Code encounters: algorithmic risk-profiling in housing

This project will examine the societal impact of algorithmic risk-profiling tools used by lenders and landlords.

Housing decisions are made with the help of algorithmic tools as a way for lenders and landlords to mitigate risk. Credit scoring in the mortgage market and automated tenant screening tools are increasingly commonplace. However, there is little understanding about the societal impact of these human-tech encounters. Questions have been raised over the construction of these technologies, whether they are understood by applicants or service users and if they embed bias into their decision making. Despite this lack of knowledge these tools have become further entrenched in our society and systems.

The research team will be addressing this knowledge gap by conducting the first UK examination of housing risk-profiling technologies. The project will be conducted in two phases:

Literature review

Scoping the field by conducting a literature review and appraisal of available products. This will build upon existing research and utilise a variety of sources such as privacy policies, internet searches and academic literature.

Qualitative dataset

Developing qualitative insight by building a dataset of 120 interviews. These will be conducted with a variety of stakeholders and will help build an understanding of risk-profiling tools.

The completion of the two phases of work will help to progress our understanding of how these tools are constructed, the motivation for their use, how they are used in the housing market, how users interact with them and any policy or practice implications.

Targeting a variety of different stakeholders will help the project have as big an impact as possible. Social housing providers, trade organisations, landlords, mortgage lenders, regulators, financial services and the general public will all be considered. Each stakeholder will receive a variety of outputs including reports, short articles, infographics, talking head videos and academic papers. These will be accompanied by engagement activities to ensure that the research findings contribute to the debate within policy and practice networks and ultimately achieve tangible change.

The partnership will be subject to an ongoing evaluation based on the RCDi framework. This will enable us to better understand the success of the network in improving research capacity.

Findings and Publications

Downloadable PDF version of the project's literature review is now available:

Literature review (PDF , 1,649kb)

The first paper from our study (Automation hesitancy: confidence deficits, established limits and notional horizons in the application of algorithms within the private rental sector in the UK) is published in ICS and will form part of a Special Issue on Algorithmic Dwelling. It explores the drive towards the adoption of new digital data resources and automation in private sector tenant referencing tools, highlighting evident hesitancy in uptake and the centrality of people within these processes.

Beer, D., Wallace, A., Ciocanel, A., Burrows, R., & Cussens, J. (2023). Automation hesitancy: confidence deficits, established limits and notional horizons in the application of algorithms within the private rental sector in the UK. Information, Communication & Society, 1–16. https://doi.org/10.1080/1369118X.2023.2264954

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Professor David Beer summarises the paper in this Faculti video:

Summary Video

New paper published about the use of Open Banking in private tenant referencing services with Alexandra Ciocanel, Alison Wallace, David Beer, James Cussens and Roger Burrows:

Ciocănel, A., Wallace, A., Beer, D., Cussens, J., & Burrows, R. (2024). Open Banking and data reassurance: the case of tenant referencing in the UK. Information, Communication & Society, 1–16. https://doi.org/10.1080/1369118X.2024.2310481

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New paper from the team on the retention and commitment to the manual in automated systems:

Beer, D., Wallace, A., Burrows, R., Ciocanel, A., & Cussens, J. (2024). Valuing the manual: the demarcation of embodied practices within algorithmic decision-making processes. Social & Cultural Geography, 1–19. https://doi.org/10.1080/14649365.2024.2347872

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New paper from the team on digital tenant risk-profiling tools in England’s Private Rented Sector (PRS) and their influence on housing access and fairness:

Wallace, A., Beer, D., Burrows, R., Ciocănel, A., & Cussens, J. (2025). Algorithmic tenancies and the ordinal tenant: digital risk-profiling in England’s private rented sector. Housing Studies, 1–21. https://doi.org/10.1080/02673037.2025.2453005

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New blog post on Platform about new modes of screening for access to housing in an ordinal society:

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Main Findings

The Code Encounters project has concluded and the overarching findings and tenure specific reports are available below. In addition, separate briefings highlight the findings for each housing tenure.

The study examined the use of new data and technologies in tenant referencing in the private rented sector (PRS), affordability assessments in social housing and in credit risk decision making in mortgage lending.

The project illustrates the increasing importance of algorithmic assessments that govern our access to a home. While in practice we see a hesitant and variegated landscape, and much value placed on human input, we observe the memetic use of greater automation and expanded data collection practices. We highlight the use of Open Banking technologies expanding across tenure that represents a significant expansion of digital insights available to landlords and lenders about financial behaviours beyond a person’s payment histories. Inferences made from such digital data and algorithmic assessment illustrate what Foucade and Healey conceptualise as the Ordinal Society that necessitates greater awareness of the importance of people managing their digital profiles.

There are 4 reports, one short report summarising the project findings and 3 tenure specific reports and policy briefings.

Overarching findings

Wallace, A., Beer, D., Burrows, R., Ciocănel, A.and Cussens, J. (2024) Housing and Algorithmic Risk Profiling in England- Report of overarching findings- Code Encounters Report 1. York/ Bristol, University of York/University of Bristol.

Overarching findings (PDF , 2,342kb)

Private rented sector

Wallace, A., Beer, D., Burrows, R., Ciocănel, A. and Cussens, J. (2024) Digital tenant referencing in England's private rented sector - Code Encounters Report 2. York/Bristol, University of York/University of Bristol.

Private rented sector policy briefing (PDF , 1,342kb)

Private rented sector full report (PDF , 2,670kb)

Social housing

Wallace, A., Beer, D., Burrows, R., Ciocănel, A. and Cussens, J. (2024) Data, automation and purpose in pre-tenancy affordability checks in social housing - Code Encounters Report 3. York/Bristol, University of York/University of Bristol.

Social housing policy briefing (PDF , 959kb)

Social housing full report (PDF , 2,801kb)

Mortgage Lending

Wallace, A., Beer, D., Burrows, R., Ciocănel, A. and Cussens, J. (2024) Credit risk decisions, mortgage lending and technological possibilities - Code Encounters Report 4. York/ Bristol, University of York/University of Bristol.

Mortgage lending policy briefing (PDF , 1,097kb)

Mortgage lending full report (PDF , 2,510kb)

Funder

Funded by the Nuffield Foundation

Timescales

The project runs from January 2022 to December 2023

Project Lead

Dr Alison Wallace

Blogs

This blog for the Red Foundation outlines early findings from our research into the use of new data sources and automation relating to access to housing. Here we outline the use of Open Banking technology where prospective tenants are asked to give permission to access the transactions in their current account. We reflect on the issues this raises for accessing a home.

You are your transactional data: Open Banking in tenant referencing

Algorithmic Dwelling Symposium

The Bristol and York Code Encounters team hosted the Algorithmic Dwelling Symposium in January 2023 at the University of York campus.

This highly successful day brought together a range of scholars working in this area, covering how data is produced, how we engage with algorithms in various life encounters and the potential and limitations of these data and technologies for housing and other services.