Customer Story
Generali Real Estate Leverages AI and Machine Learning to Inform Investment Strategies
30
machine learning models
95%
machine learning model accuracy
80%
satellite module accuracy
Overview
Generali Real Estate is one of the world’s leading real estate asset managers. Headquartered in Italy with nine European offices, the company has more than 360 employees, €37.4 billion assets under management (AuM), and 190 years of experience managing a portfolio of more than 2000 buildings. Many buildings, such as the 17th century Palazzo Bonaparte palace in Rome, have significant historical value.
Challenge
When Generali Real Estate became one of the first real estate asset managers to establish a dedicated division for AI and machine learning (ML) innovation, its first task was to disrupt the traditional decision-making processes that usually inform investment strategies.
For example, standard real estate metrics often don’t reveal the reason for significant variances in the value of assets, even when similar assets are only within a few streets of each other. The team discovered that as much as a 60 percent change in value, observed over seven years, could not be explained using classic real estate metrics such as prime rent or capital value.
To address these challenges, Generali Real Estate developed City Forward®, an innovative cloud-based location intelligence platform that helps real estate professionals and others make smarter decisions powered by highly accurate AI-driven insights.
“We wanted to use alternative forms of data, especially spatial data, to address these problems,” says Costanza Balboni Cestelli, Head of Data Intelligence & Innovation for Generali Real Estate. “Ultimately, without data context, there is no such thing as AI in the field of location intelligence.”
Data scientists for City Forward needed to feed the ML models, but they faced challenges, including:
- Standardizing data coming from different data sources
- Verifying the accuracy of the data
- Feeding data to ML models with maximum accuracy and consistency
- Enriching in-house data with accurate third-party data to feed models and provide lift
The City Forward team wanted to balance global and local data sources and ensure consistency, quality, and scalability when looking at data providers. “We wanted to speak with the best provider of this type of data, and we knew Precisely was a leader in the location intelligence and data enrichment market,” she says.
Industry
Real Estate
Company overview
- Headquartered in Italy
- €37.4B+ Assets Under Management
- 2,000+ Buildings
- 360+ Employees
- 190 Years of Experience
- 9 European Offices
Solutions
“Precisely provides us with access to accurate, consistent, and contextual enrichment data that helps power our AI/ML models in a way that is both scalable and reliable.”
Costanza Balboni Cestelli, Head of Data Intelligence & Innovation
Generali Real Estate
“We wanted to speak with the best provider of this type of data, and we knew Precisely was a leader in the location intelligence and data enrichment market.”
Costanza Balboni Cestelli Head of Data Intelligence & Innovation
Solution
City Forward turned to Precisely to help them standardize and verify property addresses, geocode addresses with latitude and longitude coordinates, enrich data sets with third-party information, and join their data using the PreciselyID. “We started using Precisely’s data along with other types of data such as social demographic, satellite or real estate data that can also be transaction based,” says Balboni Cestelli. “Then we paired them to understand what effect those variables have on market attractiveness or the value of an asset. Precisely provides us with access to accurate, consistent, and contextual enrichment data that helps power our AI/ML models in a way that is both scalable and reliable. We started with 20 variables and immediately, point of interest (POI) and proximity stood out as one of the most significant. Cities and geographies influence, and are influenced by, everything that goes on around them. The idea was to build a structured and scalable database that contains point of interest data.”
Outcome
The City Forward platform leverages Precisely Points of Interest data, alongside data from other third-party providers, to deliver comprehensive information on business locations, leisure hot spots, and other geographic features – revealing hyper-local insights on real estate assets and more. Because Precisely assigns a PreciselyID to every address it geocodes, it’s easy for clients to analyze data for attributes that relate to specific locations. Leveraging the Precisely portfolio of market-leading geo addressing solutions ensures customers are equipped with the most accurate location and address information available .
For Generali, City Forward paved the way for a quantum leap forward. “This solution led to a new level of precision in the real estate industry, and we pioneered the use of alternative data for real estate. We are testing more use cases from retail to urban planning, to ad industries, all over Europe,” Balboni Cestelli says.
Today, City Forward is Europe’s largest, most varied, and most granular data infrastructure. The application uses more than 800 variables and more than 30 ML models, bringing unprecedented granularity to forecasts. Beyond real estate, City Forward is scalable across industries and geographies where it’s used in more than a dozen use cases to shed light on sociodemographic information, consumer habits, web data, ESG (environmental, social, and governance) reporting such as CO2 emissions, green areas, criminality, points of interest and territorial data, people mobility, traffic and tourism flows, and satellite data.
Next Steps
“We have been working with Precisely since day one, and we still do, and we will continue to. Our 30 ML models have an average accuracy of 95%. Our satellite modules are extremely useful as they have an average accuracy of 80%,” Balboni Cestelli says. “More than 400 colleagues are using City Forward data for real estate operations, as well as a few other clients in retail and the public sector. Going forward, we’re exploring how to incorporate GenAI, use computer vision or other technology to enhance images, and increase the number of use cases where location intelligence can change the game.”
About Generali Real Estate
Generali Real Estate S.p.A. is one of the world’s leading real estate asset managers with around €37.4 billion of assets under management as of end of 2023. It leverages the expertise of more than 370 professionals, with operating units located in the main European cities.
The company’s integrated business model covers the full scope of asset management activities and the entire real estate value chain. A series of cross-border investment vehicles, managed by the specialized asset manager Generali Real Estate S.p.A. Società di gestione del risparmio, aims to create long-term value for investors with a core/core +profile by investing in assets characterized by good locations, high liquidity and strong underlying leasing dynamics. The portfolio under management comprises a unique mix of historical and modern properties, ranging from landmark buildings to new architectural masterpieces, which has enabled the company to develop best-in-class skills in the fields of sustainability, urban development and technological innovation. Generali Real Estate is part of the Generali Investments ecosystem of asset management firms.
In recognition of their innovative work, Generali Real Estate received the Data Integrity Award for Best AI Impact.
Precisely Points of Interest
Identify trends in a specific area and derive actionable insights.