...were the focus of a Future.Value conference at the University of St. Gallen on February 22nd. The host was IBM with their Watson IOT center in Munich. Uwe Klötzner was on-site and summarized the most important information.
Data availability in the insurance economy allows for new services and business models both in accessing new target audiences and beyond just insurance. Here are a few examples:
- "Bought by many" bundles risks that were previously hard to insure or not even insured, such as travel health insurance, without almost any exclusions. This creates a business model out of bundling rare risks that would otherwise be rejected.
- Telematics rates such as Friday or Metromile bill motor vehicle insurance solely according to driven kilometers (pay per use) or driver behavior (pay as your drive) – and they do not require any multi-page application forms either.
- Pitpat combines canine insurance with a wearable and provides health data.
It requires the customer’s utmost willingness to share data. In an international IBM study, only 42% of consumers stated that they trust the insurance industry. As such, the pre-conditions for data-based services could be better. Recommendations:
- High transparency: Explain what is being processed, how , and for what purpose; while doing so, country-specific peculiarities must be followed (e.g. mentality, differing willingness to share data).
- Clear communication of the added value: Financial incentives; convenience or benefits for third parties. However, the benefits that customers perceive are crucial. This is where customer-rewarding loyalty programs are helpful. All in all, companies should focus more heavily on high-quality services than on financial compensation.
- Minimize costs in the form of time/expenses, loss of privacy, etc.
Data can also be used to further develop existing processes as well. 40% of newly created data now comes from objects with sensors (internet of things - IoT). There is definitely potential in using IoT technologies for insurance companies - such as in these fields:
- Automatic claims processing, e.g. automatic photo evaluation or when damage is located after natural disasters using drone photos and the extent of the damage is assessed.
- Strengthening the customer relationship by preventing damage in conjunction with predictive maintenance concepts.
- Increasing precautions: e.g. moisture sensors can detect water damage early on and limit the amount of damage thanks to faster intervention.
- Expanding the customer relationship through business models that combine sensors and digital services.
Digital business models and services offer insurance companies the opportunity to build closer customer relationships than before and, at the same time, improve their own image. However, amidst all the excitement about technical possibilities, the economic added value of the technology used should not be disregarded.
mm1 assist you with the definition, the systematic evaluation of the success probabilities of business models and with the implementation in business processes and functioning IT systems.