Listen to an experienced, global panel of insurance professionals present, discuss and answer your questions on the theme of “AI & Machine Learning”.
Brought to you by The Digital Insurer and sponsored by KPMG.
This presentation was given at the OECD Network of AI Specialists (ONE) held in Paris on February 26 and 27. It was presented at the joint session of ONE and the Digital Council. It covers some of the key trends and developments in AI including operationalizing AI, responsible AI and National AI Strategies
Data has always played a central role in the insurance industry, and today, insurance carriers have access to more of it than ever before. We have created more data in the past two years than the human race has ever created. Insurers—like organisations in most industries—are overwhelmed by the explosion in data from a host of sources, including telematics, online and social media activity, voice analytics, connected sensors and wearable devices. They need machines to process this information and unearth analytical insights. But most insurers are struggling to maximise the benefits of machine learning.
Ai in insurance how to automate insurance claim processing with machine lear...Skyl.ai
Explore more at https://skyl.ai/form?p=start-trial
About the webinar
Insurance companies are looking at technology to solve complexity created by the presence of cumbersome processes and the presence of multiple entities like actuaries, support team and customers in the claim processing cycle.
Today, a lot of insurance companies are opting for Machine Learning to simplify and automate the processes to reduce fraudulent claims, predict underwriting risks, improve customer relationship management. This automated insurance claim process can remove excessive human intervention or manual errors and can report the claim, capture damage, update the system and communicate with the customers by itself. This leads to an effortless process enabling clients to file their claims without much hassle.
In this webinar, we will discuss how insurers are increasingly relying on machine learning to improve claim processing efficiency and increase ROI.
BBS-248 Artificial Intelligence (AI) for Financial ServicesOzgur Karakaya
• Artificial Intelligence (AI) general info and the AI world market
• AI in financial sector: services that AI can be applied (Investing, Management, Market Research, Blockchain, Fraud Detection, AI Assistants/Bots, etc.)
• AI firms, products and the tech behind.
This presentation was given at the OECD Network of AI Specialists (ONE) held in Paris on February 26 and 27. It was presented at the joint session of ONE and the Digital Council. It covers some of the key trends and developments in AI including operationalizing AI, responsible AI and National AI Strategies
Data has always played a central role in the insurance industry, and today, insurance carriers have access to more of it than ever before. We have created more data in the past two years than the human race has ever created. Insurers—like organisations in most industries—are overwhelmed by the explosion in data from a host of sources, including telematics, online and social media activity, voice analytics, connected sensors and wearable devices. They need machines to process this information and unearth analytical insights. But most insurers are struggling to maximise the benefits of machine learning.
Ai in insurance how to automate insurance claim processing with machine lear...Skyl.ai
Explore more at https://skyl.ai/form?p=start-trial
About the webinar
Insurance companies are looking at technology to solve complexity created by the presence of cumbersome processes and the presence of multiple entities like actuaries, support team and customers in the claim processing cycle.
Today, a lot of insurance companies are opting for Machine Learning to simplify and automate the processes to reduce fraudulent claims, predict underwriting risks, improve customer relationship management. This automated insurance claim process can remove excessive human intervention or manual errors and can report the claim, capture damage, update the system and communicate with the customers by itself. This leads to an effortless process enabling clients to file their claims without much hassle.
In this webinar, we will discuss how insurers are increasingly relying on machine learning to improve claim processing efficiency and increase ROI.
BBS-248 Artificial Intelligence (AI) for Financial ServicesOzgur Karakaya
• Artificial Intelligence (AI) general info and the AI world market
• AI in financial sector: services that AI can be applied (Investing, Management, Market Research, Blockchain, Fraud Detection, AI Assistants/Bots, etc.)
• AI firms, products and the tech behind.
The slide has details on below points:
1. Introduction to Machine Learning
2. What are the challenges in acceptance of Machine Learning in Banks
3. How to overcome the challenges in adoption of Machine Learning in Banks
4. How to find new use cases of Machine Learning
5. Few current interesting use cases of Machine Learning
Please contact me (shekup@gmail.com) or connect with me on LinkedIn (https://www.linkedin.com/in/shekup/) for more explanation on ML and how it may help your business.
