Have you heard of Yo!, the mobile app that is a stripped-down push notification service? The simplicity resulted in over 1 million users signing up in the first couple of weeks of its availability. Initially, the app was positioned as a way to send the word "Yo" to contacts, as a way to say, "Hello. Thinking of you," or something to that effect.
Quickly, an API was released to allow subscribers to receive a push notification of, for instance, a goal scored in a soccer match. What if the subscription was made to a health-related event? Or, to a change in coverage? How about using the push notification inside an enterprise?
Hint: Senior executives do not care about text via SMS or the technical manner in which the process occurs. They care that the information is securely transmitted, especially in regulated industries. More importantly, the information in the push needs to be relevant to the recipient. What is the measure underlying the message? Is the rate of change of the reported information meaningful for a push notification process? The information needs to be relevant for an action that can accelerate a positive change to a process or activity.
Introducing sensors and smart devices and the Internet of Things (IoT) to the discussion is useful. A dongle is used by an automobile insurer to collect information from an ODB-II port, which is found in most cars manufactured after 1995. It would not be useful to push notifications internally that "John Doe has shown excessive hard braking events this morning." Or, would it? Spewing such information to a senior executive would be useless. Sending it to a local broker for a new customer with whom a life insurance policy discussion is going to occur in the afternoon might be valuable. This use of data, at a personally identifiable level, is governed by rules and regulations, as well as infrastructure that would be needed for such scheduling. Take the "Yo" concept to the next wave of IoT devices, wearable technology, and the enterprise uses in the insurance industry for notifications becomes even more interesting.
Analyzing risk and generating predictive models and accurately assessing a customer's propensity for categories of activities are mainstays of your insurer, whether for health, auto, property, or general liability. When, not if, insurers are able to act in near real-time to events captured via sensors in the form of data sent from a personally identifiable device or from social media text mining, pricing of services becomes granular and risk is more predictable. Analytics in a modern insurance company will take into account data elements from external devices and ecosystems. This multi-source data approach will result in better service to customer segments, higher customer retention rates, and greater profitability.
Profit in the insurance industry is negatively affected by fraud. Lowering incidences of fraud includes analyzing known fraudulent claims and feeding data to underwriting systems. Add in what were once considered exotic or untrusted external data sources, and scoring analyses begin to show spikes. Speech to text analysis from call centers is now very accurate. Mining for phrases and sentiment through use of speech analytics and social media analytics is now necessary, and not just an exercise for technical analysts.
Yo, the measurement of data points for customer engagement and risk reduction and increased profitability is accelerating at a rate never seen in the past. Modern insurance analytics are needed to measure this data and inform claimants, customers, brokers, and other parties sooner than ever before. Companies that embrace the analysis and provide meaningful notifications quickly will avoid disruption in the industry.