1. AI is helping life insurance companies improve processes like underwriting and claims handling by making them more efficient.
2. One case study showed how using consented health data and predictive models allowed underwriting decisions to be made in hours instead of weeks.
3. Another case study demonstrated how combining human and machine pattern detection helped identify suspicious claims patterns that could indicate fraud.
ML, AI, DL, DS, AA - are all of these the same or are they different? So much confusion. Learn how ML can be applied (with Insurance as an case study).
The insurance industry – from product development to underwriting to claims – is being fundamentally transformed by AI technologies. Although some companies are investing aggressively in AI to slash costs while also enhancing the customer experience, most insurers will need to accelerate their efforts or risk discovering that it has become too late to catch up.
A View on AI in Insurance - Chris Madsen - H2O AI World London 2018Sri Ambati
This talk was recorded in London on October 30th, 2018 and can be viewed here: https://youtu.be/LFVIGMMlfhI
A view on what is driving AI and ML developments in insurance and why.
• What is driving the change in insurance and why is AI/ML so important?
• What does the future look like?
• Which AI/ML use cases are being worked on in the industry?
• Which ones are needed?
Chris Madsen is Chairman and CEO of Blue Square Re N.V., Aegon’s internal reinsurer and a company he co-founded in 2010.
Mr. Madsen holds a Masters in Engineering from Princeton University in Princeton, USA. His undergraduate degree is in Mathematics and Economics. He is an Associate of the Society of Actuaries, a Member of the American Academy of Actuaries and a Chartered Financial Analyst.
He started his professional career in New York in 1990, working as Consulting Actuary and later Principal. Mr. Madsen has published numerous articles on innovative underwriting risk solutions and is a frequent speaker on the topic and related developments.
Mr. Madsen is an avid proponent and driver of integrating start-up and insurtech expertise into insurance solutions - including internet-of-things applications as well as blockchain initiatives such as “B3i”. He is also responsible for the ground-breaking longevity solutions that Aegon brought to the capital markets totalling over EUR 20bn of reserves.
Listen to an experienced, global panel of insurance professionals present, discuss and answer your questions on the theme of “Data & Analytics from a Life & Health perspective”.
Brought to you by The Digital Insurer and sponsored by KPMG.
INFOGRAPHIC: Fixing the Insurance Industry - how big data can transform custo...Capgemini
Insurers are facing a moment of truth. Customer satisfaction levels have hit worryingly low levels. According to a survey conducted by Capgemini in 2014, less than a third of customers globally are satisfied with the services of their insurance providers. Traditional insurers also face competition from new entrants who are determined to meet customer expectations. Non-traditional competitors, such as ecommerce majors and technology startups, are leveraging their data-rich customer interactions to create and sell insurance products.
Surprisingly, insurers seem to have overlooked the impact of Big Data on improving customer experience as they often focus their Big Data efforts on detecting fraudulent claims and improving underwriting profitability. In fact, only 12% of insurers consider the enhancement of customer experience as a top Big Data priority. This is startling given the poor levels of customer satisfaction in the insurance industry.
ML, AI, DL, DS, AA - are all of these the same or are they different? So much confusion. Learn how ML can be applied (with Insurance as an case study).
The insurance industry – from product development to underwriting to claims – is being fundamentally transformed by AI technologies. Although some companies are investing aggressively in AI to slash costs while also enhancing the customer experience, most insurers will need to accelerate their efforts or risk discovering that it has become too late to catch up.
A View on AI in Insurance - Chris Madsen - H2O AI World London 2018Sri Ambati
This talk was recorded in London on October 30th, 2018 and can be viewed here: https://youtu.be/LFVIGMMlfhI
A view on what is driving AI and ML developments in insurance and why.
• What is driving the change in insurance and why is AI/ML so important?
• What does the future look like?
• Which AI/ML use cases are being worked on in the industry?
• Which ones are needed?
Chris Madsen is Chairman and CEO of Blue Square Re N.V., Aegon’s internal reinsurer and a company he co-founded in 2010.
Mr. Madsen holds a Masters in Engineering from Princeton University in Princeton, USA. His undergraduate degree is in Mathematics and Economics. He is an Associate of the Society of Actuaries, a Member of the American Academy of Actuaries and a Chartered Financial Analyst.
He started his professional career in New York in 1990, working as Consulting Actuary and later Principal. Mr. Madsen has published numerous articles on innovative underwriting risk solutions and is a frequent speaker on the topic and related developments.
