Using open source code to manage risk
The Internet, computer science and digital technologies have both dark and bright sides. The internet was originally created to be a data community where digital material could be freely accessed, shared and integrated, but today it can be a magnet for fraudsters, scammers, fake news and trolls. It’s also full of reliable, high-quality data that can be used to create innovative products and services, make more sustainable decisions, and address shared problems (see the “Open Data Use Cases” sidebar).
Financial professionals should be aware of the side of the digital world that is based on data sharing, open source collaboration and collaboration opportunities, especially to manage risk.
According to the Open Knowledge Foundation, “Open data is data that can be freely used, reused and distributed by anyone – subject only to the requirement of attribution and sharing equally.” And open data is meant to be interoperable, facilitating cooperation and collaboration (see the “Open Data Sources” sidebar).
Open data is here to use
Open, interoperable data, meaning that it can be shared and used, is not a utopian vision; open datasets are there waiting to be used. Even the most tech-savvy will already have used some open, sharable, interoperable data, although in many cases they have likely paid someone to provide them with freely available data. I’ve seen far too many expensive consultancy reports that contain direct lift from freely available government or World Bank datasets – properly referenced, of course.
Open data forms the basis for many apps, websites and information systems. These systems combine various open data sets to transform online experiences. Take, for example, the widely used global platform Tripadvisor. It seamlessly combines reviews and photos provided by millions of consumers and marketing materials from individual businesses, with open source data such as location data from tourist boards, satellite imagery, map data, street view data, location services and weather forecasts.
The property sector is another example of innovative use of open data. In the analog days, all the data you had when buying or leasing real estate was an ad in a newspaper and two typed pages that were handed out when you viewed the property or physically walked into a realtor’s office. If it was a very expensive property, you may have been sent a color brochure in the post. Now everyone has instant access to online video tours, photo galleries, real estate price datasets, local crime statistics, average income data, details of local connecting roads and public transport, school performance data and even drone or satellite footage of the property and its surroundings. You can even find old photos of the property related to the previous sale and compare changes since then. And the sophistication and richness of data on these sites continues to grow.
Use of open source data in your own systems
Imagine if you could replicate the changes observed in the real estate sector in your financial information systems, based on the integration of open source data. Think about what you can do with your asset register. No longer would there be a couple of columns in an Excel spreadsheet. You can geotag it and place it on a GIS (geographic information system), link it to data on climate risk exposure, sea level rise risk, crime statistics, satellite imagery, potential pollution sources, resource availability, access to clean water, demographic information to help with workforce planning, transport availability data, drone footage or videos to manage and monitor repairs and maintenance.
This new, improved asset registry drawing on interoperable open data can greatly improve strategic decisions about assets and their protection, maintenance, sale and relocation, as well as informing leasing decisions or renegotiating insurance premiums.
Risk registers
Perhaps the biggest benefit of integrating open source data can be your risk registers.
Often the risk comes from changes outside your business, which were previously considered too expensive to collect and difficult to integrate into financial or business systems. Open source data that provides reliable, up-to-date data about the state of the systems that are the source of these risks can make managing these risks much easier.
A 2022 survey of more than 3,000 UK adults, including more than 1,000 senior decision-makers, suggests that business readiness to address the challenges of the sustainability agenda is low despite known existential threats to their business models.
Open datasets provide evidence that would simply be far too expensive for an individual business to obtain, but has been collected, aggregated and curated by organizations responsible for managing these risks. These organizations include planning authorities, universities, governments, producer organisations, international agencies, police, health boards and so on. To fulfill their responsibilities, these organizations share data that can be used by others to manage risk.
It would not make sense for any business to invest in its own global climate change forecasting model, despite the exposure of all businesses to climate risks such as those leading to business relocation or supply chain disruptions from projected sea level rise, floods or wildfires.
Fortunately, there are many applications or datasets that provide readily usable data on the probability of damage for virtually any location around the globe for different scenarios. When combined with data on the location of a company’s premises, its logistics network and the location of its suppliers, it is possible to begin to identify how predictable threats can seriously affect the business. This means that the business can react proactively and not have to wait for a disaster to occur and the costs to be incurred to fix it.
