The real estate industry has reached an inflection point. While property technology (PropTech) has long targeted efficiency improvements, robotic process automation (RPA) now enables a digital transformation touching all parts of the sector.
RPA allows configuring software robots to carry out repetitive, manually intensive tasks relying on existing IT systems. By automatically handling high-volume, mundane work, RPA liberates employees to focus on higher-value responsibilities.
Leading real estate enterprises are already utilizing RPA with profound impacts…
Benefits of Applying RPA in Real Estate
RPA delivers manifold benefits when deployed for real estate processes:
Improved Efficiency and Productivity
By automating repetitive tasks, RPA reduces manual workloads for employees. Software robots operate around the clock without fatigue. This results in higher throughput, shorter cycle times, and massive productivity gains.
As one example, CBRE automated the processing of 40,000 annual appraisals – cutting time per report from 2 hours to just 4 minutes. Such efficiency improvements free up employee time for judgment-intensive work.
Forrester Research estimates that RPA drives productivity gains between 200-300%. A Deloitte study found 86% of early RPA adopters in real estate got over 15% in improved efficiency. As processes reach scale, net productivity can double or triple.
Cost Savings
With streamlined operations and fewer employees needed for routine tasks, RPA drives considerable cost reduction. Gartner estimates cost savings between 25-50% for initial RPA projects, with peak cost reduction potential over 65%.
Savings may multiply when RPA is integrated across real estate platforms like ERP, CRM, and document management. Large real estate enterprises can save millions of dollars at scale. JLL reportedly saved $10 million over 2 years via RPA optimization of service charge processing and accounting tasks.
Per RPA vendor UIPath, typical 2-3 year ROIs range from 200-300% as the automation cost is recovered rapidly from efficiency gains and headcount reduction. Expanding RPA usage fosters a multiplier effect on savings.
Enhanced Customer Experience
RPA also provides indirect savings from improved customer satisfaction. Consistently fast turnaround on requests like rental applications or mortgage processing yields higher renewal and referral rates.
Software robots facilitate 24/7 availability too. Customers can securely check a property listing or loan application anytime – accelerating their journey. This drives more qualified leads and faster deal completion.
As per ServiceNow, RPA enabled response times reduced 12x across one real estate enterprise – translating to higher customer retention. Moreover, bot-driven consistency cuts application fall-off that happens from manual errors.
Increased Compliance and Auditability
With detailed activity logging, RPA results in higher transparency than manual processes. The technology enforces standardized protocols consistently – ensuring stricter regulatory compliance.
Detailed audit trails satisfy external oversight while minimizing compliance costs. RPA thereby enables reliably achieving compliance at scale. One large financial services company saved over $2 million in just audit support costs after RPA deployment.
Use Cases: How RPA is Transforming Real Estate Processes
RPA is applicable across diverse real estate subsectors. Some exemplary use cases where RPA has delivered major efficiency gains include:
Automating Leasing Processes
Tasks like rental applications, background checks, lease generation and rent collection involve many repetitive steps. RPA can ingest applicant details, connect to screening databases, auto-populate leasing contracts and process payments – with minimal human review required.
Knight Frank automated the entire tenant acquisition process using RPA, saving 10,000 operational hours annually. Average cycle time for credit checks, documentation and approval declined from 2 days to 2 hours.
Streamlining Property Management Workflows
From work order creation to rent collection and accounting reconciliation, property managers handle high volumes of repetitive tasks. RPA helps schedule maintenance calls automatically, allocate payments and match statements – enabling managers to oversee more properties.
An anonymous case study quotes a real estate firm that utilized RPA to manage double the properties with the same staff, allowing expansion to newer geographies without proportional headcount growth.
Assisting Valuers and Appraisers
The research heavy and repetitive process of collecting comparable property insights is ideal for RPA. Automated data aggregation from MLS records and market reports allows appraisers to focus solely on valuation analysis – slashing turnaround times.
RPA bots can extract historical sales values, zoning details, geospatial metrics etc. to feed into pricing models. One MLP provider notes that leveraging RPA yielded a 20% higher appraisal throughput for its valuation team.
Supporting Financing and Mortgages
Bot-driven automation assists homebuyers through the mortgage journey. Software robots can extract data from loan applications, validate assets/income, assign risk ratings, generate approval paperwork and so on – reducing fallout from manual errors.
The Federal Home Loan Mortgage Corporation achieved $3 million in cost savings using RPA for quality control and loan eligibility checks. What took 3 FTE earlier was reduced to a half-day of software robot effort resulting in lower operating costs and pricing.
Emerging Use Cases in Property Development, Investment and Transactions
While RPA has demonstrated value in property leasing, management and mortgages – newer applications are now emerging across real estate like:
Site Analysis and Development Planning
Analyzing land suitability for construction requires aggregating disparate data around transportation access, geo hazards, zoning policies etc. Automating this research through software bots reduces legwork for development firms.
