Platforming landlords: A critical trend analysis of rental housing technology in Australia and beyond

Abstract

This article advances a critical analysis of digital technologies in rental housing by drawing out five trends in the Australian ‘RentTech’ market and placing them in direct relation with shared political-economic imperatives that transcend borders and underpins the development of rental technologies around the world. By situating Australian examples within a wider context, we draw connections across seemingly disparate dynamics. We show how service integration across the value chain (Trend 1) leverages rentier models to accumulate data rents (Trend 2), which facilitates value extraction from rental assets (Trend 3) and supports risk management imperatives through moral evaluation of renters (Trend 4), all of which are in service of consolidation in the private rental market (Trend 5). Together, these interlocking dynamics describe how RentTech is both responding to housing financialisation and shared logics of property and data assetisation, while also actively shaping its future direction. Our aim is to analyse patterns that exist within and across markets for RentTech to better understand how this sector is developing in different global and national contexts. We conclude by arguing that there are key points of convergence between international markets and shared imperatives that inform the current state and trajectory of technologies in rental housing.

Introduction

Digital technologies are reconfiguring the private rental sector. On the demand side, access to housing is now mediated by real estate platforms. Renters must be legible to – and evaluated by – digital intermediaries to become and remain housed (Wolifson et al., 2024). On the supply side, real estate technologies exert influence on housing markets as they both respond to processes of housing assetisation by large financial institutions (Shaw, 2020; Rogers et al., 2019) and contribute to the further expansion of housing financialisation (Adkins et al., 2020; Fields, 2022). The digitisation of residential real estate can be used to manage and control renters and properties (Ferreri & Sanyal, 2022; McElroy & Vergerio, 2022), serve the socio-economic interests of property owners while further disadvantaging renters (Nethercote, 2023a; Rogers et al., 2024) and accelerate discriminatory practices in housing application selection and tenancy (Wolifson et al., 2024; Przedetsky, 2024).

The ‘RentTech’ sector is booming around the world – renters interact with it, knowingly or unknowingly, at every stage of their housing experience, while landlords and property managers depend on a sprawling market of platforms that help manage and maximise the value chain for private rental housing. In the Australian RentTech market, which is the focus of our analysis, digital intermediaries include online listing sites (e.g., realestate.com.au; domain.com.au), online application platforms (e.g., 2Apply; Ignite), some with tenant risk evaluation and algorithmic ‘matching’ processes (e.g., Snug; Cubbi), digitised rental property management (e.g., Kolmeo; RentBetter), rent payment apps (e.g., Ailo; Managed) and rewards systems (e.g., RentalRewards; Occubuy). Several companies seek to capture the whole renting cycle, offering digital products for the entire process (e.g., Sorted). There are also many enterprise products on the market used by real estate agencies to manage client data, automate workflows and extract insights (e.g., PropertyMe, Our Property, PropertyTree).

As RentTech grows in size and influence, there is a corresponding growth in critical attention by scholars, journalists and regulators. This work tends to focus on high-profile cases of corporate practices and technical systems leading to terrible consequences, with many examples concentrated in the United States. For instance, McElroy and Vergerio (2022) found that increasing deployment of biometric surveillance technologies such as facial recognition in New York City rental housing has accelerated gentrification by creating justifications for landlords to evict ‘undesirable’ tenants.

Meanwhile, rental pricing platform RealPage has come under fire by federal regulators in the United States for using software to set rental prices for properties, effectively engaging in algorithmic collusion that drives rents up (Fry, 2024) and denies rental homes to people based on faulty algorithms (Kirchner & Goldstein, 2020). Analysis conducted by the White House Council of Economic Advisors found anticompetitive algorithmic pricing cost renters an estimated $3.8 billion USD in 2023 alone (White House, 2024).

These critical studies and legal actions are incredibly valuable for shining light on specific practices that exemplify the motivations and consequences of the RentTech sector. Yet there is also a need for further analysis that takes a broader view of the market and its interlocking dynamics. This work can help situate specific cases in a wider context and draw connections across seemingly disparate themes, such as showing how the integration of enterprise services is linked to practices of judging the moral worth of renters, which is then connected to systems of risk management and assetisation by financial institutions. Additionally, broader analysis can direct our attention to patterns that exist within and across markets for RentTech outside of the United States, thus giving us a better understanding of how this sector is developing in different national and global contexts. This comparative work can also illuminate whether particular case studies are unique to their local setting or are indicative of larger trends.

To that end, we conducted a market analysis of the Australian RentTech sector – situating it within the local context of private rental housing in Australia – to better understand the contours and trajectory of this large, active and growing sector for digital technology services. Based on mapping the landscape of the Australian RentTech market, we derived five major trends that represent important dynamics and imperatives within the Australian RentTech sector, and show how these trends directly relate to patterns and phenomena elsewhere in the world. Large financial institutions operate transnationally, investment capital for both real estate and tech startups easily flows across borders, international networks such as industry conferences and major consultancies facilitate shared business practices, and successful strategies in one market tend to be quickly copied, localised and deployed in other markets around the world. Our broader aim is to illuminate key points of convergence across markets and shared imperatives that inform the current state and future direction of technologies in rental housing.

The five trends we explore are not intended to be a totally comprehensive view of the entire market, but rather a way to locate Australia within a global shift towards digitised housing provision. There are surely other themes that could be drawn out of a market analysis with different goals and positions in relation to the industry, but the ones offered here provide a critical vantage point for seeing how RentTech is developing in Australia. The trends outlined below are not independent nor siloed in practice, rather they overlap and bleed into each other as the practices exemplified by one trend compound and are reinforced by those of other trends. The distinctions we make are analytical constructs that allow us to focus on specific, interlocking dynamics.