The slides are inspired by:
Survey & interviews done by me with Bankers & Technology Professionals
Presentation from Google NEXT 2017
Presentation by DATUM on Youtube
Royal Society Machine Learning
Big Data & Social Analytics Course from MIT & GetSmarter
Cognitive analytics: What's coming in 2016?IBM Analytics
Cognitive analytics is innovating and evolving rapidly. Expert predictions in this area are essential for organizations that plan to leverage cognitive analytics in their big data analytics strategies in 2016 and beyond. It is the core investment that organizations everywhere should make to stay relevant in the insight economy. IBM is the premier solution provider, with IBM Watson as its flagship cognitive analytics platform, for realizing the opportunities this innovative technology makes possible.
Learn more about IBM Analytics at http://ibm.co/advancedanalytics
Functionalities in AI Applications and Use Cases (OECD)AnandSRao1962
This presentation was given at the OECD Network of AI Specialists (ONE) held in Paris on February 26 and 27. It covers the methodology for assessing AI use cases by technology, value chain, use, business impact, business value, and effort required.
This deck contains the information on how you can use the cognitive service in the Microsoft Bot Framework. Technologies used Azure Bot Framework, Azure Cloud and Cognitive Services. You can configure this bot on multiple channels like Web, Telegram, Skype and many more.
Please find the bot URL: https://insurancebotweb.azurewebsites.net/About
Three big questions about AI in financial servicesWhite & Case
To ride the rising wave of AI, financial services companies will have to navigate evolving standards, regulations and risk dynamics—particularly regarding data rights, algorithmic accountability and cybersecurity.
Ibm cognitive business_strategy_presentationdiannepatricia
IBM Cognitive Business Strategy presentation. Presented by Dianne Fodell and Jim Spohrer at the Cognitive Systems Institute Group Speaker Series call on October 8, 2015.
SmartData Webinar: Cognitive Computing in the Mobile App EconomyDATAVERSITY
Mobility is transforming work and life throughout the planet. Mobile apps--built for a growing range of handhelds, wearables, Internet of Things, and other platforms--are becoming the universal access paths to commerce, content, and community in the 21st century. The app economy refers to this new world where every decision, action, exploration, and experience is continuously enriched and optimized through the cloud-served apps that accompany you everywhere. In this webinar, James Kobielus, IBM's Big Data Evangelist, will discuss the potential of cognitive computing to super-power the emerging app economy. In addition to providing an overview of IBM's Watson strategy for cognitive computing, Kobielus will go in-depth on IBM's strategic partnership with Apple to draw on the strengths of each company to transform enterprise mobility through a new class of apps that leverage IBM’s Watson-based big data analytics cloud and add value to Apple's iPhone and iPad platforms in diverse industries.
Gene Villeneuve - Moving from descriptive to cognitive analyticsIBM Sverige
As the scope of big data rapidly expands, so does the scope of the analytics that are necessary to extract insight from that data. It is simply impossible for humans or indeed rules-based engines to take that information to action. More and more, clients need analytics to make the best decisions possible; or better yet, embed those analytics into processes to automate the decision-making process, which they simply the answers based on the questions being asked at the point of impact. In order to address these rapidly evolving needs, we need to ensure the right analytics capability are deployed to suit each situation, each point of interaction and each decision point within a process. Join this session, and learn how IBM can provide a solution for the varying types of analytics: from descriptive to predictive to prescriptive to cognitive.
Talk presented at the Analytics Frontiers Conference in Charlotte on March 21. The presentation evaluates opportunities and risks of AI and how consumers, businesses, society and governments can mitigate some of the risks.
Ai - Artificial Intelligence predictions-2018-report - PWCRick Bouter
Here’s some actionable advice on artificial intelligence (AI), that you can
use today: If someone says they know exactly what AI will look like and
do in 10 years, smile politely, then change the subject or walk away.
The slide has details on below points:
1. Introduction to Machine Learning
2. What are the challenges in acceptance of Machine Learning in Banks
3. How to overcome the challenges in adoption of Machine Learning in Banks
4. How to find new use cases of Machine Learning
5. Few current interesting use cases of Machine Learning
Please contact me (shekup@gmail.com) or connect with me on LinkedIn (https://www.linkedin.com/in/shekup/) for more explanation on ML and how it may help your business.
The slides are inspired by:
Survey & interviews done by me with Bankers & Technology Professionals
Presentation from Google NEXT 2017
Presentation by DATUM on Youtube
Royal Society Machine Learning
Big Data & Social Analytics Course from MIT & GetSmarter
Cognitive analytics: What's coming in 2016?IBM Analytics
Cognitive analytics is innovating and evolving rapidly. Expert predictions in this area are essential for organizations that plan to leverage cognitive analytics in their big data analytics strategies in 2016 and beyond. It is the core investment that organizations everywhere should make to stay relevant in the insight economy. IBM is the premier solution provider, with IBM Watson as its flagship cognitive analytics platform, for realizing the opportunities this innovative technology makes possible.
