What we're looking for in research applications

To academics and researchers, novel data is inherently very exciting. There's incredible potential to create high-impact research projects that use this data to answer pivotal policy questions. At the Financial Data Service (FINDS), funded by Smart Data Research UK and run by Smart Data Foundry, we seek to make this new data available in the form of private sector financial data held in a Trusted Research Environment (TRE), and we've just launched our digitalised data application process. However as this data is highly sensitive, it requires strict controls around access, usage and storage.    

Developing and implementing these controls is an important part of what we do as a data service. Following well-established guidelines and advice such as GDPR and the 5 Safes Model developed by the ONS, we have created a set of policies we adhere to when deciding whether to grant a research project access to the data in the TRE. These range from ensuring a project is scientifically robust and the data requested is appropriate to meet the aims of the project, to drilling down into the ethics and intended impacts of using this data.

What should a researcher be thinking about when applying to access data through FINDS? 

1. Is the requested data fully aligned with the research project’s needs?

Researchers should ask if this data is truly necessary for a research project. Will the research questions use this data as a focal point and be unanswerable without it? Or will the data merely provide a contextual backdrop, adding to but not being essential to the answers? If the latter, consider that we are constantly working on free-to-access aggregated data products that could help enhance your project instead. These can be viewed in the data catalogue on myFoundry.

2. Have you considered data minimisation?

This is a key principle for us, making sure that researchers are only accessing data that is absolutely necessary for their projects. That's not to say this is easy; by nature a lot of research is exploratory, so one may feel like they need all of the fields and the whole population sample from a given dataset before they can tell what is actually useful for their analysis, especially in case some fields have unexpected effects on others. The unexpected can be where some really exciting research begins!

Data minimisation doesn’t mean asking researchers to hack down their data asks to the point that exploration isn’t possible. However, we do as that researchers justify, on a field-by-field basis, why access is required for their research. This helps us to be confident that the request is appropriately minimised to protect the privacy of the data subjects.

3. Who is on your team, and what support will they need?

Then there are some miscellaneous things to be considered. Who's in your project team, and do they all need data access? You're certainly not allowed to look into the TRE over someone's shoulder without permission to access yourself. Do they have the right types of skills for big data analysis, such as not having to sacrifice efficiency for usability when working with different data formats? Have you got a reasonable project timeframe in place for data access, analysis, and egress? All these things are essential for getting the most out of our data for your project.

4. Have you considered the ethical implications and impacts of your project?

At Smart Data Foundry, we're clear that we're only interested in research that intends to benefit the public, and we make sure that all projects align with our missions of reducing poverty and inequality or improving economic wellbeing. Of course, 'public good' can be a somewhat nebulous concept; how can we truly know what that is without consulting every member of the public? However, there are certain measures we have in place to assess this. For example, will the research form an evidence base or improve knowledge in a way that can enhance policy decisions?

Fairness is central to our assessment of your research proposal; we ask applicants to consider not only the data protection harms as described by the Information Commissioner's Office, but also beyond this into wider harms that could result from inappropriate use of data.

Ethical principles

We are guided by three key ethical principles when considering research applications to use smart data available through FINDS:   

• Public benefit – we seek clarity on the public benefit of the proposal, and the positive contribution it will make to reducing poverty and inequality and improving economic well-being.  We need particular assurance that the proposal will contribute to an evidence base that supports public policy-making or public service delivery and/or improve knowledge, in particular on social or economic trends.

• Transparency and accountability – we expect to see that the research proposal has appropriate governance and oversight.

• Fairness – applicants are asked to consider any potential for harm, in particular, unintended discriminatory effects on individuals and social groups that could arise from the research proposal.

The application process

Once you are confident that your research proposal has considered all of the above, you can start the application process. Applications are made via myFoundry, and can take 12-16 weeks for approval and the creation of your dedicated environment within the TRE.

1. Submit your application

Using the form available via myFoundry, please include as much information as possible about your project, including: 

• Your research question and how it aligns with Smart Data Foundry’s missions to reduce poverty and inequality and improve economic wellbeing.

• The stakeholders, including how your project is being funded. 

• The project team, and who will be accessing the data.

• Any ethics checks and data impact assessments which you have already undertaken.

• The datasets you’re hoping to access, and the fields you would like access to. 

2. Assessment & data suitability checks

Once we receive your proposal, we assess your proposal, including performing data suitability checks to ensure that your project is aligned with the data available and that we can properly support your project.

3. Ethics & disclosure checks

Your proposal undergoes an ethics check and we ask for a DBS check for everyone involved in the project. If you cannot provide an institutional ethics assessment, we will provide you with an assessment form to complete.

 4. Data protection training

Once approved, everyone involved in the project who will access the TRE must complete Data Protection Training to understand your responsibilities when accessing sensitive data in the TRE.

5. Access the TRE

Your project is set up and access is granted to the TRE – your project can begin! More guidance for researchers accessing the TRE can be found on myFoundry

In summary

At Smart Data Foundry and FINDS, we believe in the transformative potential of financial data to support research that improves lives and informs better policy. But with that potential comes the responsibility to ensure that access to sensitive data is handled with care, rigour, and a deep commitment to ethical standards. Our application process is designed to support researchers in building strong, impactful proposals that are methodologically sound, privacy-conscious, and aligned with our mission to drive public good.

By considering the necessity and minimisation of data, assembling the right team, and critically evaluating ethical implications, applicants not only improve their chances of quick approval but also help us maintain a safe, trusted environment for impactful research. If you're confident your project meets these principles, we encourage you to take the next step and apply through myFoundry. We look forward to working with you to unlock new insights and drive meaningful change through smart data.