Technology Driven Value Generation in Insurance by Oliver Wyman

Article Synopsis :

Insurers are leveraging cutting-edge technologies to improve existing products and develop innovative new offerings. Key technologies include cloud computing, the Internet of Things (IoT), big data, artificial intelligence, and blockchain.

The big five digital insurance technologies: Cloud, IoT, Big Data, AI, and blockchain 

“Technology Driven Value Generation in Insurance” from Oliver Wyman and Zhong An Insurance and Zhong An Technology analyses these five specific technologies in pursuit of answers to the following questions:

1. Which technologies are shaping the future of the insurance industry?
2. What are the applications of these technologies in the insurance industry?
3. What is the potential value these applications could generate?
4. How can an insurer with strong technology capabilities monetise them?
5. Who is benefiting from the value generated by these applications?

The first section of the report introduces the five technologies themselves, in layman’s terms, with ‘key implications’ of each:

CLOUD COMPUTING – Key implication: Cloud computing benefits individuals through improved interactive platforms and data management, and businesses through cost efficiency and workforce mobility.

INTERNET OF THINGS (TELEMATICS) – Key implication:  Telematics can increase efficiency, productivity and create value through increased accuracy and speed of decisions through the connectivity between systems and objects.

BIG DATA – Key implication: Big data offers more-advanced ways to analyse and use data – with a range of applications, from recommendation engines to fraud detection. Sensor data can also be leveraged to recognise human activity.

ARTIFICIAL INTELLIGENCE (AI) – Key implication: Applications of AI are increasingly widespread and complex. A 2013 study by the Oxford Martin School – ‘The future of employment: How susceptible are jobs to computerisation?’ – claims 47% of US jobs (in 2010) could become highly computerised in 10 or 20 years due to AI. This is especially important for insurers, as all insurance-specific job profiles analysed had at least a 90% chance of being partially or fully digitised.

BLOCKCHAIN – Key implication: : Blockchain has a range of use cases from virtual currencies like bitcoin to smart contracts, data storage, and automated transactions. Its technical potential is still understood by only a small group of experts. However, new uses continue to be developed.

The body of this comprehensive report evaluates the five technologies through the lens of three areas of application:

Application area 1 “improve”: Improvement of operating models employed in producing traditional insurance propositions. This is “innovation behind the curtain,” as the end customer interacts with a conventional insurance proposition. Five areas of ‘improvement’ include:

• Street pricing: Digitisation increases the transparency of the product offering. Insurers must develop dynamic pricing capabilities to react quickly in a transparent, agile market, taking into account the competitive situation at a given moment.
• Yield management: Online distribution platforms route customers to insurers and are paid for this lead generation. However, the type, quality, and cost of these leads varies significantly. Insurers must react dynamically to changing quality, price, and lead costs to ensure that the right clients are channelled to their offerings. Technology to jointly optimise “lead cost”, “steer price” and “customer lifetime value” is yield management.
• Competition on speed: Digital technology has dramatically increased the speed of dissemination of new trends. Insurers rely on static datasets such as mortality tables and claims triangles, and they must understand how rapidly changing behaviour impacts losses to “skim the cream” and underwrite the best risks.
• Improved insight: As a by-product of digitisation, insurers have access to vast amounts of data, which can be analysed to improve existing processes, enabling reduction of reliance on proxy variables when pricing products. Underwriting and fraud detection/prevention could also be improved.
• Automation: Several processes in insurance companies’ back-offices could be partially or fully automated through advanced technology such as AI, going beyond the already established straight-through processing capabilities for simple transactions.

Application area 2 “upgrade”: Technology-enabled upgrades of existing insurance products that alter the insurance proposition and have an impact on the customer experience. Such upgrades are “in front of the curtain” – they often add risk or claims services. Four major areas for ‘upgrades’ include:

• Core insurance products: Several insurance products have already been upgraded through digitisation. The best example is “pay as you drive,” or the even more innovative “pay how you drive” in car insurance.
• Insurance-related excess-value offerings: Insurers are trying to increase their range of service offerings to generate unique value points. An example of an excess-value offering is an online risk analysis tool for small businesses.
• Other excess-value offerings: Offerings and services not connected to insurance per se. A good example is an online alarm system provided as an additional component to the householder’s insurance policy. If the alarm goes off, the insurance company alerts the police, notifies the customer, and starts the claims process if a theft occurs.
• Claim handling services: Services and products that provide additional value to customers in “moments of truth” – that is, when a claim is filed. Excellent opportunities exist to reduce cost and boost the quality of customer experience.

Application area 3 “innovate”: Insurance business model innovations, such as embedding insurance into an ecosystem which ultimately might not even need insurance propositions anymore but has other, often opaque, ways of providing cover for risks. Three potential areas for ‘innovation’ include:

• Ecosystem integration: A digital ecosystem is a network of companies, individuals, institutions, and consumers that interact to create new services and value. One example is a health insurer leveraging health data and knowledge with partner nutritionists, makers of fitness-tracking devices, and fitness centres.
• Individual coverage concepts: An advanced vision of this concept could feature an end consumer in dialogue with a chat bot. The consumer would describe what coverage they need. The bot would ask for information needed to assess the risk, and then issue concrete statements on the coverage. The transcript of this dialogue would become the insurance contract, without the need for further insurance products or terms and conditions.
• Self-regulating insurance: An ideal form of insurance would give customers truly hassle-free coverage. The claims-handling process in particular could, in future, be resolved, automatically, the moment the claim occurs. For example, a claim from a farmer with crop hail insurance would be triggered based on a weather report and satellite surveillance of the field, without the farmer having to file a claim.

A deep-dive is provided on all five technologies, including ‘maturity of the underlying technology’ and ‘value generation by the technology.’ Each section includes detailed case studies, both global and China-specific.

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