The retail insurance broking industry is facing an onslaught of latest technologies with a promise of transformational change and value creation. These technologies have the possibility to redescribe risk transfer and risk management and reset the retail insurance broking business products and models.

This groundswell is driven by the increase of the web of Things (IoT) and large data which beckon a replacement world where risk is instantaneously measured, predicted, interpreted, and mitigated through a gentle stream of data sources.

At its core, the proliferation and accessibility of data create a foundation to reset the retail insurance broking industry. We are during a world where we now have more data and knowledge available then we all know what to try to do while the curve of accelerating data sources and knowledge continues to exponentially increase. IoT has the potential to redefine the frequency and speed of how insurable risk is evaluated, priced, and sold.

Let’s consider a couple of examples from an IOT future world.

First, auto insurance is going to be transformed from a world of annual policy terms that in essence “mark up the value of accidents” to insurance offers and transactions that are made in real-time to drivers supported instantaneous data coming from geo-location, weather and traffic patterns, vehicle informatics, and driver experience. If a snowstorm is moving through Chicago at an hour, the insurance rate would be much above a sunny weekend day in LA. The variable price of risk is often determined at a micro-level and therefore the buying decisions will dictate if they're willing to assume the danger.

Another example is the catastrophic weather-related risk. With the continued advancement in meteorology and real-time monitoring, The near future could see a commodity exchange develop around catastrophic risk during an actual event. a corporation could utilize excess insurance markets to shop for more insurance or buy an option for extra limits during a developing situation. The info available through IoT can define pricing in real-time because of the storm and therefore the corresponding risk develops. This may change how capital is deployed and also transform the role of risk management during crisis situations into a model more like currency hedges and derivative trading.

Already today, JLT flood mapping is proceeding with big data and IoT through a singular flood model that collects government data from the last 40 years and amalgamates with various external data sources to raise the model and predict flood risk at a property by property basis. This enables owners and insurance companies to spot the danger at each individual property and price the insurance accordingly. This level of detail fundamentally shifts how companies assess risk and buy flood insurance. Furthermore, this insight becomes a part of the operational models of companies further refining their strategic decisions and investments.

"These technologies have the potential to redefine risk transfer and risk management and reset the retail insurance broking business model and products"

The proliferation of wearable and private technology, and therefore the corresponding data and knowledge, reflects yet one more rapidly developing area of IoT. As an example, one among the first challenges for risk management and mitigation is the definition of “Who or what's where?” During a crisis, it's critical that the people and assets are identified and guarded. Many firms have made considerable advancement during this space, like MOBSS, who have created technology that gives identity persistence and validation across any setting. These solutions open up a world where companies can track their people and assets in real-time and using analytics better understand the implications to enhance operations.

Another area of transformational substitute is with risk arising from International activities and IoT. Within the technology-connected world, sovereignty and borders matter far but before, the littlest company can compete and operate an equivalent level because of the largest companies across the world. IoT and large data begin to redefine the principles of trade and therefore the underlying rules of risk. The power to now view the whole system from a knowledge perspective requires retail brokers to vary their aperture and move beyond a world of localized risk to an interconnected world where each element is said and may have an impression on the whole system.

For instance, the littlest of supply chain interruptions can have ripple effects across a whole ecosystem compounding a seemingly small issue into a drag that affects business income. Additionally, product use of component parts exposes new risk as they will become the access points for hackers and cybercriminals. Finally, the speed of political change is understood soon. Companies who can understand how this information affects the system will better respond and mitigate their risk. The interconnected world that clients operate requires the broker to mirror and have equivalent capabilities and reach.

Ending where we started, with the increasing expectations of consumers, technology and knowledge drive a replacement standard of possibilities for Retail Insurance Brokers. Clients see the potential and demand that the broker understands the tools and capabilities of what technology can provide and also require discussions that intertwine technology with the insurance broking and management process.

The future of retail broking, very similar to the longer term of the retail industry generally, requires firms to know and harness the facility of knowledge in real-time to extend the efficiency of transactions, the relevance of the merchandise, and client satisfaction.