Mr. Madsen is an avid proponent and driver of integrating start-up and insurtech expertise into insurance solutions - including internet-of-things applications as well as blockchain initiatives such as “B3i”. He is also responsible for the ground-breaking longevity solutions that Aegon brought to the capital markets totalling over EUR 20bn of reserves.
Listen to an experienced, global panel of insurance professionals present, discuss and answer your questions on the theme of “Data & Analytics from a Life & Health perspective”.
Brought to you by The Digital Insurer and sponsored by KPMG.
INFOGRAPHIC: Fixing the Insurance Industry - how big data can transform custo...Capgemini
Insurers are facing a moment of truth. Customer satisfaction levels have hit worryingly low levels. According to a survey conducted by Capgemini in 2014, less than a third of customers globally are satisfied with the services of their insurance providers. Traditional insurers also face competition from new entrants who are determined to meet customer expectations. Non-traditional competitors, such as ecommerce majors and technology startups, are leveraging their data-rich customer interactions to create and sell insurance products.
Surprisingly, insurers seem to have overlooked the impact of Big Data on improving customer experience as they often focus their Big Data efforts on detecting fraudulent claims and improving underwriting profitability. In fact, only 12% of insurers consider the enhancement of customer experience as a top Big Data priority. This is startling given the poor levels of customer satisfaction in the insurance industry.
This presentation provides a brief insight into the need to undertake an analytics project, particularly as it pertains to claims management and fraud. To this end the presentation will touch on the general challenges confronting the property and casualty insurance industry, as well as the challenges and lessons learnt from early adopters of business intelligence. In the face of these challenges analytics holds the potential to generate substantial value as evidenced by several short case study examples. The presentation concludes with a look at the issue of fraud as it pertains to the industry and some of the metrics that are influenced by it.
The presentation draws extensively, and focuses on, the work and viewpoints from industry participants including; Accenture, IBM, Ernst & Young, Strategy Meets Action, Ordnance Survey, Gartner, Insurance Institute of America, American Institute for Chartered Property Casualty Underwriters, International Risk Management Institute and John Standish Consulting. References are included on each slide as well as on the “References” slides at the end of the presentation.
By taking a ‘rapid-fire’ directional approach, public service organizations can quickly identify key issues and insights that reveal new potential value or even suggest a beneficial change in strategic direction. Learn more about Unplanned Analytics and the FASTT Methodology
The insurance industry has remained much the same for more than 100 years, but over the past decade it has seen a number of exciting new innovations and new business models.
2015 SOA Annual Meeting - Beagle Street and Teachers LifeKevin Pledge
Presentation by Chris Samuel featuring two case studies - Beagle Street (UK) and Teachers Life (Canada), discussing how their approach from selling online is different from rest of the market and how they are making an impact.
According to research findings released by NTT DATA Services, voice-controlled virtual assistants such as Amazon’s Alexa and Apple’s Siri will influence the future of online and mobile interactions between consumers and their financial services institutions and insurance carriers.
Accenture Compliance Risk Study 2017: Financial Servicesaccenture
The Accenture 2017 Compliance Risk Study indicates the transformation journey for Compliance has entered a new phase in the face of the digital age and escalating margin and performance pressures. Review our infographic to learn more, or download study results: https://accntu.re/2oyr1eG
Unbundling the Insurance Value Chain - Disruption in the Insurance Sector - The 7th. International Istanbul Insurance Confrence - Prof. Dr. Selim YAZICI (2016)
The Pulse of Pensions: What Members Really Think of Their Pension Plans and R...accenture
We asked nearly 2,800 public and private employees with defined benefit, defined contribution and hybrid plans their views on top-of-mind pensions and retirement topics.
Accenture Digital Health Technology Vision 2018accenture
Explore Accenture's Digital Health Tech Vision 2018 report, showcasing five health IT trends that are going to redefine how intelligent enterprises of the future will work.
Please find here our first Insurance Review on Digital Disruption of the Insurance sector. We've put together the best, most shared and liked articles on this topic. All articles have been published before on our Financial Services blog
Global consumers want similar things when it comes to personal data. In this slideshow, we explore the sentiments about data privacy expressed by people across countries, industries, and data types.
For more information, please check out the BCG report, "The Trust Advantage" (http://on.bcg.com/1gr9j5P) and visit the "Big Data and Beyond" section of bcg.perspectives (http://on.bcg.com/1g7tpgc).
Webinar Deck for 2018 Health Technology & Impact on InsuranceThe Digital Insurer
Listen to an experienced, global panel of insurance professionals present, discuss and answer your questions on the theme of “Health Technology & Impact on Insurance”.
