SlideShare a Scribd company logo
Areas
AI will transform
insurance in
years
Cecilia Chow, Head of Sales, Key Accounts, JOS
Handwritten policy application forms remain popular, particularly
Chinese application forms, in Hong Kong. Turning paper-based
information into digital data is a time-consuming and costly
process for insurance providers. Natural language processing
(NLP) technologies like optical character recognition (OCR) and
speech recognition can significantly simplify this process. Many
commercial OCR software can reach up to 90% accuracy rate*,
but its ability to recognize handwritten Chinese characters
remains much lower. In the next five years, the maturing of AI and
NLP will greatly enhance man-machine interactions, transforming
the process of policy applications.
*https://en.wikipedia.org/wiki/Optical_character_recognition#Accuracy
Simplified
policy applications
24x7 personalised customer services
Many Hong Kong leading insurance providers have started their chatbot
journeys. They have matured from the first‐generation FAQ chatbots into
transactional chatbots, which integrates database, analytics, robotic processing
automation (RPA) to handle personalised enquiries 24x7. They can answer
questions about premium payment options, finding nearby doctors and healthy
food recommendations. But this is still the beginning. The chatbot market is
expected to reach US$3.2 billion by 2021*. The next generation chatbots are
expected to be virtual assistants to answer complex personalised questions, like
policy coverage assessment and offer customised coverages recommendations.
* https://www.prnewswire.com/news-releases/chatbots-market-growing-at-a-cagr-of-352-during-2016-to-2021---
reportsnreports-623184583.html
Personalised and
behavioural policy premium
The maturing of Internet of things (IoT) and its integration with AI
are driving this transformation. Traditionally insurance premium
is based on statistical sampling of past performances to forecast
risk level of future outcomes. IoT disrupts this process. It allows
insurance providers to collect data of real events and behaviour
from individuals—instead of sample data—then integrate with
machine learning algorithm to price insurance coverage. Many
insurance providers are taking advantage of wearables and
sensors, aiming to allow safer drivers and people with healthier
lifestyle to pay less.
Enable fraud detection
Fraudulent claims are massive cost for insurance
providers. It is reported to cost the industry US$80
billion in fraudulent claims each year*. One of the
most common form of fraud is identity theft, where
policyholder’s identity data is stolen for filing claims.
Some insurance providers, like Zhong An, have started
to turn towards machine learning for fraud detection.
More are expected to do the same in the next five
years. Instead of relying on human to manually catch
inaccurate claims, they use AI algorithm to identify
patterns and recognize fraudulent claims.
* http://www.insurancefraud.org/statistics.htm
Speed up claim process
The insurance industry is notorious of its slow claim processes. It is
often a result of multiple touchpoints across different departments aiming
to avoid fraudulent claims. But speed in claims settlement will be critical for
success in the next five years. AI algorithms do not only detect fraud, but also
reduce human intervention and multiple touchpoints to speed up the claim
process. An AI-enabled insurance player Lemonade stated it settles a claim
in less than three seconds.* A faster claim process does not only bring
customer satisfaction, but also improved productivity.
*https://www.cbsnews.com/news/digital-disruption-is-rocking-the-insurance-world/

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AI transforms insurance industry

  • 1. Areas AI will transform insurance in years Cecilia Chow, Head of Sales, Key Accounts, JOS
  • 2. Handwritten policy application forms remain popular, particularly Chinese application forms, in Hong Kong. Turning paper-based information into digital data is a time-consuming and costly process for insurance providers. Natural language processing (NLP) technologies like optical character recognition (OCR) and speech recognition can significantly simplify this process. Many commercial OCR software can reach up to 90% accuracy rate*, but its ability to recognize handwritten Chinese characters remains much lower. In the next five years, the maturing of AI and NLP will greatly enhance man-machine interactions, transforming the process of policy applications. *https://en.wikipedia.org/wiki/Optical_character_recognition#Accuracy Simplified policy applications
  • 3. 24x7 personalised customer services Many Hong Kong leading insurance providers have started their chatbot journeys. They have matured from the first‐generation FAQ chatbots into transactional chatbots, which integrates database, analytics, robotic processing automation (RPA) to handle personalised enquiries 24x7. They can answer questions about premium payment options, finding nearby doctors and healthy food recommendations. But this is still the beginning. The chatbot market is expected to reach US$3.2 billion by 2021*. The next generation chatbots are expected to be virtual assistants to answer complex personalised questions, like policy coverage assessment and offer customised coverages recommendations. * https://www.prnewswire.com/news-releases/chatbots-market-growing-at-a-cagr-of-352-during-2016-to-2021--- reportsnreports-623184583.html
  • 4. Personalised and behavioural policy premium The maturing of Internet of things (IoT) and its integration with AI are driving this transformation. Traditionally insurance premium is based on statistical sampling of past performances to forecast risk level of future outcomes. IoT disrupts this process. It allows insurance providers to collect data of real events and behaviour from individuals—instead of sample data—then integrate with machine learning algorithm to price insurance coverage. Many insurance providers are taking advantage of wearables and sensors, aiming to allow safer drivers and people with healthier lifestyle to pay less.
  • 5. Enable fraud detection Fraudulent claims are massive cost for insurance providers. It is reported to cost the industry US$80 billion in fraudulent claims each year*. One of the most common form of fraud is identity theft, where policyholder’s identity data is stolen for filing claims. Some insurance providers, like Zhong An, have started to turn towards machine learning for fraud detection. More are expected to do the same in the next five years. Instead of relying on human to manually catch inaccurate claims, they use AI algorithm to identify patterns and recognize fraudulent claims. * http://www.insurancefraud.org/statistics.htm
  • 6. Speed up claim process The insurance industry is notorious of its slow claim processes. It is often a result of multiple touchpoints across different departments aiming to avoid fraudulent claims. But speed in claims settlement will be critical for success in the next five years. AI algorithms do not only detect fraud, but also reduce human intervention and multiple touchpoints to speed up the claim process. An AI-enabled insurance player Lemonade stated it settles a claim in less than three seconds.* A faster claim process does not only bring customer satisfaction, but also improved productivity. *https://www.cbsnews.com/news/digital-disruption-is-rocking-the-insurance-world/