The next section situates our work in the context of the Australian private rental market and literature on the political-economy of RentTech. We then outline our methods for studying the RentTech market and deriving our five trends. The sections exploring each trend follow the same structure: we describe the trend, then provide examples from the Australian market, then we further analyse the trend by drawing connections to the broader context, dynamics and literature outside of Australia. Trend 1 focuses on market emphasis on service integration rather than disruption, whereby RentTech companies are more interested in bolstering existing practices within real estate businesses rather than fundamentally challenging current market dynamics. Trend 2 highlights how RentTech is creating ways to systematise data generation and collection by embedding themselves as necessary intermediaries. Trend 3 explores how RentTech ‘sweats’ rental assets – that is, how it enables the extraction of additional value from rental assets that are already in place. Trend 4 links these processes to digitised practices of valuation and selection of prospective tenants, who are framed in terms of moral and market worth. Finally, Trend 5 focuses on how RentTech facilitates and benefits from consolidation in the market. We conclude by considering how these trends fit together, and arguing that they highlight key points of convergence across international markets.

Australian market context

In the United States and United Kingdom, a significant amount of RentTech development has occurred as part of the rise in institutional investment in rental housing markets from ‘global corporate landlords’ such as hedge funds, private equity firms, real estate investment trusts and publicly listed real estate firms (Beswick et al., 2016; Nethercote, 2024). These highly capitalised investors depend on digital infrastructure to consolidate and automate core functions of large-scale property management, such as tenancy applications, rent collection and maintenance requests (Fields, 2022; McElroy & Vergerio, 2022; Nethercote, 2023a). Much of the research on the urban political economy of RentTech has focused on exploring how RentTech has emerged as digital enablers and service providers for large financial institutions. There are exceptions, of course – and in our analysis of the five trends we build on the growing body of work on proptech / RentTech in Australia – but most of the literature is based in this context of corporate landlords and late-stage financialisation.

Unlike these locations, Australia's private rental market is characterised by small-scale individual investors, often referred to as ‘mum and dad landlords’, who might only have two or three rental properties and engage a real estate agent as a managing intermediary (Beer, 1999; Hulse et al., 2020). These are significantly smaller-scale operations compared to institutional investors that own entire apartment buildings or have thousands of single-family rental homes in their portfolios of assets. This means digital technologies in Australia's private rental sector are more commonly deployed by real estate agencies, rather than by individual or corporate landlords (Maalsen et al., 2026). There are some exceptions to this, such as the subset of products designed to enable landlords to self-manage their rental properties without engaging a traditional real estate agent (e.g., Cubbi; RentBetter; Renting Smart), with approximately 25% of individual landlords opting to self-manage rather than outsource property management (Hulse et al., 2018; RentBetter, n.d.).

There is also a nascent Australian ‘Build-to-Rent’ (BTR) sector in which corporate landlords develop and use bespoke tech products such as resident apps and incorporate ‘smart’ devices into architectural design (Nethercote, 2020). While the United States and Canada have more mature BTR sectors, and other anglophone liberal regimes such as the United Kingdom and Ireland are experiencing rapid expansion, Australia has, to date, not kept pace with these international trends (for a detailed look at BTR see Nethercote, 2020). As of 2024, less than 4000 BTR apartments operated in Australia (Real Estate Institute of Australia, 2024). Overall, the private rental sector is the fastest-growing segment of the Australian housing market (Hulse et al., 2018).

Against the backdrop of declining home ownership and a rising proportion of private renters, rental property management has taken on increased importance in the real estate industry. In the past, rental properties were perceived as lower value to real estate businesses compared to house sales. However, according to interviews conducted with real estate professionals, the ‘rent roll’ – the list of rental properties under management by an agency, including information about tenants, lease agreements and rental income – is now seen as an important asset class and a form of ‘stable revenue’ that enables agencies to ‘weather the volatility of the housing sales market’ (Hulse et al., 2018). In order to generate the economies of scale required to manage growing rent rolls, real estate agencies are turning to information technologies to reduce costs, outsource functions, automate workflows and ultimately manage more rental properties with fewer staff. It is within this context that the Australian proptech industry has rapidly expanded, seizing upon the opportunity of an estimated AUD$4 billion in annual rental commissions (Davis, 2022).

This creates a somewhat unique landscape of market and policy conditions for the development and implementation of RentTech, which differs in meaningful ways from the United States and United Kingdom. Maalsen et al. (2024) highlight that differences in rental regulations make it challenging to transfer products to Australia from overseas. Instead, the Australian RentTech landscape is dominated by smaller developers simultaneously integrating and competing with each other to provide products and services at every point in the rental cycle. Australian RentTech companies must also navigate an evolving regulatory landscape, with different requirements in residential tenancy legislation in each state and territory, and a varied pace of oversight reforms across jurisdictions. Differences in the Australian housing environment and the corresponding RentTech industry have distinct consequences compared to the forms of corporate landlordism that dominates much of the international proptech literature and thus warrants further attention. At the same time, by focusing our analysis on broader trends, we also show how, despite differences in the landscapes of urban housing, there are shared RentTech logics and imperatives that run across different geographies. In other words, the trends we identify are core features of the broader political-economic system of rentier platform capitalism, which are then differently translated into local contexts.

