Delivering great customer experience and solving problems with data science

Reviewing data

In today’s competitive marketplace, companies are constantly looking for ways to deliver a high level of risk protection with great customer experience, while maintaining long-term business viability.

It can be a balancing act but one that companies, like Aviva Canada, are managing with the power of data science and data analytics.

Solving problems with data science – the intersection of data, analytics, and business

Data science involves collecting data, building models to identify data patterns, and making predictions to recommend actions. It is an iterative process that requires a well-defined problem, for which models are built, insights are shared, and actions are undertaken to address the business problem. Once deployed, ongoing model monitoring, with proactive checks on insights, is critical to identify potential business improvements and new problems to solve.

What does this mean in the real world?

Well-defined business objectives and effective partnerships are essential. Without them, problem solving with data science can quickly turn into a “hammer in search of a nail” situation that yields little to no business value. Companies need to invest time and resources to make data usable, trustable, and connected to enhance business value. Finally, problem-solving processes must be repeatable and scalable for long-term traction in business development. There are no “magic bullets”. Staying grounded in the fundamental data science principles ensures business solutions are sustainable for the long term.

Data science and business learning at Aviva

The Data Science practice at Aviva Canada has invested time and effort in weaponizing our data, building best-in-class data analysis models, and automating deployment and training while working with our business stakeholders to solve various business challenges. By partnering with our business stakeholders to help them unleash the power of data, Aviva Canada is better equipped to take care of their customers, support employees, and stay competitive in the market.

Aviva’s strategic focus for data science falls under five pillars:

  1. Pricing innovation – to harness market-leading pricing sophistication.
  2. Operational excellence – to advance Aviva’s underwriting and claims processes
  3. Customer centricity – to provide dynamic customer-centric service and pricing
  4. Research and development – with the goal of becoming Canada’s best AI model innovator
  5. People development – to be a hub for top insurance talent

Data solution success stories at Aviva

Aviva Canada has already seen success in using data science to improve its business operations. One example is the use of machine learning algorithms to adequately price insurance products, while enhancing decision making and automation capabilities. Another example is the use of machine learning models and analytics to support real-time decision making to transform claims operations, resulting in cost reductions for our customers enabling improved customer experience.

Aviva Canada is committed to using data science to deliver great customer experience at a lower cost. Partnering with the businesses, weaponizing data and investing time and resources to build repeatable and scalable processes are key to unlocking the value of data science in the long term. 


Looking to protect your business against new and evolving risks?

Aviva’s Global Corporate & Specialty team offers a prevention-first approach that combines technological innovation with risk management. If your large corporate business requires protection, with expert claims management and dedicated support, our team can help.

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