Embedding machine learning

GROW

Grow your customers’ average product holding by understanding and predicting their insurance needs and the ways in which they want to be marketed to.

Predictive analytics can help insurers identify which products and services their customers want, but it cannot tell them what marketing actions should be taken to help increase average product holding. However, by moving up the analytics maturity curve to prescriptive analytics, insurers can identify which channel, creative approach and or financial incentive will help them grow ancillary revenues.

SERVICE

Harness the power of every customer interaction to better understand and predict your customers’ insurance wants and needs as they progress through the policy lifecycle.

Machine learning is helping insurers empower their call centers – and add intelligence across other channels too – in order to improve customer experience and offer more relevant products and services throughout the policy lifecycle.

CLAIM

Power claims processes with predictive decision-making, in order to help identify opportunities to reduce claims losses and to increase automation within the claims journey.

Claims handling is the ‘shop window’ of insurance, and it provides insurers with an opportunity to enhance the image of their brand. For example, by using predictive insights to offer car hire, personal injury and assistance services – and by integrating these insights within the existing supplier network – insurers can cuts costs, reduce handling time and deliver seamless claims journeys for their customers.

RETAIN

Use artificial intelligence (AI) to understand how your customers are likely to react to different pre-renewal strategies in order to retain high-value business.

By experimenting with price changes, outbound contact methods, creative approach and incentives, insurers can use AI to decide which pre-renewal strategy to apply to an individual customer to increase the chances of renewal.