Brought to you by The Digital Insurer and sponsored by KPMG.
Consumer trust has become the new battleground for digital success. To win, organizations need to master the fundamentals of data ethics, manage the "give-to-get" ratio and solve the customer trust equation, our recent research reveals.
This presentation provides a brief insight into the need to undertake an analytics project, particularly as it pertains to claims management and fraud. To this end the presentation will touch on the general challenges confronting the property and casualty insurance industry, as well as the challenges and lessons learnt from early adopters of business intelligence. In the face of these challenges analytics holds the potential to generate substantial value as evidenced by several short case study examples. The presentation concludes with a look at the issue of fraud as it pertains to the industry and some of the metrics that are influenced by it.
The presentation draws extensively, and focuses on, the work and viewpoints from industry participants including; Accenture, IBM, Ernst & Young, Strategy Meets Action, Ordnance Survey, Gartner, Insurance Institute of America, American Institute for Chartered Property Casualty Underwriters, International Risk Management Institute and John Standish Consulting. References are included on each slide as well as on the “References” slides at the end of the presentation.
By taking a ‘rapid-fire’ directional approach, public service organizations can quickly identify key issues and insights that reveal new potential value or even suggest a beneficial change in strategic direction. Learn more about Unplanned Analytics and the FASTT Methodology
The insurance industry has remained much the same for more than 100 years, but over the past decade it has seen a number of exciting new innovations and new business models.
2015 SOA Annual Meeting - Beagle Street and Teachers LifeKevin Pledge
Presentation by Chris Samuel featuring two case studies - Beagle Street (UK) and Teachers Life (Canada), discussing how their approach from selling online is different from rest of the market and how they are making an impact.
According to research findings released by NTT DATA Services, voice-controlled virtual assistants such as Amazon’s Alexa and Apple’s Siri will influence the future of online and mobile interactions between consumers and their financial services institutions and insurance carriers.
Accenture Compliance Risk Study 2017: Financial Servicesaccenture
The Accenture 2017 Compliance Risk Study indicates the transformation journey for Compliance has entered a new phase in the face of the digital age and escalating margin and performance pressures. Review our infographic to learn more, or download study results: https://accntu.re/2oyr1eG
Unbundling the Insurance Value Chain - Disruption in the Insurance Sector - The 7th. International Istanbul Insurance Confrence - Prof. Dr. Selim YAZICI (2016)
The Pulse of Pensions: What Members Really Think of Their Pension Plans and R...accenture
We asked nearly 2,800 public and private employees with defined benefit, defined contribution and hybrid plans their views on top-of-mind pensions and retirement topics.
Accenture Digital Health Technology Vision 2018accenture
Explore Accenture's Digital Health Tech Vision 2018 report, showcasing five health IT trends that are going to redefine how intelligent enterprises of the future will work.
Please find here our first Insurance Review on Digital Disruption of the Insurance sector. We've put together the best, most shared and liked articles on this topic. All articles have been published before on our Financial Services blog
Global consumers want similar things when it comes to personal data. In this slideshow, we explore the sentiments about data privacy expressed by people across countries, industries, and data types.
For more information, please check out the BCG report, "The Trust Advantage" (http://on.bcg.com/1gr9j5P) and visit the "Big Data and Beyond" section of bcg.perspectives (http://on.bcg.com/1g7tpgc).
Webinar Deck for 2018 Health Technology & Impact on InsuranceThe Digital Insurer
Listen to an experienced, global panel of insurance professionals present, discuss and answer your questions on the theme of “Health Technology & Impact on Insurance”.
Brought to you by The Digital Insurer and sponsored by KPMG.
Consumer trust has become the new battleground for digital success. To win, organizations need to master the fundamentals of data ethics, manage the "give-to-get" ratio and solve the customer trust equation, our recent research reveals.
Consumer trust has become the new battleground for digital success. To win, organizations need to master the fundamentals of data ethics, manage the "give-to-get" ratio and solve the customer trust equation, our recent research reveals.
