The insurance industry is a multibillion-dollar industry, yet it lags far behind other industries like banking and big tech in its adaptation of automation. I experienced this first-hand as an intern at State Farm. I completed a project that was a massive data entry job and made it into a process that took clicking three buttons to finish. Although just one example, it was clear that State Farm as well as the insurance industry in general are not utilizing automation and machine learning. The adaptation of automation and machine learning will have internal and external benefits for insurance companies like increased efficiencies in business processes and increased customer satisfaction. However, to realize these external and internal benefits, companies, like State Farm, must implement an adhocratic culture where risk taking is incentivized, and companies must invest resources into their underwriting processes, rather through internal investment or an acquisition, to automate the process.
Through research, interviews, and analysis, our paper provides the local community with a resource that offers a comprehensive collection of insight into the Mirabella at ASU Life Plan Community and the projected impact it will have on the City of Tempe and Arizona State University.
Through research, interviews, and analysis, our paper provides the local community with a resource that offers a comprehensive collection of insight into the Mirabella at ASU Life Plan Community and the projected impact it will have on the City of Tempe and Arizona State University.
Through research, interviews, and analysis, our paper provides the local community with a resource that offers a comprehensive collection of insight into the Mirabella at ASU Life Plan Community and the projected impact it will have on the City of Tempe and Arizona State University.
My thesis process consists of a start-up business plan for a mobile car maintenance company. Mobile car maintenance is a very new branch of the traditional brick-and-mortar car maintenance industry. The business plan will feature key components such as an executive summary, market analysis, and pricing structure. Within the business plan, there will be an in-depth financial portion estimating expenses, revenues, the initial investment required, etc. to create a discounted cash flows chart for the first 5 years of the start-up. This financial analysis will illustrate the opportunity of this business model to potential investors as well as assist in formulating the company's capital structure.
It is essential for transportation management centers to equip and manage a network of fixed and mobile sensors in order to quickly detect traffic incidents and further monitor the related impact areas, especially for high-impact accidents with dramatic traffic congestion propagation. As emerging small Unmanned Aerial Vehicles (UAVs) start to have a more flexible regulation environment, it is critically important to fully explore the potential for of using UAVs for monitoring recurring and non-recurring traffic conditions and special events on transportation networks. This paper presents a space-time network-based modeling framework for integrated fixed and mobile sensor networks, in order to provide a rapid and systematic road traffic monitoring mechanism. By constructing a discretized space-time network to characterize not only the speed for UAVs but also the time-sensitive impact areas of traffic congestion, we formulate the problem as a linear integer programming model to minimize the detection delay cost and operational cost, subject to feasible flying route constraints. A Lagrangian relaxation solution framework is developed to decompose the original complex problem into a series of computationally efficient time-dependent and least cost path finding sub-problems. Several examples are used to demonstrate the results of proposed models in UAVs' route planning for small and medium-scale networks.