Method

We derived the following trends through the process of creating and analysing a database of RentTech products and companies that are headquartered in Australia and were operating during 2024. Based on extensive desk research, the first author collated 60 entries, with each being a different RentTech product in the market. Each entry contained information including headquarter location, a description of product features, the primary user (e.g., renters, agents or landlords), types of data collected (if applicable or available), samples of marketing language as well as other notes, quotes and links about the product that didn’t fit into predefined fields. By connecting head companies, private equity firms and subsidiaries, the database also aims to trace key acquisitions and partnerships to better understand the make-up and concentration of the Australian RentTech sector. We also analysed a large corpus of textual sources from the RentTech industry, including marketing materials, product descriptions, company websites, media reporting, video demos of platform features and online industry panel discussions.

While the broader proptech sector is significantly larger than what is captured in our database – it is estimated there are over 600 proptech businesses operating in Australia (Proptech Australia, n.d.) – our analysis was limited to products and services that directly interact with the rental cycle rather than other segments like property sales. That is, we focused on processes related to entry into a rental agreement (listing, searching and applying for rental properties; tenant assessment and screening; bond payment), living in a rental home (rent payment; property management; communications and maintenance) and exiting from a rental home (moving services; vacancy management). We included products and services whose primary user is the renter, such as web portals and apps for tenants, as well as systems designed to be used by real estate agents and landlords, which the renter may never directly interact with or be aware of. Other products in the broader proptech industry were set aside, although we do acknowledge that many of them have indirect impacts upon the experience and nature of renting. For example, data-driven property valuation and property data analytics (such as PointData and CoreLogic), and fractional investment platforms (such as BrickX and Bricklet) were excluded for the purpose of this analysis.

Trend 1 – ‘Every tool you need, under one roof’: integrating services across the rental value chain

Contrary to typical narratives of disruption in the tech sector – where the business models of start-ups are based on displacing incumbents in an industry via tactics focused on software applications and aggressive expansion – the RentTech market in Australia is better characterised by integration and coordination. Instead of digital platforms seeking to undermine major real estate agencies, what we see is myriad smaller vendors selling a multitude of digital services to big real estate agency players, with each service focused on specific parts of the rental business. We find RentTech start-ups attempting to innovate at every step of the rental cycle – from tenant screening to portfolio management – often with the goal of partnering with larger companies that operate across the value chain. Established real estate companies in the industry tend to integrate services from many vendors into their operations. RentTech start-ups are more likely to be in competition with each other than with major incumbents in the rental market. At the same time, these smaller companies partner with each other as a strategy to be more competitive in a market dominated by high levels of consolidation by proptech giants in Australia like REA Group. This is a point of difference compared to many other sectors of the tech industry, which are often more interested in unsettling established industry norms and practices, rather than creating a sprawling vendor ecosystem of B2B SaaS ¹ that facilitates incumbents like we see in Australia.

However, this process of integration is not always seamless and services do not always neatly fit together, especially in cases where a company is contracted with multiple vendors for different parts of their operations. This dynamic has given rise to companies such as Bricks + Agent and PropertyMe that seek to coordinate a range of services on one platform, thus addressing problems of interoperability and usability that arise from working with too many vendors. Bricks + Agent and PropertyMe both boast that they have partnered with dozens of other service providers – or, in industry parlance, they have ‘deep integration’. These coordinators use language like ‘every tool you need, under one roof’ (AgentBox, n.d.), which emphasises their value-add as a one-stop shop for any solution to any problem, while also representing their goal of capturing more of the rental value chain and bringing it onto their platform. These are enterprise systems; their customers are other businesses, not renters. This quote from AgentBox (owned by Reapit), a client relations management software suite, is a typical example of their marketing: ‘Experience the power of a complete solution, right out of the box. Supercharge your agency with cutting-edge automation, unrivalled client engagement and advanced prospecting tools – the trifecta for industry excellence’.

These coordinating platforms are marketed as more convenient because they bring together services and disparate flows of data. The integration of services into incumbent operations on unified platforms raises serious questions about data collection, aggregation, the development of individualised tenant profiles and information sharing agreements between different companies. These questions are largely unanswered thanks to a lack of scrutiny, low levels of transparency into industry practices and loose regulations in the private rental sector (Maalsen et al., 2026). However, consumer research into the tenant experience suggests many renters are uncomfortable with these tools, yet feel they have no choice but to use them (Choice, 2023). This line of analysis is outside the scope of this article, but we focus on renter experiences and the data subjectivities that RentTech engenders in future work currently underway.

The emphasis on integration and coordination in the RentTech sector shows an intention to bolster existing practices within the real estate business, rather than fundamentally challenge current market dynamics. RentTech companies are seeking to embed themselves as necessary intermediaries in long-established rental housing systems. By making RentTech products indispensable and fully intertwined with day-to-day business activities, the RentTech sector is able to shore-up their ongoing value proposition, extend market dominance and ensure influence over the future of real estate.

Crucially, this process of integration lays the foundations for further value extraction as technologies for data generation, automation and risk governance become more sophisticated and companies find more ways to valorise the data they are able to collect – discussed in further detail in Trend 2.

There are, of course, some exceptions that remain committed to the strategy of disruption: short-term rental platforms, flatmate-finding services, tenant bond loans and insurance products purport to disrupt aspects of the private rental sector (Maalsen, 2023; Rogers et al., 2024). We also found disruptive logic and rhetoric in our analysis of the subset of RentTech products designed to enable individual landlords to self-manage their rental properties without engaging a real estate agent. RentBetter (n.d.) describes itself as ‘a leading disruptor in the Australian residential real estate market’, which they pitch as ‘a better way (to rent your property)’. RentingSmart (n.d.) likewise implores landlords to ‘Ditch the real estate agent. Be a smarter investor’. However, self-management of rental properties remains a small proportion of landlords in Australia (Hulse et al., 2018).