Underwriting and Investment Analysis
RPA shows early promise in gathering real-time market data like rent forecasts and absorption rates to feed net present value models for acquisition and project viability – enabling faster underwriting.
Transaction Management
Bot-driven support in transaction processes like due diligence, closing protocols and paperwork management frees up expensive legal resources to negotiate better contracts and derisk deals.
As these expanded use cases deliver ROI, RPA adoption will permeate across real estate segments unlocking enormous value.
Overcoming RPA Implementation Challenges
Despite its benefits, RPA adoption faces barriers like:
Integrating with Legacy Real Estate Systems
Long-used platforms often lack APIs for easy connectivity. Rigorous testing ensures bots can extract data from proprietary user interfaces without needing complex integration work.
Ensuring Access Security and Controls
Stringent user access rules govern real estate data access like credit reports or tenant details. RPA platforms provide access logs and runtime analytics to prove regulatory compliance.
Managing Unstructured Data
From handwritten lease details to scanned property titles, real estate processes rely heavily on unstructured data. Advanced OCR and machine learning extract meaning from free-form data.
Managing Process Change
RPA changes ways of working, threatening roles like mortgage underwriters and property administrators. Change management through transparent communication and reskilling/redeployment is vital for long-term RPA success.
Best Practices for RPA in Real Estate
Follow these crucial best practices when deploying RPA in real estate:
Start Small Before Going Big
Proof-of-concept focused on a contained process like lease generation builds confidence for larger automation. It also provides a template to scale across other processes.
Involve Employees Closely
Actively engage impacted employees through the RPA lifecycle – from candidate selection and design review to UAT signoff. This secures buy-in and surfaces simplification ideas early.
Develop Rigorous Testing
Test bots extensively against boundary and edge cases. Schedule regression testing after any application changes. Such rigorous validation prevents failures or compliance issues post-deployment.
Ensure Auditability and Access Controls
Verify that RPA platforms create immutable process logs for any audits. Lock down proper access controls and identity management avoiding permissions creep.
As per Gartner, it is vital to "ensure licensing complies with third-party software terms to mitigate legal or audit risks." Review policies around data handling as part of internal audits.
Plan for Scalability from Outset
Anchor RPA initiatives around a scalability roadmap across business functions. Architect the automation approach for quick replication without needing proofs-of-concept.
RPA success should be measured in cost savings and efficiency improvement overtime through increased bot usage. Assign dedicated teams for continuous expansion of automation coverage.
Maturing the Implementation: Advanced RPA Practices
Evolving from basic task automation to enterprise-wide RPA needs robust practices around:
Bot Deployment and Lifecycle Management
Centralized bot factories allow large-scale development, testing and version upgrades. IT teams oversee bot network monitoring, license management, change control policies and business continuity protocols.
Security and Access Protocols
Enterprise-grade user access controls, multi-factor authentication mechanisms, and data encryption technologies secure the RPA infrastructure for heavy usage across business functions.
Dedicated security operations teams run penetration testing, cyberthreat monitoring and disaster recovery programs to enable always-on RPA availability.
IT Governance Frameworks
Consistent policies covering development hygiene, testing rigor, operational metrics, business continuity and code reusability foster efficient RPA scaling. Steering committees provide strategic oversight on automation roadmaps.
Such mature management practices pave the path to optimized ROI from large-scale RPA adoption.
The Future of RPA – Smarter Automations, Broader Applications
RPA serves as launchpad for an intelligent real estate enterprise via steps like:
Integration with AI/ML for Smart Automations
While RPA handles structured data, smarter algorithms can extract insights from natural language or image data. Combining RPA with AI/ML unlocks next-generation intelligent process automation.
For instance, mortgage application processing will evolve using computer vision for document classification, natural language bots for information capture from written appraisals and support calls, and predictive models guiding approvals.
Expanding Use Cases Across Real Estate Value Chain
Early RPA successes prime its adoption across far-reaching use cases – from automated visual inspections using drone footage to AI bots aiding property development planning through dynamic market analysis.
As leading real estate companies demonstrate RPA‘s potential, its maturity will likely ascend into an enterprise automation imperative. Per Gartner, RPA software revenues are estimated to top $2 billion by 2022 due to expansion across verticals like real estate.
Mainstreaming adoption
RPA is estimated to grow between 20-50% yearly across real estate segments like residential brokerages, commercial leasing services, mortgage providers and property management companies.
Per Deloitte‘s 2022 Global Outsourcing Survey, ~35% of real estate leaders will adopt RPA in the next 2 years – a 300% increase over current penetration.
As RPA delivers against core KPIs like cost, efficiency, scalability and experience – early movers will inspire the mainstream in driving enterprise-wide automation.