BDW16 London - Amjad Zaim, Cognitro Analytics: How Deep is Your Learning Big Data Week
Deep learning, a new class of AI (Artificial Intelligence) algorithms is making big promises to unlock an unprecedented level of intelligence from voluminous forms of structured and unstructured data produced from online data factories and internet-enabled smart devices. But despite the big hype about big data, deep learning and AI in general, less than half of the projects undertaking by companies looking to push the boundaries of analytics through data science fail to deliver the expected results according to a recent Gartner’s study. From our experience, a major factor in this failure is the myopic view of technology coupled with lack of understanding of what’s needed to build an ecosystem of analytics technology architecture, talent resources and systems of governance. We present a national e-health analytics transformation case study where we describe the recipe for how we envision analytics to be able to create the spin-off factor to reshape and revolutionize the industry landscape through our tested and proven framework of “Transform and Digitize”, Inform and Contextualize”, Embed and Institutionalize, “Innovate and Evangelize”. For organizations, large and small, to deepen their learning and win with analytics a holistic approach has to address all the underlying components across the full analytics value chain…. it’s a never-ending journey!
As more and more companies in a range of industries adopt machine learning and more advanced AI algorithms, the ability to provide understandable explanations for different stakeholders becomes critical. If people don’t know why an AI system made a decision, they may not trust the outcome.
The presentation Azeem Azhar gave at the December Hacking Finance Breakfast.
Find Azeem online: http://www.exponentialview.co
View his talk on youtube: https://youtu.be/38_1hmkI9kA
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
September 2014 | Social Media and Mobile Tech Paige Rasid
Early-stage companies pitch their ideas and businesses at CVG's Second Thursday Social Media and Mobile Tech event. Followed by a presentation by SocialFly, focused on trends in social media and how they impact your business.
For latest information see http://www.blionline.org/ao
Recent research from the AICPA says that the business environment for CPAs and their clients will be characterized by “unprecedented, massive and highly accelerated change” through 2025. To thrive in this new age of hyper-change and growing uncertainty, it is now an imperative to learn a new competency--how to accurately anticipate the future. The key to success in this fast-changing environment is to commit to changing before you are being forced to. This session will show how to anticipate these trends and move from being a crisis manager to an opportunity manager. At the end of the session participants will set actionable steps to elevate and accelerate their firm's strategy.
- Anticipate marketplace trends that will shape future markets
- Understand emerging innovation faster
- Identify opportunities
- Develop clear actionable steps to accelerate growth for the organization and its customers
Enabling Learning Agility in an Era of Accelerated Changearun pradhan
How do we enable a culture of continuous learning? How do we support agile, adaptive and innovative thinking when change is business as usual? And how do we future-proof ourselves in the face of the robot apocalypse? This presentation stems from my work developing Learn2LearnApp.com and serves as a primer in developing learning agility for individuals and organisations.
Similar to P 01 ins_analytics_ai_in_life_case_studies_2017_10_16_v12 (20)
P 02 ta_in_uw_transformation_2017_06_13_v5Vishwa Kolla
Text Analytics can be fun, useful and distracting. It is not just about the tools, but about how to use tools to drive business outcome. In this deck, you will get a sneak peak into some uses of text analytics in Life Insurance Transformation
P 02 internal_data_first_2017_04_22_v6Vishwa Kolla
Data is the new oil and Analytics is the combustion engine. Internal data plays a special role in every organization. See how one can become internal data rich and move the value needle. Through what we call thoughtful data engineering, we found good data trumped good models time and again.
Crossing the Digital Chasm - Applying Advanced Analytics in acquiring, nurtur...Vishwa Kolla
We are at a point of inflection of embedding Advanced Analytics everywhere.
If you are interested in learning about:
1) Why should we cross the Cigital Chasm
2) Which of the areas should one focus
3) Which of the problems should one focus on
4) What are the opportunities / challenges / mitigations
then this is for you.
Big Data and Analytics - Why Should We Care?Vishwa Kolla
Big Data is Big and it is easy to get lost. If you are interested in a primer on what it is all about and how you can get started on the analytics, this deck will help you scratch the surface.
If you are interested in learning to communicate better (clearly, concisely and crisply) and in learning to talk like an executive, this deck is a starter for you.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
3. 3
BIG DATA or ANALYTICS or DATA SCIENCE or AI or AA – WHAT IS IT?