Learn more about IBM Analytics at http://ibm.co/advancedanalytics
Functionalities in AI Applications and Use Cases (OECD)AnandSRao1962
This presentation was given at the OECD Network of AI Specialists (ONE) held in Paris on February 26 and 27. It covers the methodology for assessing AI use cases by technology, value chain, use, business impact, business value, and effort required.
This deck contains the information on how you can use the cognitive service in the Microsoft Bot Framework. Technologies used Azure Bot Framework, Azure Cloud and Cognitive Services. You can configure this bot on multiple channels like Web, Telegram, Skype and many more.
Please find the bot URL: https://insurancebotweb.azurewebsites.net/About
Three big questions about AI in financial servicesWhite & Case
To ride the rising wave of AI, financial services companies will have to navigate evolving standards, regulations and risk dynamics—particularly regarding data rights, algorithmic accountability and cybersecurity.
Ibm cognitive business_strategy_presentationdiannepatricia
IBM Cognitive Business Strategy presentation. Presented by Dianne Fodell and Jim Spohrer at the Cognitive Systems Institute Group Speaker Series call on October 8, 2015.
SmartData Webinar: Cognitive Computing in the Mobile App EconomyDATAVERSITY
Mobility is transforming work and life throughout the planet. Mobile apps--built for a growing range of handhelds, wearables, Internet of Things, and other platforms--are becoming the universal access paths to commerce, content, and community in the 21st century. The app economy refers to this new world where every decision, action, exploration, and experience is continuously enriched and optimized through the cloud-served apps that accompany you everywhere. In this webinar, James Kobielus, IBM's Big Data Evangelist, will discuss the potential of cognitive computing to super-power the emerging app economy. In addition to providing an overview of IBM's Watson strategy for cognitive computing, Kobielus will go in-depth on IBM's strategic partnership with Apple to draw on the strengths of each company to transform enterprise mobility through a new class of apps that leverage IBM’s Watson-based big data analytics cloud and add value to Apple's iPhone and iPad platforms in diverse industries.
Gene Villeneuve - Moving from descriptive to cognitive analyticsIBM Sverige
As the scope of big data rapidly expands, so does the scope of the analytics that are necessary to extract insight from that data. It is simply impossible for humans or indeed rules-based engines to take that information to action. More and more, clients need analytics to make the best decisions possible; or better yet, embed those analytics into processes to automate the decision-making process, which they simply the answers based on the questions being asked at the point of impact. In order to address these rapidly evolving needs, we need to ensure the right analytics capability are deployed to suit each situation, each point of interaction and each decision point within a process. Join this session, and learn how IBM can provide a solution for the varying types of analytics: from descriptive to predictive to prescriptive to cognitive.
Talk presented at the Analytics Frontiers Conference in Charlotte on March 21. The presentation evaluates opportunities and risks of AI and how consumers, businesses, society and governments can mitigate some of the risks.
Ai - Artificial Intelligence predictions-2018-report - PWCRick Bouter
Here’s some actionable advice on artificial intelligence (AI), that you can
use today: If someone says they know exactly what AI will look like and
do in 10 years, smile politely, then change the subject or walk away.
Turning AI into Concrete Value: The Successful Implementers' ToolkitCapgemini
A Capgemini study of nearly 1,000 organizations implementing Artificial Intelligence highlights the growth opportunity of AI and counters fears that AI will cause massive job losses in the short term.
Turning AI into concrete value: the successful implementers’ toolkitBen Gilchriest
This research is a pragmatic guide to help organizations in their AI investment decisions, built from an analysis of over 50 AI case studies and a survey of nearly 1,000 senior executives already implementing AI.
Insurance, Industrial Automation, Healthcare and Recruitment projects implemented by Fortifier IT Company. Some of the technologies used during implementation: Artificial Intelligence, text and image recognition, Internet of Things.
Insurance, Industrial Automation, Healthcare and Recruitment projects implemented by Fortifier IT Company. Some of the technologies used during implementation: Artificial Intelligence, text and image recognition, Internet of Things.
Artificial intelligence (AI) currently being used by insurance companies has failed to remove gender bias from the profession’s claims, underwriting and marketing processes.
A Chartered Insurance Institute (CII) report tells insurers they must tackle these gender biases. The report found that the datasets used to train the algorithms which support AI systems are rooted in outdated gender concepts. Algorithms learn by being trained on historic data but the report notes more and more of that data is now unstructured, coming from text, audio, video and sensors.
