Based on new advances in Deep Learning, a new field is emerging called Deep Analytics which deals with unconventional data collected from pictures, videos, documents written in different languages, mobile apps and data collected from Sensors and IoT (Internet of Things). The information sources with these kinds of data are exploding. For example, amount of video traffic on Internet alone is going to become 82% of total traffic according Cisco.
Given these vast amount of this new data, it is critical for statisticians to be involved in developing techniques for analysis of such data. I will describe a number of advances and challenges in this field with applications to Computer Vision, NLP (Natural Language Processing) and sensors in context of risk analysis and risk mitigation. The applications include automated damage detection, damage prevention, identifying and bench-marking causes of accidents, and legal documents.