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Creating an analytical environment

Creating an analytical environment

4 key areas for insurers to focus on when creating a truly integrated and holistic data ecosystem.


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Steve stormonth audit executive director kpmg in the channel islands

Audit Partner

KPMG Channel Islands Limited


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Insurance CEOs are well aware that analytics is the key to business agility - it can help reduce costs, automate processes, remove waste and enhance decision-making. Indeed, they cited in KPMG International's survey that their top strategic priority is to become more 'data-driven', and almost nine-in-ten say they have put new investment into data and analytics over the past year.

Taking strong first steps

Many insurers have made strong progress in their use of analytics and analytical models across the front, middle and back office. They have poured resources into improving their data management and analytical capabilities, and almost every insurer has start to gain strong proficiencies in areas such as propensity modeling, claims analytics, clustering and customer analytics.

Even though many insurance CEOs think they might be ready to move onto more advanced analytics approaches such as artificial intelligence, cognitive computing and machine learning, most seem to be struggling to step up their game. Few have achieved the level of analytical sophistication required to rival some of their newer, more agile competitors. Besides, 43 percent of CEOs surveyed expressed concern that the lack of quality data is hindering depth of insight.

Analysing the competition

There are many reasons why traditional insurers may be struggling. Most are trying to deal with their legacy IT environment which - having often been stitched together through a series of mergers and acquisitions - has become cumbersome. Their data is often locked up in incongruous silos, making it difficult to gain an integrated view of their customers across various products. Some are worried that too much analytics-driven automation may disrupt their historically strong customer relationships.

Insurtech companies, on the other hand, have based their business models and customer propositions on analytics. They understand the value of creating a 'single view of the customer' and they use that data and analysis to automate their entire value chain - from client onboarding and risk assessment through to claims and settlement. They are aiming to not only improve the overall customer experience, but also to reduce their process time and improve their cost to serve.

For now, the traditional insurers still have the upper hand as they boast deeper relationships with their customers and have much more customer data to develop more valuable insights and deliver a much broader range of services across the value chain; but they will need to move quickly and with purpose if they hope to retain that advantage

Creating the right environment

While insurers may face many challenges and risks with stepping up their analytics, we believe there are four key areas where they can focus on to eventually outperform their competitors:

  1. Simplify and sharpen analytics operating models and governance. Rather than treating analytics as a special initiative which runs the risk of low accountability by any group, a more effective approach is to embed the governance of data and analytics into your 'business as usual' programs and operations.
  2. Master the data. Despite the range of data management initiatives, few insurers have truly achieved an integrated view of their data that allows them to confidently pull the right data and make trustworthy decisions. Insurers should consider leveraging Application Program Interfaces (APIs) and Big Data tools that can access and integrate the relevant data from the appropriate systems to deliver rapidly an integrated data ecosystem.
  3. Focus on practical use cases. Knowing what you are trying to achieve with your analytics and how you plan to achieve it will save you from pouring resources into technologies, capabilities and initiatives that provide little future value. The most efficient route is to identify, scope and trial practical uses cases that can deliver scalable and sustainable enterprise value.
  4. Think and act holistically. Analytics should be a part of the day-to-day business operations - so that practices, capabilities and value can be leveraged across the enterprise. From governance and strategy through to talent and technology, insurance leaders will need to take an integrated and holistic view on analytics.

Given the pace of change in today's insurance marketplace, traditional insurers who want to truly compete and win in this new data-driven environment will need to move faster, with more purpose and confidence towards more sophisticated forms of analytics.

Contact your local KPMG advisors to learn more about how we can help step up your analytics game and outperform your competitors.

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