In this sense, the value proposition of the majority of Australian RentTech to the real estate industry is to integrate disparate and often labourious processes, to increase efficiency and profitability in the real estate business. Meanwhile, RentTech is able to generate value from existing dynamics in the real estate sector in two key ways: (1) by extracting platform rents from other players in the real estate industry who increasingly rely upon their technology services as they become further integrated and the market continues to consolidate; and (2) by always looking for data creation and valorisation opportunities to generate new forms of revenue into the future. Prioritising integration over outright disruption is a strategy that aligns with the rentier model, in which the platform makes itself a necessary intermediary in the circuits of production, consumption and accumulation that drive capitalism (Sadowski, 2025).

While the figure of the rentier may differ as rentier activities expand and evolve beyond landed property, digital platforms – including RentTech – nonetheless uphold rentier dynamics (Rogers et al., 2024). Unlike developing wholly new approaches, ‘innovation as rentiership’ is characterised by the extraction and capture of value through ownership and control over assets (Birch et al., 2020). RentTech is both responding to and benefiting from assetisation of housing by facilitating landed rent extraction, while valorising rent data as an asset class itself. Such a model is not unique to Australia, rather, this trend represents a local translation of a broader political-economic system of rentier platform capitalism. It also shows how RentTech in Australia reflects a commitment to the political process of turning things into assets to consolidate ‘assetisation power’ (Birch & Muniesa, 2020: 185). Pushing back against the hype of technological disruption in global property markets, Faxon et al. (2024: 450) observe that ‘new technologies have not fundamentally challenged the prevailing political economy of land and real estate; instead, they often reinforce existing exclusions and benefit the powerful’. Rather than disrupting established market dynamics, this trend reveals how RentTech is overwhelmingly more interested in securing a seat at the table and carving off its own slice of the pie.

Trend 2 – ‘Automate your work like magic’: minimising touchpoints and creating data points

Many firms in the Australian RentTech market seek to automate and minimise interactions or ‘touch points’ between agents, landlords, tenants and other contractors, while at the same time transforming each interaction into a data point. In doing so, RentTech is creating ways to systematise data generation, collection and analysis on renters, workers and property that have previously been uncollected or otherwise less readily able to be analysed and operationalised. Given that most RentTech companies do not control or derive income directly from ownership of material assets (landed property), this data imperative (Fourcade & Healy, 2017; Schildt, 2020) operates in tandem with efforts to extract platform rents by positioning themselves as necessary intermediaries in established real estate businesses (see Trend 1).

There is now considerable critical literature and public attention focused on how renter data is collected and used through online rental application platforms and algorithmic tenant screening (see Przhedetsky, 2024; Short et al., 2008; Floreani, 2022; Convery, 2022, 2023). However, beyond the application stage, there is also a growing segment of RentTech firms seeking to capture, automate and datafy processes associated with ongoing property management once tenants have moved into rental homes. This indicates that, in addition to the information contained within rental applications used to assess and screen potential tenants, the rent data generated throughout the duration of a lease is also of value to RentTech companies, real estate agents and landlords.

For example, Bricks + Agent – a property maintenance platform with a cloud-based marketplace connecting agents with tradespeople – claims each maintenance request involves, on average, 20 touch points, with each property averaging at least two requests annually (PropertyMe, 2020). By overseeing the workflow of tenancy management, Bricks + Agent transforms these touch points into previously unrealised opportunities for data collection, while also claiming to streamline the workload for both agents and tradespeople. In this way, Bricks + Agent is actively creating new data for accumulation, in addition to collating forgotten data. The transformation of touch points to data points is a core part of the value proposition for the all-in-one platforms that aim to integrate and capture the entire rental cycle, such as PropertyMe (‘automate your work like magic’, n.d.) and Sorted (‘streamlines the entire property lifecycle’, n.d.).

In addition to automating communications with tenants, some RentTech firms are also marketing generative AI assistants like Claire, created by Propic, which claims to ‘free up your team from the mundane and focus on the high-value tasks such as growing your business and building stronger relationships with your landlords’ (Propic, n.d.). Interacting with tenants is routinely positioned as a lower-value, labour-intensive and yet necessary task that lends itself well to being automated or ‘streamlined’. This is promoted as a way to reduce the labour of agents (who are frequently framed as overworked and understaffed in industry materials), while also making agents more productive and boosting their ability to scale-up in the market – a related trend we discuss further below. In reality, as McElroy (2024) shows in research on the ‘fictions of frictionless property management’, these technologies offload the labour of property management onto other workers and renters who must now navigate and maintain automated systems that they have no control over.

In addition to powering automation, the data generated through ongoing property management is processed into data-driven insights about properties as financial assets in the broader market. These insights enhance visibility and control of the property for the owner, create avenues for operational gains for real estate agencies and hold potential to generate future income streams through data analytics about the growing rental market (Rogers et al., 2024). Expectations of data valorisation are often based on little more than speculation with no clear pathway towards monetisation, but this shows how the broader imperative in digital capitalism to extract data first and then figure out ways to valorise it later is translated into the real estate market (Sadowski, 2025).

These technologies also act to distance tenants from landlords and agents. This can become a barrier that reinforces or further obfuscates instances of discrimination and poses challenges to renter self-advocacy and agent/landlord accountability by using supposedly objective, data-driven insights to justify decisions such as raising rents or excluding certain tenants (Wolifson et al., 2024). Creating distance can be a deliberate strategy to maximise wealth accumulation; for example, a US-based proptech developer suggested human letting agents had ‘too much empathy’ when determining rent prices, compared to the computer-generated system (Vogell et al., 2022). At its core, the expansion of data-generating technologies into rental housing is a form of digital mediation that simultaneously responds to and expands the commodification and financialisation of housing (Fields, 2022; Shrestha et al., 2023; Wijburg et al., 2018).

