Artificial Intelligence in Finance: IoT for credit risk prevention
IoT and Indutry 4.0.
The term IoT (Internet of Things) was first coined in 1999 by Kevin Ashton to define electronic devices and everyday objects with internet connectivity. Internet of Things is known to be the new revolution of the Internet, as it allows objects and devices to interact with each other, collecting, processing and sharing data via wired or wireless networks.
IoT devices have spread rapidly in our daily lives (smartphones, security sistems, small and domestic appliances and so on) yet is the industrial sector the most prolific field of application. The introduction of IoT technologies into the manufacturing environment marked the beginning of the fourth industrial revolution, better known as Industry 4.0, making the industrial production process more efficient and reducing waste.
In the upcoming future sensors, machines, workpieces and software will be increasingly connected with each other beyond the single factory, creating a digitalized, automated and integrated system which will link together all the player of the supply chain.
Integration of IoT data in oplon Risk Platform
Industry 4.0. technologies are a valuable source of information for risk management and prevention. The integration of industrial data in risk analysis improves financial forecasts accuracy, as it allows the monitoring of the whole production process identifying in advance errors and failures.
oplon Risk Platform is a modular Augmented Analytics risk management platform that fully automates the credit assessment process. Using Artificial Intelligence and BigData Analysis, oplon can include both financial data and unstructured alternative data in the assessment process.
Alternative Data can be defined as the data provided by non-traditional sources, such as those produced by social networks and search engines or data generated by sensors. Alternative data tends to be unstructured, unorganized and text-heavy, and can only be processed by Artificial Intelligence (more about alternative data in credit risk assessment here)
The integration of financial data (such as balance sheets, bank account trends, mortgage amounts, etc.) and alternative data allows oplon Risk Platform to perform in-depth analyses and to provide accurate forecasts of company performances. The algorithm identifies potential risk factors and automatically calculates the company's credit assessment.
Using APIs oplon allows the integration of both custom models (developed independently or upon request) and information from external sources within the platform. Each API describes a specific operation that can be embedded in different operating systems without having to program it again, allowing different applications or programs to interact and share data in real-time.
For instance, it has been possibile to expoit data from 4.0. manufacturing technologies to assess the exposure risk and forecast cash flows. The model includes in the exposure risk analysis the energy efficency data of photovoltaic systems, whose construction was financed by an investment fund. oplon Risk Platform monitors the efficiency curves of each panel and notifies any problems to the companies involved in the project. At the same time, data are used to predict risk factors and project's cash flows.
Furthermore, the application of IoT data in finance improves companies’ workflow and management, allowing decision-makers to adopt ethic investment strategy in terms of sustainability: Artificial Intelligence reduces error probability, saving resources and money and cutting down waste in the manufacturing process.