We work with existing deal sources to gain access to their real estate (debt and equity) deal flow. Each of these firms performs their own screening analyses during the vetting stage and provides a set of high quality deal flow. We see the same value from several other channels, online and offline, and will likely expand our sourcing channels in the future.

We screen these deals with our proprietary software, trained on nineteen years of commercial real estate data. Our algorithms are focused on risk mitigation, improving overall fund performance by reducing loss or writedown. The GILfund proprietary investment selection model indicates between 20-50% improvement in loss/writedown rate resulting in a potential 1.8-4.5% improvement in net annualized return over average market performance, but having the potential for disproportionate value in a leveraged scenario.

This expertise in real estate asset selection is codified into software, tested against historical data corpus and current trends.

Drivers for property selection / rejection can be evaluated manually, both to better train the system and to doublecheck human evaluations.Our underlying algorithms will continue to evolve and improve as market conditions change.