Infrastructure Data Economy

The decrease in public infrastructure spending has resulted in an infrastructure investment gap of $2.5-3.5 trn per year. To engage private financing to make up this gap, new investment solutions and business models need to be conceived. The integration of IoT with advanced data analytics is opening up the data economy for infrastructure investment. For example:

1. Network modeling to understand data and financial flows in ever-evolving industry value chains
2. Machine learning algorithms that integrate financials with textual data mining techniques to understand risk
3. Financial asset risk pricing strategies that value the impact of natural resources in the capital markets
4. Application of artificial intelligence and 'smart asset allocation' strategies to design new investment models