Leading Practices in Multi-Channel Distribution in Insurance by Navdeep Arora

1. Leading Practices in Multi-Channel Distribution in Insurance Navdeep Arora 8 April 2020

2. 6 key characteristics of leading multi-channel distribution models Leading Characteristics Examples 1 Integrating digital and traditional channels to provide a consistent and seamless customer experience regardless of entry point • Connecting all channels to new and legacy platforms to provide a single view of customer product holdings and enable policy administration • Establishing a seamless transition between channels across entire purchase cycles 2 Co-developing new channels with customers and agents, by piloting new models and seeking advocacy to ‘roll-out’ model • Recruiting volunteer ‘agents’ to co-develop, pilot and advocate the benefits of ‘digital channel enablement’ and multi-distribution channel model. Enables agent buy-in • Using Crowd Sourcing to understanding customers needs and co-develop digital capabilities 3 Moving from a ‘push’ to ‘pull’ product and pricing strategy, providing common modularised products for customer tailoring, agnostic of channel • Move away from channel specific products and prices to a common product construct and across all channels with ‘modular’ options to allow customers to tailor product to needs. Channel agnostic pricing • Information query to existing book to prevent lower new business premiums for existing customers

3. 6 key characteristics of leading multi-channel distribution models Leading Characteristics Examples 4 Reinventing rating models using customer segment analytics to price on customer behaviour and life time value, not channel economics • Customer segment behavioural analytics are applied into rating models to inform technical price on a ‘life time value’ basis. Pricing based on predictive indicators such as length of product holding, claims frequency, average claims cost, propensity for multi-product holdings, contact centre utilisation 5 Managing conflict by assigning all ‘direct’ sales to an agent by postcode and providing ‘trail commission’ to support retention • Agents are awarded ‘trail’ commissions for all direct ‘new business’ sales of customers within allocated postcode. Agents are incentivised to promote carrier regardless of sales channel and provide service • Improving agent productivity by leveraging ‘predictive analytics’ to provide ‘attractive’ target risk profiles 6 Capturing information from all customer touch-points for data analytics and machine learning, driving personalised customer journeys, consistent communications and pricing and next best action • Capturing information on customer preferences and behaviours from ‘unstructured’ sources such as social media data and contact centre notes and ‘structured’ sources such as customer journey break-points • Data used for machine learning, providing personalised customer journeys on digital channels and telephony scripts, next best action prompts connected to customer touch-points, recorded quotes for consistent pricing across channels

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