the future of ai in financial services – insurance · evolving workforce composition. an aging...

The Future of AI in Financial Services – Insurance

Deloitte PresentationMay 2018

The latest from the World Economic Forum

© Deloitte LLP and affiliated entities.

1 The Changing Insurance Landscape

2 What is AI?

4 AI in Canada

3 Role of AI in the Insurer of the Future

Agenda

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The Changing Insurance Landscape

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Five primary forces are driving change in the Canadian insurance market, causing incumbents to rethink traditional ways of doing business

Forces of Change

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Increasing Customer ExpectationsMembers increasingly expect to engage conveniently and directly with their benefits and retirement providers, often through digital channels

1

Rise of Emerging TechnologiesEmerging technologies (e.g., RPA, AI, blockchain) and advanced analytics are enabling operational efficiencies, deeper customer insight, and innovative business models

3

Rapidly Shifting Regulatory EnvironmentNew regulations (e.g., LICAT, IFRS 17, CRM2, pension reforms) are forcing financial institutions to invest heavily in new data, processes and systems

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Evolving Workforce CompositionAn aging population and growing share of millennials and contract workers in the workforce have resulted in shifting expectations for disability and wellness in the workplace, as well as growing demand for retirement products

2Insurance

Trends

Increased Competitive LandscapeIntroduction of new entrants such as InsurTechstart-ups and Tech incumbents capitalizing on new, lower cost business models and improved customer experiences are increasing competitive pressure on incumbents

4


Emerging technology is a key accelerator and enabler of change in the insurance industry, with a few cutting-edge capabilities enabling transformation through AI

Rise of Emerging Technologies

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Machine learning trains computers to produce specified outputs (e.g., natural language processing, predictions), but unlike traditional programming does not dictate their methods of doing so; this allows it to become more accurate over time

Machine / Deep Learning

AI leverages big data, advanced analytics, machine learning, and other technology to drive insights and convert them to action, making decisions alongside or independently of humans

Artificial IntelligenceBig Data

An increasingly connected and digital world is generating unprecedented volumes of structured and unstructured customer, business, and risk data

New tools (e.g., RPA) are leveraging data to gain greater insight, allowing insurers to better understand their customers and automate processes

Advanced Analytics


What is Artificial Intelligence?

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AI has slowly but steadily begun to affect our lives by facilitating many of our everyday tasks and activities, from scheduling meetings to driving cars

Artificial Intelligence

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Interact

Act

Understand

Artificial Intelligence Conceptually, artificial intelligence (AI) refers to computer systems able to perform tasks that traditionally require human intelligence

What is AI• Artificial Narrow Intelligence (ANI) – an AI able to

match human capabilities and ways of thinking in specified domains (e.g., chess, analytics)

• Artificial General Intelligence (AGI) – an AI matching human capabilities and ways of thinking in any domain

• AGI has not yet been achieved, but ANI is already transforming the world

There are several categories of human capability that AI developers are able to match or exceed


Artificial intelligence programs can act, interact, and understand, powered by a foundation of machine learning algorithms that improve over time

Making Sense of Artificial Intelligence

7

TextImagesSpeech

Etc.

TextImagesSpeech

Etc.

User AppWebsite RobotEtc.

Cloud Solution Firm Server

Etc.

Machine Learning Pre-trained Models

Speech / Voice Recognition

Text Analytics / Natural Language Processing

Natural Language Generation

Object Recognition

Sentiment Detection

Pattern / Anomaly Detection

Recommendation Engine

Etc.

AI Application


AI’s enormous potential and high public profile have given rise to a few key mythsAI Myths and Misconceptions

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Myth 1: AI only automates the work that people doIn most cases, AI is used to complement human labour with machine labour

Myth 2: AI will lead to substantial job lossesAI can be used to free up capacity to complete value-added activities

Myth 3: The financial benefits of AI are far down the road83% of respondents to a Deloitte survey of AI users said their companies had achieved moderate or substantial impacts from AI projects

Myth 4: AI is only about transformational changeAlthough AI has significant transformational potential, it can also deliver a wide range of incremental benefits


What role will AI play in the Insurer of the future?

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The World Economic Forum and Deloitte have spent the past year exploring the future of AI and automation in financial services

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1 How are existing AI capabilities changing the operating models of financial institutions?

