G
enerali Real Estate, an Italian asset management company with €37.4 billion under management across nine European countries, sought to maximize its location data's potential and gain deeper insights into its geographically referenced information.
In partnership with Precisely, a data integrity vendor, Generali developed City Forward, a rapid location intelligence tool that leverages Precisely's Points of Interest (POI) data. The tool was designed to provide valuable information to investment and asset management teams, helping them better understand the macro-location through geographically referenced insights.
Costanza Balboni Cestelli, head of data intelligence and innovation at Generali Real Estate, notes that City Forward was originally developed to address a significant challenge: traditional real estate metrics often failed to explain why assets with similar characteristics had vastly different values. The team discovered that up to 60% of an asset's value change over seven years couldn't be attributed to these metrics.
City Forward uses over 800 variables and 30 machine learning models to generate market forecasts for three to five years, achieving a 92% accuracy rate in real estate and 85-93% in other use cases. The tool has become a mature product, used by more than 400 Generali colleagues across 11 cities in Italy, France, Germany, and the UK.
However, developing City Forward presented significant challenges, particularly regarding data consistency and quality across different European countries and languages. Balboni Cestelli estimates that roughly 50% of the development time was spent addressing these issues.
To overcome these challenges, Generali engaged with third-party vendors to ensure consistent delivery of high-quality data across geographies. The company has now publicly released City Forward and is exploring its application in other industries, such as mobility, urban planning, and geo-marketing.
Balboni Cestelli emphasizes the importance of location intelligence and the potential for extracting value from geographical data. She notes that only 10% of this data is currently used in its geographical context, highlighting the need for specialized talent to manage and extract insights from location-based information.
The success of City Forward has been measured through standard accuracy metrics and real-life investment outcomes, with Generali achieving a 92% accuracy rate across asset types and 85-93% in other use cases. Balboni Cestelli credits Precisely's flexibility and accommodation of custom requirements for the tool's effectiveness.