Yet the report warns embedded in that historic data are decisions based upon historic biases, particularly around gender. The report concluded insurance firms need to prepare a structured response to this issue, starting with visible leadership on tackling gender bias in AI.
Onramp key takeaways:
1) Same Insurtech brutal truths
2) The future of the Insurers will be insurtech
3) Reasons why for adopting IoT in the insurance sector
4) The IoT Insurance Observatory mission
In the year 2014, while e-commerce was majorly a business-to-consumer (B2C) game a platform best constructed for consumer brands and retail transactions, business-to-business (B2B) was barely on the limelight. B2B ordering solutions were very few, pricey, and complex in nature. Because of this, it was difficult for small wholesale distributors and retailers to implement B2B ordering solutions in their businesses.
The reasons why for adopting IoT in the insurance sector are:
1) frequency of interaction
2) value creation
3) knowledge creation
4) sustainability
An incredible opportunity for the insurance sector
Technology tech trends 2022 and beyond Brian Pichman
It's that time of year again, where we get to look ahead and finally have some good news. Tech enthusiast Brian Pichman of the Evolve Project will showcase the latest technology trends and how that impact our learning spaces and spaces at home. It is guaranteed to make you forget about all of 2020 and 2021....well maybe that's a new technology about to be released, the MIB memory eraser. Join this exciting webinar and leave with some high hopes of new technology to explore!
From the conference Future Tech in Insurance at Forsikringsakademiet, nov 15 2016. Defining cognitive and how that is relevant for insurance companies.
how to sell pi coins in all Africa Countries.DOT TECH
Yes. You can sell your pi network for other cryptocurrencies like Bitcoin, usdt , Ethereum and other currencies And this is done easily with the help from a pi merchant.
What is a pi merchant ?
Since pi is not launched yet in any exchange. The only way you can sell right now is through merchants.
A verified Pi merchant is someone who buys pi network coins from miners and resell them to investors looking forward to hold massive quantities of pi coins before mainnet launch in 2026.
I will leave the telegram contact of my personal pi merchant to trade with.
@Pi_vendor_247
How to get verified on Coinbase Account?_.docxBuy bitget
t's important to note that buying verified Coinbase accounts is not recommended and may violate Coinbase's terms of service. Instead of searching to "buy verified Coinbase accounts," follow the proper steps to verify your own account to ensure compliance and security.
The secret way to sell pi coins effortlessly.DOT TECH
Well as we all know pi isn't launched yet. But you can still sell your pi coins effortlessly because some whales in China are interested in holding massive pi coins. And they are willing to pay good money for it. If you are interested in selling I will leave a contact for you. Just telegram this number below. I sold about 3000 pi coins to him and he paid me immediately.
Telegram: @Pi_vendor_247
Currently pi network is not tradable on binance or any other exchange because we are still in the enclosed mainnet.
Right now the only way to sell pi coins is by trading with a verified merchant.
What is a pi merchant?
A pi merchant is someone verified by pi network team and allowed to barter pi coins for goods and services.
Since pi network is not doing any pre-sale The only way exchanges like binance/huobi or crypto whales can get pi is by buying from miners. And a merchant stands in between the exchanges and the miners.
I will leave the telegram contact of my personal pi merchant. I and my friends has traded more than 6000pi coins successfully
Tele-gram
@Pi_vendor_247
USDA Loans in California: A Comprehensive Overview.pptxmarketing367770
USDA Loans in California: A Comprehensive Overview
If you're dreaming of owning a home in California's rural or suburban areas, a USDA loan might be the perfect solution. The U.S. Department of Agriculture (USDA) offers these loans to help low-to-moderate-income individuals and families achieve homeownership.
Key Features of USDA Loans:
Zero Down Payment: USDA loans require no down payment, making homeownership more accessible.
Competitive Interest Rates: These loans often come with lower interest rates compared to conventional loans.
Flexible Credit Requirements: USDA loans have more lenient credit score requirements, helping those with less-than-perfect credit.
Guaranteed Loan Program: The USDA guarantees a portion of the loan, reducing risk for lenders and expanding borrowing options.
Eligibility Criteria:
Location: The property must be located in a USDA-designated rural or suburban area. Many areas in California qualify.
Income Limits: Applicants must meet income guidelines, which vary by region and household size.
Primary Residence: The home must be used as the borrower's primary residence.
Application Process:
Find a USDA-Approved Lender: Not all lenders offer USDA loans, so it's essential to choose one approved by the USDA.
