{"id":47220,"date":"2024-03-15T15:21:12","date_gmt":"2024-03-15T15:21:12","guid":{"rendered":"https:\/\/www.elixirr.com\/en-us\/?p=47220"},"modified":"2025-10-31T10:20:45","modified_gmt":"2025-10-31T10:20:45","slug":"a-productised-banking-data-ecosystem-leads-to-better-data-security-cost-and-scale","status":"publish","type":"post","link":"https:\/\/www.elixirr.com\/en-us\/a-productised-banking-data-ecosystem-leads-to-better-data-security-cost-and-scale\/","title":{"rendered":"A productised banking data ecosystem leads to better data security, cost and scale\u00a0"},"content":{"rendered":"\n

Our banking clients recognize the power of data, though working out how to manage and leverage it to its maximum potential is not easy. As banks, their customers and enabling technologies change at pace, so does the breadth, volume and diversity of data, creating an ever-evolving challenge. We believe that pursuing a product-led approach to data management and enablement is the path forward, not only for an enhanced data-driven ways of work today, but also for setting the foundation for enhanced value tomorrow. <\/p>\n\n\n\n

The banking data challenge <\/strong><\/h2>\n\n\n\n

Financial institutions are constantly striving to outperform competitors, deliver innovative value to customers, manage risk effectively, and adapt to the ever-changing dynamics of the market. Today more than ever, data sits at the heart of these efforts, serving as the key to unlocking insights from historical, transactional, operational and market data. However, building an enterprise view of data is not easy, particularly as the pace of technological change creates new and varied data sources that need rationalising, categorizing and analysing to derive meaningful value.  <\/p>\n\n\n\n

Traditionally, two approaches have been adopted to manage data. The bottom-up approach involves individual functional teams creating, storing and utilizing data tailored to their needs, leading to fragmented data efficacy, duplicated organizational efforts, and a complex technological infrastructure. Conversely, the top-down approach, where a central team defines and manages data aggregation and extraction for the entire enterprise, often results in bottlenecks in data management and governance, as well as a misalignment with the specific needs of business units for effective execution of use cases. <\/p>\n\n\n\n

A new approach to data management <\/strong><\/h2>\n\n\n\n

To tackle these challenges, banks are increasingly pursuing a productised approach to data management as a means to consolidate and structure data for enterprise use. A productised approach means managing data in the same way you would a consumer product \u2013 analysing what consumers want and need, prioritizing product features, and so on.  <\/p>\n\n\n\n

Put simply, a data product is a logical grouping of data designed with commonality, consistency, and, most importantly, user consumption in mind. In banking, we see these typically grouped around customers, accounts and specific product areas such as deposits, loans and investments. The goal is to create easily accessible, ready-to-use datasets that can be utilized across the organization to meet diverse needs. This not only establishes a single source of truth but also eliminates the tangled web of disparate data storage and access methods. Moreover, data products promote enhanced data literacy by presenting data in a clear and logical manner, supported by robust data governance frameworks that are centrally defined but locally implemented, instilling confidence in users regarding data access and utilisation. <\/p>\n\n\n\n

Understanding the productised banking data ecosystem <\/strong><\/h2>\n\n\n\n

Let\u2019s unpack a productised banking data ecosystem in more detail \u2013 what does it look like and why does it matter? <\/p>\n\n\n\n

\"\"<\/a>
Click on the image to zoom in <\/figcaption><\/figure>\n\n\n\n

Banks run innumerate business processes on a daily basis both to keep the lights on and support the realization of specific strategic ambitions, such as growing deposits or expanding the customer base. Take, for example, a retail bank moving through the process of customer enrollment: a prospect enters through an active channel (digital, online, branch, etc.), an application is created and reviewed before a customer and account are created with supporting personal information. So, before a transaction even takes place, data has been produced at every touchpoint requiring storage for use. <\/p>\n\n\n\n

While this data is useful in its raw format and business lines can access it to address specific needs and use cases, where the enterprise value really kicks in is in how it\u2019s then consolidated, structured and managed \u2013 in this instance, as common data products. A productised approach means that raw data is created and ingested from core banking systems, digital applications and sources across the enterprise, before being productised and published for wider consumption.  <\/p>\n\n\n\n

By taking the data product approach we can deliver high-quality, ready-to-use data through a virtual marketplace to individuals across the organization. This marketplace provides data, governed, stored and enriched by clear standards for access and use, where users can consume using a diverse setup of methods, including reporting, AI, advanced Analytics, self service and digital applications. This marketplace can be internal-facing, external-facing, or both, depending on the maturity of the model and organizational appetite. In an internal context, business areas subscribe to data products or raw data and, assuming they meet the access requirements and agree to operating standards, are able to consume data and critically, produce valuable data that can be published back to the marketplace. For example, a corporate intelligence unit consuming the loan and customer data products to produce a regulatory risk code that is valuable for other business areas and ad hoc use cases. A similar concept applies in the external model though there are more stringent considerations required around which data can be published without compromising sensitive information before businesses can even think about commoditising what they publish and establishing the operational requirements for a functioning marketplace. Nevertheless, the opportunities exist which is what makes the productised approach to data so compelling.  <\/p>\n\n\n\n

