Implementing AI in commercial real estate
Using AI in commercial real estate to radically improve customer onboarding
When onboarding new commercial tenants, a typical scenario might unfold as follows:
A prospective tenant comes to view the premises and the meeting goes really well. The annual rent and lease length don't seem to be a problem. Then the process moves to asking for financial information and, if necessary, setting a deposit.
At this point, the process can slow down to a crawl. Documents can be slow to find and share, once they have been reviewed, more documents might be requested. The important decisions on approval and deposit size will often be made subjectively, meaning that they are hard to explain to prospective tenants.
Slow processes are costly for landlords and tenants
These long onboarding periods can be a problem for landlords. There is uncertainty over the rental terms while checks are being carried out. The processes of financial analysis and deposit setting (particularly for smaller deals) can increase vacancy times, as tenants may not wish to provide a certain document or pay a requested deposit.
The delay is also unappealing for potential tenants. Naturally, they will want an efficient application process for new premises, including being told about any financial information and/or deposit requirements. Knowing this information beforehand will help them to streamline their search.
Being open upfront about costs and processes allows landlords to establish a relationship with prospective customers based on transparency and trust. Landlords should make their application process as painless as possible so that they can fill their properties quicker with loyal and happy customers.
Large financial decisions in adjacent sectors have seen the benefits of embracing AI
In many industries, Artificial Intelligence (AI) is now widely used. For instance, in consumer finance it can be used to analyse both traditional data sources like credit history as well as newer ones such as social media accounts to make approval decisions on loan applications.
Here’s how it works. Insurami’s app lets landlords screen prospective tenants for free, then offer an alternative to the traditional deposit, a deposit guarantee, based on the risk score generated by our AI risk model. allow separate computer systems to share data with one another. By using APIs to return data on applicant companies, AI can then be used to process this data and make a decision on their application instantaneously.
AI can process large amounts of historical data and find patterns. It can then use these patterns to make decisions on new instances. AI has seen an explosion in commercial use in the last decade due to exponential growth in the amount of data being generated and captured, as well as the increasing power and availability of cloud computing solutions.
In commercial real estate, AI can use historical data to determine the profile of prospective tenants who are likely to default on their rent, if they are approved for a tenancy. When a new company applies for a vacant tenancy, the landlord would use the AI to evaluate the risk of the new tenant, and then decide immediately if they would like to proceed. This saves the landlord from wasting their time on risky tenants and lets them focus on higher value activity, like negotiations with viable tenants.
In the UK, Companies House is an important resource for gathering data on businesses. A wide variety of information is available there, from audited accounts to the names of directors. There is data available on all limited companies, with a greater depth of data for those that have been established for longer.
Even for newer companies that might have less of a presence on Companies House there are easy options for specialist companies to acquire the relevant data in a streamlined way. Cloud accounting software can be used by the companies to share management accounts data. This means that with permission, the software will share up-to-date financial data through an API. Companies will also often have social or professional networking accounts such as LinkedIn. From these it’s possible to gather key information such as the company’s employee growth and on-going customer engagement and feedback.
External AI experts can help landlords get value quickly
Using these varied data sources will require investment in resources and staff with the required specialised skills. Commercial landlords may not have the expertise in house to do this work and will want to prioritise what matters to them: sales and internal operations to improve profitability. For these reasons, outsourcing is a great option.
Landlords looking to enhance their tenant onboarding experience, should explore using AI to collect data on applicants and make approval decisions. Otherwise they risk falling behind competitors, losing the best tenants and potentially increasing vacancy rates as a result.
At Insurami, we have a team of AI experts who have experience working with data on SMEs and building algorithms that evaluate their risk. We can apply these techniques to help landlords improve their onboarding processes. Because we offer an insurance product, the Deposit Guarantee, that pays out if a tenant defaults on the obligations, we have skin in the game. Insurami’s Deposit Guarantee lets landlords screen prospective tenants for free, then offer an alternative to the traditional deposit, based on the risk score generated by our AI risk model.