Pre-Qualification: Determine your eligibility and the amount you can borrow.
Property Search: Look for properties in eligible rural or suburban areas.
Loan Application: Submit your application, including financial and personal information.
Processing and Approval: The lender and USDA will review your application. If approved, you can proceed to closing.
USDA loans are an excellent option for those looking to buy a home in California's rural and suburban areas. With no down payment and flexible requirements, these loans make homeownership more attainable for many families. Explore your eligibility today and take the first step toward owning your dream home.
US Economic Outlook - Being Decided - M Capital Group August 2021.pdfpchutichetpong
The U.S. economy is continuing its impressive recovery from the COVID-19 pandemic and not slowing down despite re-occurring bumps. The U.S. savings rate reached its highest ever recorded level at 34% in April 2020 and Americans seem ready to spend. The sectors that had been hurt the most by the pandemic specifically reduced consumer spending, like retail, leisure, hospitality, and travel, are now experiencing massive growth in revenue and job openings.
Could this growth lead to a “Roaring Twenties”? As quickly as the U.S. economy contracted, experiencing a 9.1% drop in economic output relative to the business cycle in Q2 2020, the largest in recorded history, it has rebounded beyond expectations. This surprising growth seems to be fueled by the U.S. government’s aggressive fiscal and monetary policies, and an increase in consumer spending as mobility restrictions are lifted. Unemployment rates between June 2020 and June 2021 decreased by 5.2%, while the demand for labor is increasing, coupled with increasing wages to incentivize Americans to rejoin the labor force. Schools and businesses are expected to fully reopen soon. In parallel, vaccination rates across the country and the world continue to rise, with full vaccination rates of 50% and 14.8% respectively.
However, it is not completely smooth sailing from here. According to M Capital Group, the main risks that threaten the continued growth of the U.S. economy are inflation, unsettled trade relations, and another wave of Covid-19 mutations that could shut down the world again. Have we learned from the past year of COVID-19 and adapted our economy accordingly?
“In order for the U.S. economy to continue growing, whether there is another wave or not, the U.S. needs to focus on diversifying supply chains, supporting business investment, and maintaining consumer spending,” says Grace Feeley, a research analyst at M Capital Group.
While the economic indicators are positive, the risks are coming closer to manifesting and threatening such growth. The new variants spreading throughout the world, Delta, Lambda, and Gamma, are vaccine-resistant and muddy the predictions made about the economy and health of the country. These variants bring back the feeling of uncertainty that has wreaked havoc not only on the stock market but the mindset of people around the world. MCG provides unique insight on how to mitigate these risks to possibly ensure a bright economic future.
how to swap pi coins to foreign currency withdrawable.DOT TECH
As of my last update, Pi is still in the testing phase and is not tradable on any exchanges.
However, Pi Network has announced plans to launch its Testnet and Mainnet in the future, which may include listing Pi on exchanges.
The current method for selling pi coins involves exchanging them with a pi vendor who purchases pi coins for investment reasons.
If you want to sell your pi coins, reach out to a pi vendor and sell them to anyone looking to sell pi coins from any country around the globe.
Below is the contact information for my personal pi vendor.
Telegram: @Pi_vendor_247
Empowering the Unbanked: The Vital Role of NBFCs in Promoting Financial Inclu...Vighnesh Shashtri
In India, financial inclusion remains a critical challenge, with a significant portion of the population still unbanked. Non-Banking Financial Companies (NBFCs) have emerged as key players in bridging this gap by providing financial services to those often overlooked by traditional banking institutions. This article delves into how NBFCs are fostering financial inclusion and empowering the unbanked.
The Evolution of Non-Banking Financial Companies (NBFCs) in India: Challenges...beulahfernandes8
Role in Financial System
NBFCs are critical in bridging the financial inclusion gap.
They provide specialized financial services that cater to segments often neglected by traditional banks.
Economic Impact
NBFCs contribute significantly to India's GDP.
They support sectors like micro, small, and medium enterprises (MSMEs), housing finance, and personal loans.
Introduction to Indian Financial System ()Avanish Goel
The financial system of a country is an important tool for economic development of the country, as it helps in creation of wealth by linking savings with investments.
