Data fuels every aspect of the insurance business, from underwriting risk to detecting fraudulent claims. But today’s insurers have access to more realtime data than ever before and they are using it like never before—to offer pay-as-you-go and usage-based insurance, and to help and incentivize customers to reduce their exposure to risks. But what if the data is wrong—the sensor is faulty, the customer lies or the data is biased or manipulated?

Data Veracity: The Importance of Trust is one of five trends highlighted in Accenture’s Technology Vision for Insurance 2018. Data veracity refers to the extent to which data can be trusted.

More data means more risk

The data insurers rely on comes from everywhere—from policyholders’ connected cars, homes and workplaces; from drones and satellite imaging; and from external sources such as government databases and social media. It’s helping insurance carriers to make better operational, risk and pricing decisions and develop innovative business models.

  • Commercial insurers partner with makers of industrial equipment to use sensor data to guide preventative maintenance in mines, factories and other plants.
  • Life insurers use fitness data from wearables to encourage customers to lead heathier lives.
  • Auto insurers use telematics data to coach people about driving safely.

But with the greater reliance on data comes greater risk, especially as more organizations push toward fully autonomous decision-making. The reality is that even the most advanced analytics and forecasting system is only as good as the data it is given to crunch.

Highlighting the risk is the fact that 80 percent of insurance executives report their organizations are increasingly using data to drive critical and automated decision-making at scale. A recent study estimated that 97 percent of business decisions are made using data that the company’s own managers consider of unacceptable quality.

What is going wrong, and can insurers mitigate this risk?

Addressing the risks of data veracity

Insurance companies can address this new vulnerability by establishing, implementing, and enforcing standards for data provenance (verifying the history of data through its lifecycle), context (the circumstances of its use), and integrity (securing and maintaining data). But they must also be vigilant in uncovering and addressing ways stakeholders might manipulate data.

For example, consumer reactions to incentives and dynamic pricing algorithms, or fears about how data may be used, mean there is a growing need for companies to understand people’s motives for disclosing—or disguising—data.

The presence of bad data in a system may also be a sign that a process isn’t working the way it was intended. Uncovering processes that inadvertently incentivize deceit is a key step to improving the truth in data across a system. Incentivizing truth will allow companies to reduce noise in data, so that real threats stand out.

Join me next week as I explore the impacts of another Accenture Technology Vision for Insurance 2018 trend—Extended Reality: The End of Distance, which looks at the impact of virtual and augmented reality technologies.

In the meantime, Accenture’s Technology Vision for Insurance 2018 report offers more on data veracity and how it can be addressed.

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