologies, applications and services remain usable. A complex and costly redesign, a so-called rip and replace, is not necessary. Companies can therefore continue to derive added value from their previous investments. The Data Fabric is also characterized by free and flexible scalability. This helps to absorb peak loads at short notice and to expand or reduce capacities as needed. Other tools can also be integrated quickly and easily thanks to the open system architecture.
As a result, the Data Fabric offers a central view of all data in the company, a so-called Single Source of Truth (SSOT). In addition to data discovery and data lineage, this insight also enables an informative cockpit or dashboard display of all processes in a company.
Performing analyses in real time
Taking the concept a step further is the Smart Data Fabric, which has additional built-in capabilities for analyzing data, visually displaying it in dashboards for business intelligence (BI), and using artificial intelligence (AI) and machine learning (ML). With them, financial industry organizations easily and quickly gain new insights to make informed decisions and better forecast events. Large volumes of transactional data can be ingested and analyzed simultaneously. This is based on Hybrid Transactional/Analytical Processing (HTAP), which guarantees exceptionally high performance and efficiency for multi-workloads in real time in every use case. This is exactly what matters with regard to many financial services, such as split-second transaction processing or automated credit checking and fraud prevention.
Making BI even more accessible
In the interest of better and more timely business decisions, it is also in the interest of banks to involve more employees in data analysis processes. As the study by ESG and InterSystems shows, only seven percent of companies across industries have an IT infrastructure in which more than half of the employees have access to a platform for analyzing data. The Smart Data Fabric can change that by enabling individual access to a common data model, providing the basis for self-service BI. To do this, it inserts an intermediate layer between a data platform and common tools for BI, AI and ML. The layer is used to develop a semantic data model in the form of a virtual cube. This cube can be used to organize data, define consistent metrics across existing silos, and uniquely label data fields. Employees access it with a tool of their choice, such as Microsoft Excel, Power BI, Tableau or Qlik. This is always done independently of the tools' respective query dialect, so specific queries are always answered identically. As a result, more employees are able to independently perform interactive and multidimensional analyses based on the same dataset across the company and create or modify dashboards.
Mastering digitization with Healthy Data
Immediate access to comprehensive, trusted data combined with built-in analytics and AI/ML or BI capabilities enables better and more timely business decisions. Employees immediately gain a comprehensive view of the current market situation, any risks, and emerging business opportunities. As a result, they can always find detailed answers to dynamic market developments and react quickly and appropriately even in crisis situations. The decisive factor here is above all the large amount of clean data, so-called Healthy Data, which becomes available through the successful implementation of the Smart Data Fabric approach. With this accurately processed and always up-to-date data, better results can be achieved in analyses. Healthy data is also an indispensable prerequisite for the successful use of AI and ML. In terms of companies in the financial sector, this includes use cases such as fraud detection or the automatic transaction of securities in real time. In addition, the Smart Data Fabric significantly reduces the complexity of a company's IT infrastructure. This not only simplifies operation and maintenance, but also reduces the costs involved. At the same time, the modernization and higher automation of data management cleans up any inefficiencies in the workflow.
Meeting compliance requirements
Of particular note is how the Smart Data Fabric impacts meeting compliance requirements. For financial services providers in particular, there are a number of regulatory requirements and mandates, which demands a lot of attention from them. None of them wants to risk a costly or even reputationally damaging breach. This is another area where Smart Data Fabric pays off: because the solution ensures high data quality and clearly traceable data provenance, it makes it easier to fulfill compliance tasks. In addition, data management is performed and controlled centrally, which reduces the risk of violating legal regulations and specifications or internal company guidelines. Other helpful features include real-time provision of information required for regulatory reports and the creation of models for in-house risk management. The rapid availability of data also makes it easy to implement ad hoc publications for (inter)national banking supervision and stress tests by the European Banking Authority (EBA) and the European Central Bank (ECB).
Remaining competitive and fit for the future
The financial industry is currently undergoing a period of dynamic change with numerous new, innovative and data-driven market participants. Therefore, there is a strong need for a solution that can successfully address the complex challenges of digitization. When banks invest in innovative technologies such as the Smart Data Fabric, they remain competitive and fit for the future. On its basis, they manage to derive maximum benefit from their own data and further develop their financial services. There is no shortage of concrete use cases. They range from decision support and scenario planning to risk and liquidity management, asset management and regulatory compliance. The Smart Data Fabric is the key to making a company agile, optimizing all business processes and achieving sustainable growth.