These technologies also support systems of risk governance that seek to quantify, predict and minimise risk – to the real estate agency business and the landlord's revenue-generating asset – by finding hidden insights and market advantages in flows of rental data (Ferreri & Sanyal, 2022). Such systems enable more granular oversight and control of workers – both agents and tradespeople – through features such as GPS tracking of workers, logging time taken for tradespeople to complete maintenance tasks and optimising routes between properties. Such worker surveillance is not unique to RentTech, but is rather a shared logic underpinned by a ‘metric theory of automation’ in which techniques used to measure and monitor labour influence the design and purpose of automation systems (Pasquinelli et al., 2024).

As highlighted in Trend 1, RentTech sits within the formulation of the digital platform as new rentiers of contemporary capitalism (Sadowski, 2020), collecting both traditional monetary rents and data rents (Nethercote, 2023). Much of the Australian RentTech sector fulfils the imperative to accumulate and circulate data not just by placing themselves in the middle to passively gather previously uncollected data, but by actively creating opportunities to facilitate the generation of data. This innovation strategy works to secure RentTech's value proposition in a dynamic market: today, they are startups that facilitate rental housing transactions, but tomorrow they are providers (and gatekeepers) of critical data infrastructures and insights for a growing real estate industry. In this way, RentTech contributes to processes of datafication, in which various parts of life are transformed into data (Van Dijck, 2014), as well as processes of transforming that data into an asset class to secure future revenue streams (see Nethercote, 2023; Birch et al., 2021).

The concept of assetisation provides a useful analytical tool to understand how political-economic actors – in this instance, the creators, investors and benefactors of RentTech – transform data into capitalised property through measurement, governance and valuation practices. Assetisation in service of financialisation is not a new logic for capital but these digital technologies ‘extend and empower capital's abilities of assetisation, extraction, and enclosure’ (Sadowski, 2020: 566). While the valorisation of rent data in Australia has not yet reached the same level of sophistication as overseas counterparts or some other areas of the tech sector, there is a demonstrable shared imperative between Australian RentTech companies and international counterparts to do so. Firms in the Australian RentTech market are laying groundwork for future avenues of value extraction from renter data. One possible avenue may be inspired by the likes of YieldStar – rent-setting software offered by US company RealPage – which feeds aggregated rental data into a price optimisation algorithm that drives rent up and generates more profit for property investors through a process that regulators have likened to algorithmic price fixing (US Department of Justice, 2024). Such a thing would not be possible without first creating the infrastructure to accumulate vast quantities of rent data from across the market and establishing yourself as a key intermediary at different ‘touch points’ in the rental cycle – as RentTech companies in Australia have already done. We can already see Australian firms developing their own forms of price optimisation, as discussed in the next trend.

Trend 3 – ‘Always optimal rent’: sweating rental assets

In addition to an imperative to capture as much value as possible from each property, there are also constantly evolving systems in place for making, squeezing, growing and managing value from real estate. Crucial to this process is, what's called in industry terms, ‘sweating assets’ – or, extracting more value from assets that are already in place (e.g., buildings, infrastructure or labour) by exploiting them to a greater degree and/or reducing their cost of operation. RentTech companies promise to help sweat rental assets in two key ways. First is by assisting investors, agents and landlords maximise the value of their rent-bearing assets (i.e., property) through strategies such as optimising the amount of rent produced by assets and reducing the costs of operating said assets (e.g., managing properties) through increased efficiency or cheaper alternatives like automation. Second is by turning the ‘rent roll’ itself into a valuable financial asset. As noted in our introduction, the importance of the ‘rent roll’ and its role in extracting value from housing has increased as more people are renting, and renting for longer periods (Hulse et al., 2018). Rent roll data is used to forecast income, manage risk, value properties and securitise rent flows. One of the key value propositions of many RentTech companies is to provide the tools necessary to manage and exploit a rent roll as it scales up.

We found that the RentTech products most preoccupied with sweating rental assets were those designed for, and promoted to, property investors directly. For example, Cubbi – a self-management platform for landlords – describes its price recommendation service as ‘Always Optimal Rent’, whereby they suggest rental increases and additions to leases like pet bonds with the goal of extracting the ‘highest rent possible’ from tenants (n.d.). Landlord self-management platforms seeking to replace real estate agents often play into tensions between agents and landlords, with the latter being distrustful of the former's care and attention when managing their property. For instance, Managed (n.d.) – an automated rent payment platform – directs their marketing towards landlords by playing on a sense of distrust: ‘a bad agent has access to rental funds and while it's impossible to know who is a good or bad agent, your funds are accessible’. Likewise, RentingSmart (n.d.) says: ‘Real estate agents are often too busy to manage your property as closely as you can. When you self-manage, you’ll have all the information at your fingertips’, while Cubbi (n.d.) claims that one-third of owners are frustrated with their agent, emphasising that ‘sloppy management is hard to see until it's too late’.

Such RentTech products also promise to sweat rental assets by cutting out the costs to a landlord's income that come with outsourcing work to agents. RentBetter (n.d.) promotes their product as a way to save an average of $2k per annum, per property; ‘Say goodbye to expensive property management fees!’ At the same time, enterprise RentTech products that are designed for and promoted to real estate businesses also aim to sweat rental assets, only they primarily do so by promising to lower existing costs of managing rental properties and scaling the rent roll. Console (n.d.), for example, exhorts agents to ‘drive rent roll growth through smart automation’. Likewise, PropertyMe (n.d.) frames the benefits of their property management platform as ‘reduced costs:…saving you thousands in hardware and labour costs alone’ and ‘scalability: the automated solutions…mean you’ll have plenty of time to focus on growing your rent roll’. These examples demonstrate how the analytical trends we have identified play, in practice, mutually reinforcing roles in both defining and driving how the RentTech market develops. The most popular firms like PropertyMe tend to operate as platforms that pull together multiple trends in the market, thus showing how service integration (Trend 1) and automated data-driven solutions (Trend 2) can be marshalled toward sweating rental assets (Trend 3) and managing tenant risk (Trend 4), which all contribute to further growth in the market (Trend 5).