2 Over the longer term, how will AI shift strategic priorities and competitive dynamics?

3 Where will near and longer term changes create regulatory and public policy uncertainties?

Research Questions

By working with leading incumbents…

San Francisco, USAOct. 2017

London, UKOct. 2017

Zurich, SwitzerlandNov. 2017

Hong Kong, SARNov. 2017

New York, USANov. 2017

…and with leading innovators

Through interactive workshops held in financial capitals around the world

Davos, SwitzerlandJan. 23-26, 2018


Across the value chain, AI presents opportunities for insurers to do things differently…

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Enhance Risk Advisory

Design and Offer New ProductsDo More with Less Be Proactive and

Preventative

AI can help customers better understand their risks

AI can reinvent the product development journey

Increased efficiency frees resources and creates

opportunity

AI can allow insurers to help customers avoid risk


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What are the biggest pain points and uncertainties our customers face

throughout the insurance lifecycle?

Whether through digital or analog channels, customer advisory will be increasingly

customized and tailored to the specific needs and risk exposures customers

How can we best educate and advise our customer in a way that is scalable?

How can we best customize each product to target the exact needs of customers?

Enhance Risk Advisory…

© Deloitte LLP and affiliated entities. 13

I n s u ra n c e A d v i c e a n d I n s u ra n c e Po l i c i e s s h o u l d b e c u s to m i ze d t h e i n d i v i d u a l …

Of customer’s surveyed said the ability to easily customize their policy and make updates post-purchase is important

86%

78%track and makechanges to policy

check coverage,typical payout forspecific events

69%buy more or adjustcurrent coverage

67%chat via call or message with anagent

63%

Customers said the most useful mobile insurance features are:

A d v i c e s h o u l d b e ava i l a b l eu b i q u i to u s l y a n d b e s e a m l e s s l y c ro s s - c h a n n e l …

AI will allow insurers to scale the ability to customize and deliver personalized advice…


Example: Brolly – Your Personal Insurance Assistant…


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What customers and segments are insurers choosing not to target due to

cost and access restrictions?

Automated and streamlined operations allow insurers to miniaturize products and

distribution models, enabling them to reach new customers and segments which they

never could before

How can I leverage my agility to access new markets?

How do I think across the value chain to be as lean and nimble as possible?

Do More With Less…


Car damageExternal motor mechanic

evaluates reparationtime and expenses

Manual decision aboutpayment

Insurance expertevaluates and adjusts

report

?

Car damageExternal motor mechanic

evaluates reparationtime and expenses

AI (ML) evaluates report Automated decisionabout payment

?

Car damage – Image recognition

Before:

After:

AI expands the scope of processes that can be reliably automated…


WeChat’s latest viral hit in China: health insurance“A collaboration between Tencent and Taikang Life Insurance allows WeChat users to receive various amounts of health insurance protection”

M i c r o - C o v e ra g e : C u s t o m e rs c a n p ay o n e y u a n ( $ 0 . 1 6 ) fo r i n s u ra n c e c o ve ra g e w o r t h 1 , 0 0 0 y u a n

S o c i a l a n d M u t u a l R i s k Po o l i n g : U s e rs c a n d o n a t e t o t h e i r “ f r i e n d s c i rc l e ” w h i c h i n c re a s e s f r i e n d s ’ c o ve ra g e c a p

Example: Tencent and Taikang Life Insurance


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What is missing from current product shelves?

AI allows Insurers to rethink product shelves from the ground up. Agility in product

development can supercharge speed-to-market allowing insurers to offer dynamic

products and services

What risks go uninsured today because we can’t predict them with accuracy?

What are the unserved needs of customers?

Design and Offer New Products…


….This creates an opportunity space for innovators to create new products and services

Source: Ovum research and FICO

expect cyber breaches to increase in the next year61%Of U.S. firms do not have Cyber

Insurance, yet…50%

Cyber Risk is an example of an under-insured risk category with little historical data, making it difficult to estimate losses and price liability coverage…

New risk categories exist where customers are underserved and products are scarce…


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How can we extend interaction points with customers?

The insurer of the future should be predictive, not reactionary. AI can let insurers play an

active role to help customers avoid risks

How can we leverage data to develop predictive tools?

What new business models that emerge from a predictive toolset?

