by Martijn Groot, VP Marketing and Strategy, Alveo
Financial services firms invest significantly in the acquisition and warehousing of many data sets from enterprise data providers, rating agencies, ESG data companies, and index data businesses.
Speed and ease-of-access to this data are critical for business users and applications, because when it is not readily available, it impacts the turnaround time and quality of decision making and increases operational risk. If data is not readily available, stale data will be used or firms will duplicate efforts to source it. Last-mile integration is about the delivery of required, validated data to the endpoints where it impacts decision-making: humans and business applications. There is increasing urgency about the goal of last mile integration, because the volume of this data is constantly expanding and the cost organisations face for acquiring it are constantly increasing.
It has become imperative in the financial services world to achieve seamless integration of data into business workflows and place it at the disposal of business users. Increasing automation including RPA and the adoption of AI in diverse fields puts further demands on data availability. The goal is easy access for reporting and financial models, and to enable better decision-making.
Firms will, however, not get the best out of their investment in data if they are incapable of verifying it, or enabling self-service by the end-users. It is no use if the data languishes in a database that is hard to get to, or needs advanced skills to access.
The flow of data through the organisation
Last mile data integration does, however, come with challenges. Organisations must establish efficient data onboarding processes and transform data sets to meet diverse technical requirements common in their applications landscape. Additionally, maintaining high service levels and responsiveness to requests for new data to be onboarded is vital to building trust and keeping business users engaged.
Taking the human body is an analogy, it has been said that data is the lifeblood of an organisation. However, it should not just flow through the main arteries: it should reach every vein and capillary so that every cell gets what it needs. Efficient data management is the key to make that happen.
It is at this point that effective distribution is required. This not only enables easier access to the data in whatever format required by lines of business, but also sets up exports or extracts of relevant data in predefined views or formats that then flow easily into business applications.
Automation and a feedback loop to improve decision-making
Financial sector organisations may know why they need to do this but their approaches often involve much ad hoc manual maintenance at the individual desktop level. That means the process becomes out of sync; data becomes stale and there is the real danger of duplication. All this inevitably ends up impairing the quality of decision-making.
Effective last mile data integration is an automated process that requires the identification of relevant data sources, mapping and cleaning the data. A solution must then transform and load data into the target system, using data quality and consumption information in a feedback loop. The essential aim is to make it easy for the specific business user. This necessitates understanding the taxonomies and nomenclature the user expects and then being able to mould, build and shape the data in a way that best suits that user.
Financial services firms that make a success of last mile integration will be well placed to unlock the full potential of their data and to maximise the ROI on their investment in multiple data sources. Ultimately, by verifying and making data readily available to users, financial firms place themselves in the optimum position to make decisions based on hard, trusted and timely data. They can streamline what are often complex operations, and be in the best possible condition to achieve greater efficiency and competitiveness.