To that point, the imperative to sweat rental assets interacts with, and further intensifies, the moral economy of renting, which we discuss in detail in the next section. Many RentTech products – both those designed for self-managing landlords and real estate businesses alike – promote data-driven tools for discerning ‘good’ tenants who will treat the property like it is their own house. The idea is that by finding a tenant who is a good steward of the asset, depreciation of value can be minimised through minimal wear and tear – and may even facilitate asset appreciation by tenants making improvements to the property. In this way, both the landlord and real estate agent can continue to sweat the rental asset into the long term. Cubbi (n.d.) claims that ‘if you choose the right tenant, the ongoing management should only take you around 7h per year’. Many RentTech companies provide features such as landlord-facing dashboards or mobile apps in addition to agent-facing functionality. These are framed (to landlords and agencies alike) as a way for landlords to have on-demand access to greater granular detail, control and the ability to proactively monitor their property and the tenants.

Ultimately, regardless of whether the product is designed to enable landlords to self-manage their investments or centred on empowering established real estate businesses, the majority of RentTech products share the same sweaty goals: maximise the asset's value and minimise the asset's cost. While their methods might depend on (slightly) different forms of digital platforms, tenant screening and workflow automation, as a whole RentTech companies pitch their technological services as ways to turn underutilised resources into maximally productive assets and to unlock latent value of existing spaces. Hence, RentTech intensifies the logics of financialisation and processes of assetisation that are carried out by a professional class of managers (Adkins et al., 2020; Fields, 2022; Nethercote, 2023a).

This dynamic is already present in housing contexts such as the United States, where a significant proportion of private rental housing is owned and/or managed by large corporate landlords like private equity firms (Desilver, 2021). As highlighted by Fields (2022), the expansion of financialisation in the US housing market was made possible by the post-2008 crisis market conditions; however, it was information technologies that played a crucial role in actually turning rental homes into a ‘new financial asset for the post-crisis era’ by giving investors the ability to manage, grow and sweat their portfolios of rental assets (Fields, 2022: 162). The Australian RentTech sector, while still emerging, has internalised broader logics in the global proptech sector that understands that tools for optimisation, automation and asset management are integral to not only complement pre-existing processes of assetisation in housing but also to sweat those assets and achieve ‘always optimal rent’.

Trend 4 – ‘Reduce the chance of a bad tenant by 9x’: expanding the moral economy of renters

In societies focused on promoting home ownership and property market growth such as Australia, renters are framed in terms of risk. Because some renters are understood to be riskier than others, property investors seeking to maximise value are incentivised to identify ‘good’ tenants – often framed in terms of ‘ability to pay’ and ‘ability to care’ for the investor's asset (Power and Gillon, 2022;Maalsen et al., 2024). Real estate agents and landlords employ a variety of strategies and practices when assessing and managing risks (real and imagined) associated with tenants (Short et al., 2008; Beer et al., 2023). Risk classification and moral valuation of renters are most evident at the point of tenant selection when agents and landlords are deciding which applicant is worthy of being a tenant in their property (Azevedo et al., 2024). Tenant selection is determined through combinations of factors including income, rental history and references from employers and previous agents, as well as proxy markers of risk including class, age, race, gender, household type, employment type and welfare/disability status, plus other discretionary factors such as tattoos and social media activity (Bate, 2020; Kelly, 2023; Power & Gillon, 2022). While the practice of categorising renters according to perceptions of risk and morality is long established (Ferrari & Sanyal, 2022), RentTech is further entrenching, expanding and exploiting the moral economy of renting. These technologies are being integrated into the rental application and assessment process, directly impacting tenant selection and rental housing access by organising applicants based on their data (Migozzi, 2024; Przhedetsky, 2024).

We found a dominant throughline present in Australian RentTech marketing language that frames renters in terms of both their moral worth and market value. Promotional material directed towards landlords and real estate agents explicitly asserts a need to identify and sort the ‘good’ renters from the ‘bad’ to maximise rental payment returns and minimise risk to the investor's asset. For example, Cubbi (n.d.) overtly classifies ‘Good Tenants vs Bad Tenants’ and claims to be able to ‘reduce the chance of a bad tenant by 9x’ while also promising landlords to ‘help you get the best renters at the highest rent possible’. Another company, 10ant Profiles (n.d.) – a tenant screening service based on a psychometric questionnaire – claims to perform objective personality assessments to provide a ‘tenant safety score’ based on a selection of proprietary risk indicators. This is promoted in a featured testimonial on the company's website as a way to support the gut instinct of property managers. As one agent said, ‘I felt good about these applicants, although I couldn’t honestly say that I would have recommended them to the owners if the 10ant results didn’t back my thoughts’ (10ant Profiles, 2021).

These forms of scoring and profiling are framed as ways of identifying hidden truths about what types of renters (generally) and which individual applicants (specifically) are the least risky and thus deserve to live in the landlord's investment property.

