Report 14th International Microinsurance Conference 2018
Parallel session 9
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Alternative client data for inclusive insurance Hosted by insight2impact
By Laura Montenbruck In this session, hosted by insight2impact, practitioners provided examples of the application of alternative data in insurance provision as well as opportunities and challenges. Alternative data can range from social media profiles, online platforms, call records and shopping data, to data and images from drones and satellites as well as smartphones. Used in the right way, such information can help improve the understanding of clients and the design of more efficient insurance products. Several such examples were introduced in this session.
Using credit bureau data to drive inclusive insurance At Hollard, credit bureau and shopping data is used to better target customers. Potential customers in the South African market have a need for the products Hollard offers but often can’t afford them and culturally there is also a phenomenon of difficulty in saying no to an offer provided. This results in more than desired product volumes which are not taken up. To address this, a predictive propensity-to-pay model using bureau data was developed. When customers call the hotline, their phone numbers are matched to credit bureau data providing information on their ability to pay, and subsequent customer USSD engagements and dial strategies are used to optimise conversion. Through the propensity-to-pay model, Hollard is able to better target customers and not overburden those who cannot afford them, while optimising operational efficiencies.
Decreasing operational cost enables product pricing optimisation which results in updated products that are able to reach more customers. In another project, shopping data is being used to better understand the customer and the correlation between retail and insurance behaviour. Smartphone use in crop insurance Because of basis risk, index-based insurance may in some cases not compensate a farmer’s actual damage. Sending an expert to the field for damage assessment is too costly. Is there a more cost-effective way?
64 — Francisco Ceballos, Senior Research Analyst, International Food Policy Research Institute (IFPRI), United States 65 — Belhassen Tonat, General Manager / Non-Life, Munich Reinsurance Company of Africa, South Africa 66 — Mia Thom, Technical Director, Cenfri, South Africa
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67 — Megan Lawrence, Managing Director of Customer, Strategy and Data Analytics, Hollard, South Africa 68 — Herman Smit, Technical Director, Cenfri & i2i, South Africa, facilitator of the session
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