In the next decade, we will see breakthroughs in prescriptive analytics that will lead to automated risk mitigation across industries ranging from logistics and finance to fast-moving consumer goods. The next wave of innovation will shift us from predictive insights limited by traditional data processing power to prescriptive actions based on intelligent machine learning. Rather than identifying what could happen, these capabilities will help us understand what should happen by identifying and reducing risks before they even take place.

Sophisticated data and analytics models will enable automated decision making around complex concepts such as predicting workplace accidents, addressing compliance violations and activating business interruption procedures before events take place. The drivers of this change will come from unlocking new ways of both collecting and processing data.

Enhancing data collection

Firstly, data collection will continue to soar through evolving digital channels. Statista estimates there will be 30.7 billion connected devices in 2020, which will continue to grow with the influx of remote sensing devices, satellites and drones. The key here is the shift from the collection to the application of data as machine learning models become intelligent enough to provide prescriptive actions.

Advances in quantum computing

Secondly, at the same time, there has been significant progress and investment in quantum computing. Traditional computing has limitations in the size and complexity of the problems it can solve. Quantum computing offers a new approach that leverages mechanical physics to process vast quantities of information. In October 2019, Google announced that its quantum computer called Sycamore completed a complex computation in 200 seconds. That same calculation would take even the most powerful supercomputers approximately 10,000 years to finish. Additionally, venture capital flows indicate broad investment in both the supply chain and application of quantum computing, which validate the viability of the technology.

So, how will these two trends intersect to impact insurance and risk management? My prediction is that the result will manifest to deliver highly sophisticated, automated risk mitigation at scale. Consider scenarios such as:

• International logistics companies will track and collect data such as temperature, pressure, windspeed and humidity to predict when goods may become damaged. A machine learning model will then interpret this data to tell an employee exactly when, for example, to fix the air conditioning. The new part is delivered by drone before the issue would normally have been detected.
• Large banks will track the creation of new accounts, trades and movement of money at a massive scale. Machine learning models will predict potential fraud and then a compliance manager will receive an automated report detailing the suspicious transactions and providing detailed next steps to prevent or address compliance violations.
• Consumer product companies will ingest social media, call center, email and other data for a quantum computer to integrate and detect trends. These trends will detect potential reputation risks that enable real time adjustments by CEOs, strategy teams and marketing departments.

Ultimately, predictive models will enable risk managers to see an incident before it occurs and receive detailed actions on how to reduce severity or avoid an incident altogether. This intelligent use of data will enable a safer, more resilient and more capital-efficient society.

About the Author

Jeff Simon is a VP in Aon’s Data & Analytic Services solution line focused on strategy and business development. He is a leader of the Innovation & Partnerships function, which is responsible for global strategic partnerships and driving Aon’s engagement with the emerging technology ecosystem.

Over the last 9-years at Aon, Jeff served in several roles including Talent Consulting, Finance & Operations and Corporate Strategy within the CEO Office. Prior to Aon, Jeff was at a technology development start-up based out of Atlanta.

Jeff graduated from Emory University with a Bachelor of Business Administration. He is based out of Chicago.