Even RentTech positioned as designed to serve the interest of renters reflects this moral economy. The real estate platform Rent.com.au (n.d.) – which states its mission is to empower renters through technology – asks: ‘are you shown as a good tenant?’ and prompts renters to pay for their own (optional) background and National Tenancy Database checks to ‘present you as a trusted, quality tenant’. Similarly, rental application platform 2Apply (n.d.) encourages applicants to pay for a database check to ‘show you’re a great tenant’. Meanwhile, a different application platform, Snug (n.d.), proclaims their platform ‘helps renters shine and Be the Best You’. Snug gives each applicant a ‘match score’ based on profile completion and how well it aligns with the landlord's preferences. The company has previously been accused of incentivising renters to ‘rent bid’ when applying for homes as a way to increase their score compared to other applicants (Convery, 2022). By the logic of many RentTech firms, the best way to prove your worth and mitigate your risk in the property market is by showing your value as a tenant who will pay more for rent and add-ons like background checks.

In this way, RentTech companies are both deepening and profiting from the moral economy of renting, which in turn serves to shore up their own value proposition in a growing market. RentTech companies sell their customers the promise to assess, predict and mitigate the legal and financial risks associated with a ‘bad’ tenant. Their tenant screening technologies claim to make these evaluative decisions both quicker and easier, however the ways renter data is used to organise, select and reject applicants is often unclear and unexplained – made worse by proprietary algorithms. Przhedetsky (2024) differentiates between systems that ‘screen’ tenants by filtering out ‘unsuitable’ candidates according to some predefined threshold or characteristic (e.g., whether they have a pet) to create a smaller pool of applicants, and those that ‘sort’ tenants by scoring, rating or ranking them based on a weighted analysis of application data according to algorithmic logics (e.g., highly ranking applicants who offer more rent).

These technologies can provide a veneer of data-driven objectivity for decision-making, thus making rental housing allocation appear as a neutral and fair process, while masking the underlying political-economic imperatives that drive decisions (Boeing et al., 2021). It is well established that algorithmic decision-making often reproduces pre-existing inequalities (Eubanks, 2018). The broader context for such measurement and classification of individuals is described as ‘the ordinal society’ by Fourcade and Healy (2024). As they note, ‘even when the data is bad, or the analytical results are spurious, the outcome is a form of rationalized stratification’ (Fourcade & Healy, 2024: 7). Several scholars have investigated how techno-politics translate into digital systems for tenant screening, leading to unfair and discriminatory outcomes and reinforcing exclusionary logics and socio-spatial hierarchies in housing across different contexts (Fields, 2022; McElroy, 2023; Humber, 2023; Reosti, 2020; Migozzi, 2024; Przhedetsky, 2024; Wolifson et al., 2024; So, 2023). For example, Rosen et al. (2021) found that landlords in the United States attempt to predict the future performance of a tenant through two proxies: algorithmic analysis and ‘gut instinct’, both of which have complex intersections with race, gender and class that lead to direct consequences for housing access. These dynamics are particularly notable in economies that are experiencing housing crises, as is the case in Australia, which create an extremely tight private market and push renters to compete with each other. RentTech takes advantage of these market conditions by acting as yet another intermediary that can help landlords and agents exert finer control over renters – who have few options, but to comply – and thus mitigate perceived risks to the returns on their financial assets.

Elsewhere, the rise of ‘tenant passports’ – a consolidated digital profile including factors such as rent payment history, credit data and identity checks – is becoming increasingly central to how renters go beyond ‘performing the Good Tenant’ (Power and Gillon, 2022) to meeting the characteristics of an ideal tenant (Azevedo et al., 2024). Azevedo et al. (2024) highlight how renters in Vienna leverage the ‘KSV InfoPass’ system to gain a competitive edge. Wallace et al. (2025) suggest tenant passports in the United Kingdom could increase transparency by providing tenants the opportunity to see and control data shared with agents and landlords, however, they may also inadvertently deepen inequalities by benefiting more affluent renters while marginalising others, in turn reinforcing spatial sorting. Relatedly, Ciocănel et al. (2024) have raised concerns regarding exclusionary tenant screening and use of ‘open banking’ for financial assessments of tenants. Tenant passports are not currently in use in Australia, however open banking functionality of Australia's ‘Consumer Data Right’ – which enables bank customers the ability to provide access to their data to third parties – alongside housing advocates calls for a standardised rental application process provides groundwork for the development of tenant passports in the future, with potential to add another layer to financial and moral tenant classification systems.

Trend 5 – ‘Turbocharge your growth’: consolidating control and scaling the market

RentTech plays an important role in how the real estate industry is consolidating, including how companies scale their portfolios of rental properties under management. In order to generate the economies of scale required to manage growing rent rolls, real estate agencies are turning to information technologies to reduce costs, outsource functions, automate workflows and ultimately manage more rental properties. The tools and logics provided by the RentTech market enable the real estate industry to increase how many properties a single firm can manage – and scale the amount of value (both money and data) that can be captured from each property and across the whole value chain. Similarly, to tech start-ups in other sectors, the emerging RentTech industry has financial incentives to scale their businesses at rapid and exponential rates.

RentTech facilitates this scaling by offering solutions that minimise effort and maximise returns for both real estate agencies and landlords, typically through forms of optimisation that allow agencies to manage more properties with less staff by reducing inefficiency and automating as much as possible (see Trend 2). For example, property management software company, SimpleRent (n.d.), claims to help agents ‘Turbocharge your growth while minimizing your workload with our easy-to-use property management lease and payment software’. Meanwhile, companies such as Property Tree, Bricks + Agent, Maintenance Plus and many others claim to, in the words of Inspect Real Estate (n.d.), ‘take the hassle out of tenant communications’ by automating processes such as inspection scheduling, maintenance requests, rent payments and much more. In terms of consolidation, large companies such as REA Group (majority owned by News Corp), Domain Group (currently majority owned by Nine Entertainment but under a binding Scheme Implementation Deed to transfer ownership to US-based company, Costar Group) and Reapit (backed by private equity firm Accel-KKR) – as well as smaller companies such as Proptech Labs, Snug and Rent.com.au – have been rapidly growing through either acquiring companies or creating services that operate in different areas of the market. At the same time, the types of coordination platforms outlined in Trend 1 are helping consolidate the market by bringing various services into one vertically integrated interface.

