Incorporating Habidatum’s mobility metrics alone reduced the total predicted loss error by 15 percentage points in an equipment breakdown loss prediction model. When combined with our LRS, the reduction increased to 27 percentage points compared to the baseline model. — Insurance is about future risks and losses. It is a business of preparedness based on hints found via data, statistical simulations, estimates and probabilities. There is no other way to sell coverage for future losses than first simulate them, and then price them accordingly.

INTRO When a turbulent market knocks on your door, the dependency of businesses on robust market data is critical. Reliable CPI is among the most wanted statistical indicators, however, still based on estimates not covering each and every price point in the country. Big Data could be a solution that…

Habidatum is an American company assisting urban planners, professional experts, and businesses in understanding the dynamic urban environment through “big data” analytical interpretation tools including data analytical visualization. Habidatum’s software aggregates, transforms, and interprets unstructured spatial and temporal data generated by people and their devices usually as a byproduct of…

Intro To explore how New York City (NYC) community changed over the pandemic, we took data from GPS aggregators and looked at the relocation patterns of New Yorkers choosing to leave their homes until the pandemic is over, or even longer. In the previous article, we explored people’s outflow from NYC…

Over the last few years, Habidatum has been working to make real estate property location a measurable and manageable asset. Habidatum’s Location Risk Score is the core metric that supports it and decouples real estate properties from their locations. Location Risk Score calculation is global and real time which naturally…

Intro New York City (NYC) community changed a lot over the pandemic, sending hundreds of thousands of people away from their urban dwellings, and sparking interest among urban analysts. Where did people flee and why? What is the hinterland of NYC dwellers? We took data from GPS aggregators and looked at…

Intro: make use of time, let not advantage slip When Shakespeare coined this famous romantic plea, he might have not had an idea how practical his appeal could be in the field of commerce. The amount of time one spends in a location, so-called dwell time is way more important than the number of people passing this location.

Key takeaways from our second lecture at the MIT Center for Real Estate Coming from academia ourselves we are pleased to contribute to the leading educational practices, reading guest lectures and providing students with an understanding of our own experience in linking data science with real estate markets. Кey takeaways from our second lecture at the MIT Center for Real Estate: ✓ The background of Location Risk Score:

Best vs. current use mismatches highlighted by Location Risk Score — Rationale Summary: Location has always been a key value determinant for investing in commercial real estate (CRE). However, to factor it in has always been a costly and time-consuming process with high levels of subjectivity. …