It facilitates the flow of funds form the households (savers) to business firms (investors) to aid in wealth creation and development of both the parties
Poonawalla Fincorp and IndusInd Bank Introduce New Co-Branded Credit Cardnickysharmasucks
The unveiling of the IndusInd Bank Poonawalla Fincorp eLITE RuPay Platinum Credit Card marks a notable milestone in the Indian financial landscape, showcasing a successful partnership between two leading institutions, Poonawalla Fincorp and IndusInd Bank. This co-branded credit card not only offers users a plethora of benefits but also reflects a commitment to innovation and adaptation. With a focus on providing value-driven and customer-centric solutions, this launch represents more than just a new product—it signifies a step towards redefining the banking experience for millions. Promising convenience, rewards, and a touch of luxury in everyday financial transactions, this collaboration aims to cater to the evolving needs of customers and set new standards in the industry.
BYD SWOT Analysis and In-Depth Insights 2024.pptxmikemetalprod
Indepth analysis of the BYD 2024
BYD (Build Your Dreams) is a Chinese automaker and battery manufacturer that has snowballed over the past two decades to become a significant player in electric vehicles and global clean energy technology.
This SWOT analysis examines BYD's strengths, weaknesses, opportunities, and threats as it competes in the fast-changing automotive and energy storage industries.
Founded in 1995 and headquartered in Shenzhen, BYD started as a battery company before expanding into automobiles in the early 2000s.
Initially manufacturing gasoline-powered vehicles, BYD focused on plug-in hybrid and fully electric vehicles, leveraging its expertise in battery technology.
Today, BYD is the world’s largest electric vehicle manufacturer, delivering over 1.2 million electric cars globally. The company also produces electric buses, trucks, forklifts, and rail transit.
On the energy side, BYD is a major supplier of rechargeable batteries for cell phones, laptops, electric vehicles, and energy storage systems.
3. Discussion agenda
1 Presentations:
Gary Richardson: How will insurers derive value from machine learning
Adrien Cohen: AI & motor claims assessment
Juergen Rahmel: Technical considerations for AI
Alberto Chierici: Chatbots & customer service
David Robson: Enterprise view of AI
2 Questions and Answers
3 Snap Poll – share your view
4. Questions & Answers
How to participate:
If you have a question please type into the messaging area
and send to all participants
Session format:
The moderator will use a combination of his own questions
and those from the audience
10. 10
TRACTABLE MISSION : LEARN EXPERT VISUAL TASKS
WITH ARTIFICIAL INTELLIGENCE
Past 3 years have seen fundamental
breakthroughs in computer vision via
deep learning
Deep learning systems now surpass
human accuracy in certain recognition
tasks
Tech giants (Google, Facebook…) are
applying it to generic visual recognition
tasks for consumer applications
Image classification error rate
Our mission is to identify and build commercially
disruptive applications of computer vision
Our focus is insurance claims
11. 11
TEAM OF 20 BACKED BY SILICON VALLEY VC, UNIQUELY
POSITIONNED IN MOTOR WITH MITCHELL DATASET
Raised one of the largest EU
seed rounds of 2015 from West
Coast Investor
Prof. Z. Ghahramani, head of ML
@ Cambridge both an investor
and advisor
BACKERSTEAM
Partnership with Mitchell in the
US, leading insurance claims
player
Transfer dataset of 350M images
+ estimates: enables training AI
to superhuman performance
Tractable uniquely positioned
with deep learning tech & data
PARTNERSHIP IN THE US
Founding team of 3 with previous $bn exit
R&D team of 10 with 30+ years combined
research and 1000+ citations
12. 12
PRODUCT VISION : HOW TRACTABLE AI WILL CHANGE
P&C INSURANCE
Automated
Bodyshop
Adjustment
Customer
Self Service
Generate preliminary repair estimate at FNOL from photos
Applicable to auto and home
Settle low severity claims in minutes
Flag unnecessary repair procedures from photos
Collaborative workflow with the bodyshop
Contain leakage on high volume low value claims
Total Loss
Triage
Triage between repairable and total loss at FNOL from photos
Avoid unnecessary towing operations and storage fees
Manage policyholder expectations early on in process
Automate analysis of drone footage
Elastic response to claim spike during catastrophic hail events
Maintain efficient cycle times
Roof
inspection
Hail
inspection
Count dents & measure depth from photos
Elastic response to claim spike during catastrophic hail events
Maintain efficient cycle times
1
2
3
4
5
DescriptionProduct
14. 14Dr. Juergen Rahmel
Understanding Artificial Intelligence – a Tool Box
Source: Cognitive Architectures: Research Issues and Challenges by Pat Langley,
John E. Laird and Seth Rogers
Decision Making
Planning
Reasoning
Prediction
Data Intake Processing Interaction
15. 15Dr. Juergen Rahmel
Understanding Artificial Intelligence – a Tool Box
Source: Cognitive Architectures: Research Issues and Challenges by Pat Langley,
John E. Laird and Seth Rogers
Perception
Decision Making
Planning
Reasoning
Prediction
Execution
CommunicationRecognition
Data Intake Processing Interaction
16. 16Dr. Juergen Rahmel
Understanding Artificial Intelligence – a Tool Box
Source: Cognitive Architectures: Research Issues and Challenges by Pat Langley,
John E. Laird and Seth Rogers
Perception
Reflection and Learning
Decision Making
Planning
Reasoning
Prediction
Execution
CommunicationRecognition
Data Intake Processing Interaction
17. 17Dr. Juergen Rahmel
Understanding Artificial Intelligence Integration
Example: A simple ‘Chat Bot’ solution – a talkative FAQ
Reasoning ExecutionRecognition
18. 18Dr. Juergen Rahmel
Understanding Artificial Intelligence Integration
Example: A simple ‘Chat Bot’ solution – a talkative FAQ
recognize simple
keywords
search internal
rule base
reply best possible
predefined
answer
Reasoning ExecutionRecognition
Customer:
“I had a car accident,
what to do now?”
