Why Deep Learning?
Do what you never imagined
Irrespective of whether you are using traditional business approaches or innovative new ones such as peer-to-peer, usage based pricing, bespoke coverage, active risk management, and branchless self-service, you can radically re-evaluate your business models with Deep Learning.
Within a business there are potential activities that have never been thought about, hiding in plain sight, overlooked perhaps because they would be unrealistic.
Deep Learning can make these activities possible. It releases you to genuinely think outside the box challenging and revitalising previous thinking and allowing you to explore the inconceivable.
It can also inspire you to think about and harness data that your business has never processed or been exposed to such as Internet of Things (IoT) sensor, satellite, and other external data.
Deep Learning allowed the automated visual analysis of every unique building (65 million) in Japan; identifying roof types, location, orientation, and condition to predict losses in the event of a typhoon with an accuracy of 94%.
Do what you thought impossible
Deep Learning enables you to rethink activities that you thought impossible perhaps because they would be too complicated, costly or time consuming to realise any net benefit.
Deep Learning can further improve or automate these activities. You can remove the constraints in your thinking as to what and how activities are performed and what and how data is communicated.
It can reveal hidden facts, trends and correlations that could change what decisions your personnel make, say in setting an excess, pricing or declining a risk.
Even brand new digital solutions can be radically reimagined, such as Chatbots becoming Voicebots through automated real time voice recognition and natural language processing, translation and generation.
An insurer carried out an exercise to determine if any major factor was related to the cancellation of live musical events. An analysis of 20 years of global news reports covering the sector revealed that artist age was the single most relevant factor. Doing this manually would have taken many man years effort.
Do what you do but better
Deep Learning can augment cognitive activities routinely carried out by personnel where they view, read, consider, decide, and respond to data presented to them.
Many such responses result in data being entered into digital and information systems, the majority of which are ‘dumb’, typically possessing only simple validation and, in some specialised instances, static business rules.
Deep Learning can be injected into your systems to perform some of the cognitive actions executed by your personnel – enabling better predictions and decisions to be made, reducing manual effort and releasing your personnel for more genuinely value added activities.
Deep Learning can be injected into any Robotic Process Automation (RPA) solution your may have deployed. It can significantly enhance the static logic and rules, which are a feature of this supposedly ‘intelligent’ technology by imbuing it with genuine machine intelligence.
