Investment banks use and make vast amounts of data daily to make decisions and execute transactions. Historically, a lower level of interest in data infrastructure from client-facing teams and friction in data processing limited returns on data assets. But as clients want more data, and as technology advances and costs less, there are signs of a more open approach.
At the same time, regulators are mandating banks to share more, and the growth of open data in other sectors has demonstrated its positive impact on innovation and value creation. The sector’s first true application of open data infrastructure may not be far off.
The Open Data Institute wants to support this sector shift by facilitating a discussion on data infrastructure and working with stakeholders to identify, test and implement solutions that make data more accessible and open to stakeholders.
In this spirit, our report considers:
- the sector’s existing data infrastructure, in terms of data assets (or datasets), processes, technologies and organisations
- where data assets are currently mapped on the data spectrum, from closed to open
- challenges and opportunities in using open data to create a strong data economy
- open data case studies from other industries
Our initial analysis highlights significant data challenges and ways open data may help. Much public data historically managed in a closed or proprietary way could be used more productively via a shared or open approach, using APIs and other newer technologies, offering interoperability the industry currently lacks. More radically, private data made more open in the appropriate ways could create value for banks, their clients and the economy.
Based on its delivery experience and research the Open Data Institute believes that a data infrastructure which is as open as possible will create most value for the sector.To begin strengthening the investment banking sector’s data infrastructure, we recommend a series of next steps:
To begin strengthening the investment banking sector’s data infrastructure, we recommend a series of next steps:
- Interested sector participants should task an independent facilitator, whether it is the ODI or another group, to harness the collective expertise and insights of investment banks by gathering their feedback on where the greatest data challenges lie.
- In partnership with sector participants, these learnings can be used by the ODI and/or other open data experts to assess where open data may be of use.
- One area where there may be a clear and immediate need is regulation: particularly Know Your Customer (KYC) and Markets in Financial Instruments Directive (MiFiD)
- Another area where there is a clear rationale for open data thinking but perhaps less impetus for change is the overall life cycle of a trade (where there is often unnecessarily closed data and/or public data not accessible in an open way).
- When specific challenges have been defined, working groups can be formed to begin identifying, testing and implementing open data solutions.
Open data is data that anyone can access, use and share.https://theodi.org/what-is-open-data With increasing amounts of open data available, more businesses are recognising the opportunities available to build and enhance their value proposition using open data. Open data brings more than access to new data sources. It is allowing businesses to explore innovative business models – ones that include publishing open data or supporting others to publish open data.
At the ODI, we have been working with open data startups and SMEs since we were founded in 2012. In this report, we aim to share some of the lessons we have learned about startups and SMEs who are building products and services with open data. We draw upon recent research we carried out during the EU-funded Open Data Incubator for Europe (ODINE) programme,https://opendataincubator.eu additional analysis of the data from this research and our own experiences with the ODI Accelerator programme.
The goal of this report is to help startups, SMEs and VCs to understand the business value created through open data and the new models for capturing that value. We do this by sharing lessons from our research into the successful ODINE companies and our work with other businesses. We believe that these new business models provide a glimpse of the future data economy.
The value of open data to business
Open data is creating value for the economy. Current estimates suggest the value of public sector open data sits between 0.4% and 4.1% of GDP. However, this existing research tends to also focus on the benefits of open data to the wider economy, rather than the benefits it can bring to individual organisations.
In some cases, research has revealed the huge amount of value created individual open datasets, primarily those published by governments. For example, a study of the US Landsat data, comprising satellite imagery of the Earth’s surface published under an open licence, found that the dataset generated an estimated $2.19bn economic benefit in 2011 alone.
In other research, the overall value of an organisation publishing open data has been quantified, for instance, TfL’s release of open transport data was recently estimated… However, there are few estimates of the value created for individual private sector companies, and next to none on the value they derive from publishing their own open data.
At the ODI, we have been working with companies of all sizes and trying to capture the lessons they have learned while building offerings with open data. We have been sharing these lessons through our research into open data businesses, including the Open data means business and Open Enterprise studies, and through our case studies.
Building business models involving open data
The core challenge faced by all early stage businesses is developing a strong value proposition and building a successful business model around it. However, not a great amount of published research has been done in academia and startup communities into how to create an operational and sustainable business model.
Categorising business models is often done through matrix- like frameworks, the most widely used framework is the Business Model Canvas, which breaks down a business model into nine core building blocks. Academics, businesses and others have been using these frameworks and other approaches to evaluate emerging trends and patterns among businesses building products and services with open data.
The team at Creative Commons have even developed an Open Business Model Canvas to describe business models built on openly licensed content. This fed into their recent work on the Made with Creative Commons project to document such businesses.
Others who have begun to classify these different trends include Ferro and Osella, Howard, Zeleti, Ojo and Curry, Tennison, the World Wide Web Foundation and Deloitte.
In our research for ODINE, we compiled a synthesis of the emerging trends and patterns identified in existing research, provided as… While we aim to build on this knowledge, we will not use these classifications but rather provide lessons about some of the different components of business models involving open data.
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