Be Proactive and Preventative…

© Deloitte LLP and affiliated entities. 21Source: GreenMatch

1/3 of total food made for consumption

is either lost or wasted globally

….Insurers can leverage their data to deliver new services that provide mutual benefits

Food waste is a major global issue, for society as well as representing a major cost for clients and a sources of losses in commercial liability insurance…

Improve the margins of clients

Reduce losses in commercial liability insuranceUse IoT and AI to deliver reduce food waste

Example: Food Waste…


M o n i t o r i n g r i s k s i n re a l t i m e c a n i m p ro ve i n t e r n a l o p e ra t i o n s a n d r i s k m o d e l l i n g , b u t i t a l s o c a n b e a n e w s e r v i c e o f fe r i n g

Example: Marine Insurance…


Looking Ahead…

As Insurance becomes more personalized, consumers will enjoy better prices and coverage, however this raises challenges for those who are priced-out or excluded by algorithms→Recommendation: Regulators and Insurers should work together to identify which population segments are at-

risk and pursue opportunities to mitigate exclusion and work to design algorithms that avoid biases

1

AI will push Insurance to be more connected, more real time, and more accurate, yet incumbents start from a position of disadvantage on the new battlefronts of data compared to Large Tech →Recommendation: Incumbent should expand their participation in the broader technology and data ecosystem to

establish the relationships and partnerships that will be required in the future

2

Increasing use of data raises privacy concerns and dynamic policies and coverage require new regulatory and ethical frameworks→Recommendation: Insurers can help get ahead and play an active role in defining what ethical frameworks should

look like by working together with regulators, consumers, and other stakeholders

3


AI in Canada

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A wide-ranging ecosystem of AI researchers, accelerators, startups, and international players has positioned this sector for rapid growth

Canada’s AI Ecosystem

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Toronto

Vancouver

Montreal

Edmonton

Startups

Research

Labs

Incubators, accelerators,

and VC

International players in Canada

Major international tech players are making significant investments in Canadian AI

World-renowned research centres are attracting top talent and international

attention

Canada’s government has made AI a key priority, supporting research and a supercluster that brings together

institutions, incumbents, and startups

Canadian companies have the opportunity to gain a global

competitive advantage through emerging AI technology


Sun Life provides members with Ella, an interactive digital assistant, who helps them understand their benefits and provides advice

AI in Canada Case Study: Sun Life’s Ella

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Sun Life launched Ella in 2017, an interactive digital coach that helps members understand and make full use of their benefits

Ella can provide proactive advice, such as suggesting changes at major life events

Ella is available online, by mobile app, or through Google Home

Natural language processing allows Ella to interact with members much as a contact centre representative would

How they are changing the game:


A biometric and natural language processing system in the contact centre verifies customers’ identity via voiceprint, and routes their call to the correct place

AI in Canada Case Study: Manulife

27

Manulife implemented natural language processing AI in its contact centre to better identify and serve customers

The software can recognize customers’ unique biometric voiceprint, verifying their identity through a few personal details and a simple spoken phrase

The interactive AI improves customer experience by removing the need for cumbersome verification, and improves servicing efficiency by effectively collecting information

Once the customer is identified, the system understands their spoken description of their problem and routes them to the correct place



Insurtech accelerator Cookhouse Lab brings together incumbents and startups to collaboratively solve some of the industry’s most pressing problems

AI in Canada Case Study: Cookhouse Lab

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Toronto-based Cookhouse Lab is Canada’s only insurtech accelerator, bringing together carriers, brokers, reinsurers, startups, and other players to develop innovative solutions

In late 2017, Cookhouse launched a project to explore how AI and chatbots can improve claims notification and management

The accelerator’s highly collaborative model and focus on insurance make it a key place to watch for groundbreaking innovations

Cookhouse launched an ongoing series of POVs on chatbots in insurance, potentially foreshadowing additional efforts in this area



Key Takeaways

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“There’s a way to do it better – find it.” - Thomas Edison

“Even though a lot of the buzz in AI has been around large tech companies, if you look across an entire company, really any Fortune 500 company can create a lot of value with AI as well”- Andrew Ng (Founder of Google Brain)

“These technologies are not a threat, they’re more like superpowers”- Jeff Kowalski (Chief Technology Officer, Autodesk)


Stay Connected

Read more on the role of AI in insurance, and other emerging topics, here: www.deloitte.ca/insurance

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Denizhan Uykur

Financial Services Strategy, Monitor Deloitte

Project Specialist, World Economic Forum

[email protected]

416-985-7087

Melissa Carruthers

Life & Health Insurance Strategy

[email protected]

416-453-9021

mailto:[email protected]

mailto:[email protected]

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