What next? <\/strong><\/h2>\n\n\n\n

Having worked with clients to design and implement a productised banking data ecosystem, we understand the prerequisites for success as well as the common pitfalls. This is what we\u2019ve learnt: <\/p>\n\n\n\n

    \n
  1. Start small and scale<\/strong> \u2013 Like with any initiative, proving value early is key. Starting with a manageable product area with dedicated development support and business SMEs to establish the first data product before tackling more complex data domains (e.g. customer). This will help you prove out the approach and importantly, build understanding, excitement and learnings to bring to the next iteration. <\/li>\n<\/ol>\n\n\n\n
      \n
    1. Bring the business on the journey early<\/strong> \u2013 Without buy-in and adoption, the new data ecosystem won\u2019t reach its full potential. Ensure business stakeholders and established data users understand the strategic thinking behind the new approach and that there is a clear articulation of business value to ensure you have champions not detractors amongst the business.  <\/li>\n<\/ol>\n\n\n\n
        \n
      1. Manage data products like any other product<\/strong> \u2013 To meet the target standards of accessibility and utility, data products should be owned and managed like any other product area. Establishing a product manager early will establish accountability and ensure the product is built, managed and evolved effectively, whilst also offering an expert point of contact for business areas.  <\/li>\n<\/ol>\n\n\n\n
          \n
        1. Don\u2019t leave data governance as an afterthought<\/strong> \u2013 Secure and effective business use of developed data products requires right-sized data governance standards, policies and procedures. It\u2019s important to build the required governance framework in tandem with product development to ensure a continuous feedback loop and the development of a new environment that meets all required risk and operating standards. <\/li>\n<\/ol>\n\n\n\n
            \n
          1. Establish the right operating model<\/strong> \u2013 A new data ecosystem mandates an adjusted operating model to meet the ownership, management and governance needs of the new environment. Considering this early, particularly the roles, skillsets and capabilities needed to deliver, is critical to operationalisation and adoption. <\/li>\n<\/ol>\n\n\n\n

            Whether you are looking to commoditise a data marketplace or just defining your data transformation strategy, we have the expertise and learnings to support you on your journey. Contact us to discover more. <\/p>\n\n\n","protected":false},"excerpt":{"rendered":"

            Our banking clients recognize the power of data, though working out how to manage and leverage it to its maximum potential is not easy. 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1378w, https:\/\/www.elixirr.com\/en-us\/wp-content\/uploads\/sites\/2\/2024\/03\/Data-as-a-product-1640x984.jpg 1640w\" sizes=\"(max-width: 2400px) 100vw, 2400px\" \/> <div class=\"wp-component-card__preview-icon\">\n <span class='edwp-svg '><svg width=\"47\" height=\"47\" viewBox=\"0 0 47 47\" fill=\"none\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\">\n<g>\n<path d=\"M23.4141 0.539062C36.1232 0.539183 46.4258 10.8416 46.4258 23.5508C46.4257 36.2599 36.1231 46.5624 23.4141 46.5625C10.7049 46.5625 0.402465 36.2599 0.402344 23.5508C0.402344 10.8415 10.7048 0.539062 23.4141 0.539062ZM23.4141 1.68945C11.3606 1.68945 1.55273 11.4974 1.55273 23.5508C1.55286 35.6041 11.3607 45.4111 23.4141 45.4111C35.4673 45.411 45.2743 35.604 45.2744 23.5508C45.2744 11.4974 35.4674 1.68957 23.4141 1.68945Z\" fill=\"currentColor\"\/>\n<path d=\"M19.2841 33.6992C18.9579 33.6986 18.6374 33.6111 18.3543 33.4454C17.7167 33.0759 17.3203 32.3585 17.3203 31.5797V15.8189C17.3203 15.0379 17.7167 14.3227 18.3543 13.9531C18.6442 13.7827 18.9735 13.6951 19.3078 13.6994C19.6421 13.7037 19.9692 13.7998 20.2548 13.9776L33.4237 22.0406C33.6981 22.2166 33.9244 22.461 34.0812 22.751C34.238 23.0409 34.3203 23.3668 34.3203 23.6982C34.3203 24.0295 34.238 24.3555 34.0812 24.6454C33.9244 24.9353 33.6981 25.1798 33.4237 25.3558L20.2527 33.421C19.9604 33.6017 19.6256 33.6979 19.2841 33.6992Z\" fill=\"currentColor\"\/>\n<\/g>\n<\/svg>\n<\/span> <\/div>\n <\/figure>\n <div class=\"wp-component-card__content edwp-row-load\">\n <p class=\"wp-component-card__eyebrow\">\n Articles <\/p>\n <a href='https:\/\/www.elixirr.com\/en-us\/a-productised-banking-data-ecosystem-leads-to-better-data-security-cost-and-scale\/' class='wp-component-card__title'>\n <h2>\n A productised banking data ecosystem leads to better data security, cost and scale\u00a0\n <\/h2>\n <\/a> <div class=\"wp-component-card__description\">\n Our banking clients recognize the power of data, though working out how to manage and leverage it to its maximum potential is not easy. 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