Chat Bot:
“Call Police to record the
case. Later, please submit
case number via your
Insurers Website… ”
Data / Rule Base:
…”opening hours” Mon-Fri …..
...”special offers” Offer a/b/c...
...”accident” next steps ...
...”claim” claim process ....
19. 19Dr. Juergen Rahmel
Understanding Artificial Intelligence Integration
Example: A simple ‘Chat Bot’ solution – a talkative FAQ
recognize simple
keywords
search internal
rule base
reply best possible
predefined
answer
Corporate Network
Reasoning ExecutionRecognition
Customer:
“I had a car accident,
what to do now?”
Chat Bot:
“Call Police to record the
case. Later, please submit
case number via your
Insurers Website… ”
Data / Rule Base:
…”opening hours” Mon-Fri …..
...”special offers” Offer a/b/c...
...”accident” next steps ...
...”claim” claim process ....
20. 20Dr. Juergen Rahmel
Understanding Artificial Intelligence Integration
Example: A complex ‘Chat Bot’ solution – a conversational Advisor
Corporate Network
Reasoning
Recognition
recognize
intention
clarify intention
Communication
Customer Data Product Data
Customer:
“I am thinking about increasing
my family protection”
Customer:
“I want to buy an education
insurance”
21. 21Dr. Juergen Rahmel
Understanding Artificial Intelligence Integration
Example: A complex ‘Chat Bot’ solution – a conversational Advisor
Corporate Network
Reasoning
Recognition
recognize
intention
clarify intention
Communication Communication
identify offering
customize
offering
Planning
Prediction
Reasoning
Decision Making
Customer Data Product Data
Customer:
“I am thinking about increasing
my family protection”
Customer:
“I want to buy an education
insurance”
Chat Bot:
“We propose the following
options in your situation…”
Chat Bot:
“…and the particular
product parameters are ...”
22. 22Dr. Juergen Rahmel
Understanding Artificial Intelligence Integration
Example: A complex ‘Chat Bot’ solution – a conversational Advisor
Corporate Network
Reasoning
Recognition
recognize
intention
clarify intention
Communication Communication
identify offering
customize
offering
Planning
Prediction
Reasoning
Decision Making
Customer Data Product Data
Customer:
“I am thinking about increasing
my family protection”
Customer:
“I want to buy an education
insurance”
Chat Bot:
“We propose the following
options in your situation…”
Chat Bot:
“…and the particular
product parameters are ...”
23. 23Dr. Juergen Rahmel
Understanding Artificial Intelligence Integration
Example: A complex ‘Chat Bot’ solution – a conversational Advisor
Corporate Network
Reasoning
Recognition
recognize
intention
clarify intention
Communication Communication
identify offering
customize
offering
Planning
Prediction
Reasoning
Decision Making
Customer Data Product Data
Customer:
“I am thinking about increasing
my family protection”
Customer:
“I want to buy an education
insurance”
Chat Bot:
“We propose the following
options in your situation…”
Chat Bot:
“…and the particular
product parameters are ...”
33. Artificial Intelligence in the Insurance Enterprise
David Robson - IBM Watson Group
A one minute introduction to Watson: https://www.youtube.com/watch?v=6SNs9kvRWSA
Modern AIs can ….
