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It's Insurance – but Not as We Know It



It’s Insurance – but Not as We Know It

by Tony Tarquini, European Director of Insurance, Pegasystems

The traditional insurance business model is about to undergo a radical transformation. Companies are starting to take digital transformation seriously, and as part of this they are beginning to leverage new technologies including cloud, automation, analytics, artificial intelligence and mobile to provide significantly greater risk management as part of the overall insurance proposition.

Consequently, the new "As-a-Service" model has emerged, and yet, the insurance sector hasn't jumped on this bandwagon in a mainstream way. Some argue that the industry is being foolhardy in not taking note of the negative experiences of other industries' shifts from product to technology-based service business models. For example, banks are suffering death by a thousand cuts from tech companies in payments, cards, lending, and now open banking. In fact, since the financial crisis in 2008, more than 50 institutions have been granted a banking license in the UK. The market is becoming increasingly saturated – particularly with challenger banks. The traditional institutions have admitted defeat and are now looking for ways to salvage something in the value chain.

Looking further afield, telco, healthcare and many other industries are also showing that the "As-a-Service" model is the way they will go. It's unavoidable –  even software is sprinting to a cloud based, software as a service (SaaS) model.

In terms of the insurance industry, this change will be witnessed with the advent of RMaaS (risk management as a service) and it will steal insurance companies' distribution and customers in the next couple of years.

Modern insurers are increasingly leveraging data from IoT sensors, applying powerful AI algorithms to deliver just-in-time risk warnings through true omnichannel interactions on an unprecedented scale. As this technology reduces claims, which in turn reduces premiums, the size of the traditional risk mitigation market will decrease exponentially. If traditional insurers don't replace this lost revenue stream with risk management fees and services, they will wither and die.

To ensure they don't suffer the same fate as the banks, insurers need to already have:

  • 360 degree customer view
  • Automated, guided processes driven by rule-based systems and case management
  • True omnichannel engagement platforms, not the multi-channelled siloes 96% of insurers operate today

In order to provide RMaaS, insurance companies have to interact with their customers more frequently and across a variety of channels. In addition to their current IT architecture, they will need to build new systems to deal with this change. They will require systems of Data Detection, Analysis and Response, most of which do not exist in today's insurers. Combined, these help create an "Always-On Brain", constantly monitoring and acting on the flow of performance data and orchestrating decisions and responses. These decisions will be at the very least proactive but more importantly pre-emptive – responding before customers even know they need something.

Smart, predictive analytics solutions can now instantly identify all the risk and other data available about a customer in real-time and, on the basis of a set of rules, decide exactly what the company would advise as the next best action if the most experienced staff had unlimited time to research and analyse the background and value of that customer. Responses can be automated to alert policyholders of risk events and avoid potential claims. By being able to provide that higher level of personalisation insurers can really drive customer relationships. Furthermore, the time saved on having to research the background for every new customer means that employee efforts can be directed towards more important tasks.

As an example, currently, only 4% of insurance companies have a full omni-channel response capability. However, this is critical for being able to respond using appropriate channels, customer preferences, risk level and timescales. For example, an insurer warning a customer whose washing machine is broken, and that their house could flood, should not send a letter to warn them. Similarly, they need the data in minutes, not hours, and must have predictive analytics monitoring the data like an "always-on brain" responding in the right manner.

This is not a pipedream. These technologies already exist and are being successfully exploited in a variety of industries as part of a move to a service model, generate strong, long term customer relationships and secure their revenues and profits in the digital age. For insurers, the quality of protection delivered through risk warning services and suggested solutions to the risk will be the most important differentiating factor for any company and therefore be the key to business success. It won't be easy – it is a massive change to the industry and there will be significant winners and losers.

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