CAMPAIGN NUDGE OPS - INTEG
APPS APPLICATIONS BI
STRATEGY INSIGHTS RECOMMEND
Data Math
Code
AA = COMBINE DATA AND MATH USING CODE TO DRIVE BUSINESS VALUE
4. 4
2001 – 2013 CAGR Revenue
(Firm | Industry)
Source: 2001 – 2013 Revenue figures from Capital IQ
3%
3%
3%
1%
5%
7%
7%
8%
10%
12%
INTEGRATING AI EFFECTIVELY UNLOCKS VALUE
5. 5
AI IS VERY OLD
Source: https://blogs.nvidia.com/blog/2016/07/29/whats-difference-artificial-intelligence-machine-learning-deep-learning-ai/
Most
Operate
here
7. 7
COMPUTATIONAL POWER IS INCREASING EXPONENTIALLY
Number of
Calculations
Per Second
Per $1000
Source: The zettabyte era: Trends and analysis, Cisco, updated June 7, 2017’ United Nations; MMC Ventures; Nvidia;
McKinsey Global Institute analysis
8. 8
ALGORITHMS ARE GETTING BETTER
Source: The zettabyte era: Trends and analysis, Cisco, updated June 7, 2017’ United Nations; MMC Ventures; Nvidia;
McKinsey Global Institute analysis
12. 12
AI SYSTEMS MAKE IT REAL
IOT, RPA, AUTONOMOUSML, DL
VISION & LANGUAGE CHAT BOTS
TARGETING UNDERWRITING CLAIM HANDLING
CYBER SECURITYFRAUD
CALL CENTER APP FORM
EDA / LOOKUPS CLAIMS
ADJUDICATION
APS MEETINGS
CONNECTED
HOME
CONNECTED
HEALTH
OCR
CONNECTED
CARS
MORTALITY
RISK
MORBIDITY
RISK
ANNOTATION
PAY AS
YOU GO
NOT EXHAUSTIVE
14. Source: Suncorp Group, The Changing Face of the Insurance Customer, 2013
Can I try
before I
buy?
What are my
friends doing?
I want a seamless
experience across
devices
I want options How does this
help me?
I want to be
valued
I prefer
Value to
Brand
I want to buy in 2
days
SATISFY THE SEGMENT OF 1
15. 15
USE CASES IN LIFE INSURANCE
PROSPECTING NURTUREACQUISITION
MARKET
SEGMENTS
CUSTOMER
SEGMENTS
LIKELY TO [*]
MEDIA
MIX
CHANNEL
SURVEY
ANALYTICS
CROSS / UP-
SELL
OCR
MISREP
LIKELIHOOD
MORTALITY
APS
SUMMARY
FLUIDLESS
SMOKER
LIKELIHOOD
MORBIDITY
CHURN
NEXT BEST
OFFER
CLAIM
LIKELI-
HOOD
JOURNEY
CLAIM
SEVERITY
NEXT BEST
ACTION
FRAUD
>>
TEXT
ANALYTICS
OPTIMIZE
NEXT LIKELY
ACTION
WELLNESS
IOT
ANALYTICS
NPS
ANOMALY
>>
18. 18
“Life insurance ranks at the top of the list of things consumers
know they probably should buy, but get no personal enjoyment
from whatsoever. There's just no happy way to look at life
insurance. In the best-case scenario, life insurance is just another
bill to pay. And in the worst case, your family collects the
benefits, but unfortunately you're dead.”
Source: USA Today, Knowing when you need life insurance, September 19, 2013
22. 22
Capitalism is under siege. Diminished trust in business is
causing political leaders to set policies that sap
economic growth … Business is caught in a vicious
circle … The purpose of the corporation must be
redefined around …
CREATING SHARED VALUE
Michael E. Porter and Mark Kramer, Jan-Feb 2011
24. 24
AI HELPS MAKE UW PROCESS MORE EFFICIENT
Decision
Acquired
Scheduled
UnderwriterApplicant Part I
Typically
3-6 weeks
Process
Bottle
neck
Traditional Process
End to End Turn Around Time = Hours to 3 - 6 weeks
Consent
Proxy for Cholesterol,
Glucose, Nicotine
Likely to misrepresent
Adjustment for Height
and Weight
Other issues found
after roll out
Encourages healthy
people to apply
25. 25
MAN – MACHINE COMBO SPEEDS UP SUSPICIOUS PATTERN DETECTION
not pay NOT PAYING
not payable NOT PAYING
not payble NOT PAYING
not paycheck NOT PAYING
not payment NOT PAYING
not payout NOT PAYING
not payroll NOT PAYING
payment not NOT PAYING
absence pay NOT PAYING
absent pay NOT PAYING
withhold payment NOT PAYING
pay unpaid NOT PAYING
unpaid pay NOT PAYING
Check for keyword
‘Not Paying’
Use deep learning
to find exact
words / patterns
Identify useful patterns
Identify claims associated with
the identified patterns
Business checks
flagged cases
Reports
cases to
BUIBusiness uses
expert knowledge
to provide directional
guidance
Machine
only
Man
+
Machine
Use deep learning
to find similar
words/patterns
Reports cases
To BUI
Use all
unstructured text
as input to DL
Select
A few
datasets