Read Natural Language
• News, policies, fact sheets, web sites etc
• Listen and speak
Understand
• understand what it has read or heard and retain this
knowledge at huge scale
Apply Knowledge
• In conversation with people
• Making decisions (medicine, underwriting etc)
Learn with Experience
• Train with experts and during operation
• Improves with experience and feedback
Machine Learning
Deep Learning
Natural Language Processing
34. Common use cases for AI in Insurance
Client Engagement Underwriting Claims management
Client Insight Image recognitionDiscovery
35. Visual Recognition
Analyzes the visual appearance
of images or video frames to
understand what is happening
Language Translator
Translate text from one language
to another
Personality Insights
Understand and engage users on
their own term based on their
personalities and values
Conversation
Hold natural language
conversations with both your
external and internal customers
Speech to Text
Provides highly accurate, low
latency speech recognition
capabilities
Text to Speech
Synthesizes natural-sounding
speech from text
Message Resonance
Communicate with people with a
style and words that suits them
Discovery
Add a cognitive to applications
to identify patterns, trends and
actionable insights
Relationship Extraction
Intelligently finds relationships
between sentences components
(nouns, verbs, subjects, objects)
Tradeoff Analytics
Helps make better choices under
conflicting goals with smart
visualizations & recommendations
Document Conversion
Converts a single HTML, PDF,
or Mic. Word™ document into a
normalized HTML, plain text
A cognitive platform
Tone Analyser
Leverage cognitive analysis to
identify a variety of tones at
sentence or document level
Alchemy Data News
Provides access to an AI
enriched, curated dataset of news
and blog content
DATA
Face Detection/Recognition
Returns the position, age, gender,
and, in the case of celebrities, the
identities of the people in the
photo
Alchemy API
Enable businesses to build apps
that understand the content and
context of text online
36. 2
36
Questions & Answers
How to participate:
If you have a question please type into the messaging area
and send to the presenters
Session format:
The moderator will use a combination of his own questions
and those from the audience
37. Snap Poll3
37
Q. Which of the following use cases for AI / Machine Learning
do you find most compelling
1. Educating consumers about insurance
2. Selling insurance
3. AI as an engagement tool to retain and service customers
4. Managing the claims process and identifying fraud
5. Risk Management & Prevention Advisory services
6. Other
How to participate:
Just respond to the question when it appears on your screen
38. Announcements
Preregistration Open
London 20TH Sept / Singapore 2nd Nov
Following the success of our first Asia conference last year, we will be holding our second Asia annual conference in Singapore
on 2nd November 2017
Our first annual European conference will be held in London on 20th September 2017
Pre-registration for both events is available NOW:
http://asia2017.the-digital-insurer.com/
http://europe2017.the-digital-insurer.com/
Apply For An Award
Applications are now open for Europe and Asia awards
Award categories include the Start-up Insurtech Award and Insurance Innovation Award
Award finalists will present their innovations and solutions at the conferences. The winners will be determined via a live vote
on the conference app from all the attendees
Nominate yourself today via the event website
Entries close on the 5th May for Europe and 26th May for Asia
39. Post webinar activities
Recording will be emailed to registered participants
Next Webinar will be on 17th May 2017 – Digital Transformation Strategies
Register on our website: https://www.the-digital-insurer.com/event/digital-
insurer-webinar-incumbents-fight-back-digital-transformation-strategies/
Please give us your feedback
If you would like to follow up with any of the panelists
- Simon Phipps: simon.phipps@kpmg.com
- Andrew Dart: andrew.dart@the-digital-insurer.com
- Gary Richardson: gary.richardson@kpmg.co.uk
- Adrien Cohen: adrien@tractable.io
- Juergen Rahmel: jr@ietc.hk
- Alberto Chierici: alberto.chierici@spixii.ai
- David Robson: david_robson@uk.ibm.com
Editor's Notes
Introducing the panelists
Introducing the discussion agenda
9 world class ML res from leading UK labs
AZ, Peter Dayan, in particular ZG MLG
Work closely w/ Z, proud to have as investor & advisor
30 yrs res experience, 1k citations, expertise lies in DL IL CV
9 world class ML res from leading UK labs
AZ, Peter Dayan, in particular ZG MLG
Work closely w/ Z, proud to have as investor & advisor
30 yrs res experience, 1k citations, expertise lies in DL IL CV
9 world class ML res from leading UK labs
AZ, Peter Dayan, in particular ZG MLG
Work closely w/ Z, proud to have as investor & advisor
30 yrs res experience, 1k citations, expertise lies in DL IL CV