Difficult to manage risks
Similarly, open data can be used to model very difficult to manage risks, such as modern slavery or human rights violations in the supply chain. Slavery, forced labor and child labor are known to be far more widespread than many business leaders would like to admit, especially in international supply chains.
No one associated with a company would be happy to know that they have been complicit in exploiting child cobalt miners in the Congo or trafficking fish workers in Thailand. And ignoring these risks in order to maintain a kind of punishable denial is problematic in a world of ever-expanding and readily available knowledge.
There is reasonably reliable data produced by non-governmental organizations and international agencies on the location of forced labor practices by industry and location, which can be used to map an enterprise’s risk by product, sector or supplier locations. By mapping possible intersections between information on raw materials, components and suppliers, and these sectoral or national data sets, a business can begin to predict the possibility of linkages with labor practices that could destroy its reputational capital.
This improved knowledge allows a business to focus any investigation or investigation in the high-risk parts of the supply chain.
Socially conscious investors no longer have to rely on borrowers to make reports about what happened to their money. Investors can ask borrowers to upload videos to their GIS of what they are doing and monitor index changes of several deprivation and health statistics, or evidence from local environmental regulators or community groups – even in remote areas like the Niger Delta.
Management of other sustainability-related risks such as biodiversity can also be improved by using open data. You can search for and monitor the performance of all the delicate ecosystems associated with your business, or even integrate data about the quality of these ecosystems on your website or as part of your sustainability reporting system. Integrating independent, open source, third-party data can greatly increase the credibility and legitimacy of your reporting.
Tips for using open source to manage risk
Finance professionals are natural collaborators who work better together. Harnessing the wisdom of the crowd has been and still is a winning strategy, and digital technology has turbocharged this potential.
Here are five tips for incorporating open source, non-financial data into financial management decisions:
• Integrating open data about possible risks can give you a competitive advantage in insurance, procurement and other contract negotiations. When identifying data gaps in your information systems, search for open data sets rather than proceeding without any evidence whatsoever.
• Explore the benefits of combining business information systems with open source mapping data and software. This can provide new improved data visualizations and improve the interpretability of complex datasets.
• Open datasets related to environmental risk often include detailed, reliable forecasts and scenarios that can be easily integrated into strategic planning and budgeting.
• Take advantage of online training materials and invest in developing the finance team’s capacity to integrate open source data.
• Remember to only use trusted data sets from trusted organizations so as not to violate data privacy or security laws.
Integration of open data provides significant cost reductions, better risk management and value-creating potential. A few days of training, often provided for free by open data advocates, opens up a universe of data and possibilities. And many graduates already have data analysis capabilities. The data-sharing economy is alive and thriving on the World Wide Web – waiting to be tapped.
The added value of using open data comes from better, faster decision-making, new products and services, and improved risk management, regulatory compliance and accountability.
Open data can also facilitate innovative joint ventures. The UK national mapping agency Ordnance Survey (OS) collaborated with MapServe, a London-based open source platform for publishing spatial data and interactive map applications to the web, to produce a tool to help developers, urban planners, architects and surveyors with planning application processes . This collaboration allows developers to add their project to OS maps to demonstrate how their proposal protects the natural environment and gives people access to green spaces and transport links, education and healthcare.
OS data also played a critical role in the UK’s covid-19 vaccination rollout. The integration of the OS MasterMap Highways Network road network dataset with data collected from in-vehicle GPS enabled the UK’s National Health Service to minimize travel time for 50 million adults to 2,000 proposed vaccination sites.
There is an entire ecosystem of open data standards, protocols, and organizations designed to help share open data, if you know where to look.
Open data collections and foundations:
• DataHub.io.
• ODIs.
• Open Knowledge Foundation.
International agencies: Social and economic data:
• The World Bank’s open data.
• UNICEF data.
• OECD Open Government Data.
• Data Europe EU.
Sources from national authorities:
• Data.gov.
• Data.gov.uk.
• Data.gov.au.
• Statistics Norway.
Geospatial data processing and analysis:
• Open the Data Cube.
Ian Thomson, ACMA, CGMA, is Professor of Accounting and Sustainability and Director of the Lloyds Banking Group Center for Responsible Business at the University of Birmingham in the UK. To comment on this article or suggest an idea for another article, contact Oliver Rowe on [email protected].
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