The buying and selling of rent rolls is a key method of consolidation in the real estate sector. When a real estate agency acquires a rent roll, not only does it acquire the company's portfolio of properties under management but also increases the data about the properties and tenants that a firm possesses (Rogers et al., 2024). In addition to buying rent rolls, larger real estate businesses are also more interested in developing or supporting the development of software to create, maintain and consolidate rent rolls. By providing the tools to more efficiently digitise, grow and manage the rent roll, RentTech facilitates growth and consolidation in the real estate industry by making it easier for firms to expand their portfolios and market positions. In turn, this growth increases consolidation within the RentTech sector as companies control access to significant information and produce valuable products and analytics from that data.

Since the majority of RentTech companies are interested in integrating with established business practices (see Trend 1), large real estate industry players wield disproportionate influence in shaping the RentTech market's landscape and trajectory. This aligns with what Rogers et al. (2024: 10) describe as a form of ‘proptech asset control’ by large real estate companies, which typically falls into three types: buying ready-made proptech products, partnering with a proptech company or designing and building proptech in-house to meet their specific needs. Crucially, market dominance by RentTech firms is not built upon ownership of material property but is instead built upon consolidated ownership and control over data-as-capital (Sadowski, 2019). As the data assets grow in size and value, the market power of key industry players in real estate and RentTech who control that data also grows and consolidates.

Unlike the United States and the United Kingdom, Australia's real estate market is not yet punctuated by financial institutions and institutional investors that buy, build and manage massive portfolios of (rental) properties. However, existing trends in the Australian RentTech market can be seen as more than just a reflection of the growing importance of the ‘rent roll’ as an asset class but also as a way to lay the groundwork necessary for future hyper-growth by providing the digital infrastructure and financial incentives that help facilitate the acquisition and management of larger portfolios of assets, as was necessary for expansion of financialisation in the US housing market (Fields, 2022). Likewise, Migozzi (2024: 549) highlights how automated tenant screening platforms in South Africa ‘enabled the consolidation of the private rental sector and the emergence of corporate landlords’ by further empowering institutional real estate investors to turn rental housing into a new asset class. The moral economy of renting and imperatives to use data to organise and value tenants according to metrics of risk and profit (as outlined in Trend 4 above) directly relates to the ability to further concentrate the market.

Notably, many RentTech firms provide a sliding scale for their pricing with options that go into the thousands of properties under management. This likely exceeds the needs of current residential real estate agencies, most of which have a turnover of less than $3 million per annum (Real Estate Institute of Australia, 2023), but it shows they are willing, ready and able to service the demands of large institutional landlords when the time comes. Assets are anchors for financialisation processes (Birch, 2017), and financialisation dynamics are typified by BTR because assets, unlike commodities, must be retained in order to extract ongoing value (Nethercote, 2023b). Perhaps looking to overseas counterparts for inspiration, the Australian government has created policy incentives for institutional investment in private rental housing through BTR. As Nethercote (2023b) notes, Australia has been primed for BTR market emergence. While there are many factors contributing to this, the ability for investors to scale quickly and manage large numbers of rental assets will rely on digital technologies. As such, RentTech is both responding to the shifting dynamics that increase the value of rental housing as an asset as more people rent and rent for longer, while also laying the groundwork necessary to prepare for (and usher in) new investment, development and institutional consolidation in the Australian private rental market.

Conclusion

In recent years, there has been growing recognition of the centrality of housing to the political economy of advanced capitalist societies, with some scholars insisting that political-economic analysis must take housing seriously (Aalbers & Christophers, 2014). Given that housing is a ‘crucial vector’ of social inequality and ‘contentious power dynamics’, understanding the impact of digital technologies on housing demands attention (Fields and Rogers, 2021: 3). The technological transformations of housing – including the forms of RentTech we have discussed in this article – are part of a ‘crucial terrain of struggles over housing's place in contemporary capitalism’ (Fields, 2022: 162). This is especially relevant within the context of financialised and rentier capitalism, that is, capitalism that ‘seeks to profit from rent rather than from direct productive activity’ (Christophers, 2010: 106). In this article, we have aimed to position the emerging RentTech sector and its implications for rental housing within this broader context.

Crucially, the RentTech products we have examined and the interlocking trends we have drawn out are interested in not just unlocking value from the rental home as an asset but also capturing and valorising the data that is generated from all of the processes associated with living in a rental home. The emerging RentTech sector seeks to combine and control these two assets – housing and data – in ways that further extract value and concentrate power of both. By drawing out the five trends discussed above, we have demonstrated how these market dynamics play, in practice, mutually reinforcing roles in defining and driving how the digital technologies in rental housing are developing. The most successful firms – and the ones that hold the most power – pull together all of these trends, showing how service integration (Trend 1) and automated data-driven solutions (Trend 2) can be leveraged to sweat rental assets (Trend 3) and manage tenant risk (Trend 4), all of which contribute to further growth and consolidation in the market (Trend 5). While our analysis has largely focused on cases born in Australia, positioning this in relation to shared underlying logics and imperatives demonstrates that patterns exist between markets for RentTech, which allows us to better understand how the sector is developing in different global contexts. This lays important groundwork for further comparative analysis of how these market trends and technological transformations are playing out across different political economies of rental housing.