Actuarial Innovation & Technology Resources
Self-learners on how technology impacts the actuarial landscape can find below a list of curated articles on various technology aspects. These documents were selected by volunteers for their learning content, in order to collectively cover the desired topic. Please contact research@soa.org for comments or suggestions.
Artificial Intelligence - Introduction
Artificial Intelligence - Insurance Industry
Autonomous Vehicles
Big Data Solutions
Blockchain
Cloud Computing
Cyber Risk / Cyber Insurance
Data Analytic Tools
InsurTech Financing
Internet of Things
Machine Learning
Personal Health Monitoring / Wearable Devices
Predictive Analytics
Software Development/Management/Training
Telematics
Usage Based Insurance
Virtual Reality
Artificial Intelligence - Introduction
AI ethics: A business imperative for boards and C-suites
AI: Past, Present, and Future
Shankar Vaidyanathan
SOA, December 2018. PDF. 7 pgs.
The purpose of this report is to demonstrate how artificial intelligence applications have grown since their infancy and invite the reader to consider the vast data at our disposal for the future.
Bot.Me: A revolutionary partnership How AI is pushing man and machine closer together
Anand Rao, Matthew Lieberman
Research & Insights. April 2017. PDF. 18 pgs.
We are right now at the human 2.0 era that AI works as a assisted intelligence, augmented intelligence and autonomous intelligence in every field. One potential exploration for AI is to become a great equalizer while it breaks the limitation of traditional service, provide better service with lower the cost at the same time.
Reconstructing work: Automation, artificial intelligence, and the essential role of humans
Peter Evans-Greenwood, Harvey Lewis, Jim Guszcza
Deloitte Review. July 2017, Iss 21. PDF. 21 pgs.
If we’re to draw a line between human and machine, then it is the distinction between creating and using knowledge. Facing with the rapid development of AI industry, we are peddling in a new era, integrating human and AI.
Artificial Intelligence - Insurance Industry
Read why algorithms we can’t understand can eliminate bias and make insurance fairer.
Daniel Schreiber
Linked-in. December 2019.
By assigning risk on an individual basis and validating the assessed risk against the loss ratio, it is possible for AI-pricing to assign risks on an individual basis and so provide fairer pricing to everyone by avoiding bias.
Breaking through the issues preventing AI adoption in insurance
Neal Silbert
Insurance Business. February 2019.
AI has the potential to help underwriters better understand their customers, improve risk differentiation and establish substantially more accurate pricing. The development of Automated Machine Learning (Auto ML) has emerged as a multi-needed solution. This new level of automation allows actuaries to use Auto ML with fewer days of training in order to increase the capacity to solve problems.
Commercial insurers primed for intelligent automation
Day Bishop and David Ovenden
Emphasis. January 2018.
AI currently provides sophisticated automation and real-time decision support in the commercial. The most common approach is Robotic process automation (RPA), which deliver consistent, accurate and informed decisions in underwriting, pricing and claims.
Humanizing Insurance Claims with Artificial Intelligence
Insurance Nexus. September 2018. Video. 1 hour.
This video mainly discusses how AI technology will help the improve the customer side of the insurance industry. Insurance customers demand real-time, personalized and omnichannel claims. At the same time, customers are increasingly craving a human connection, and to be listened to as a unique individual, not just a number in a database.
Insurance 2030—The impact of AI on the future of insurance
Ramnath Balasubramanian, Ari Libarikian, and Doug McElhaney
McKinsey & Company. April 2018. PDF.
In the revolution of Artificial Intelligence, insurance will shift from the current state of “detect and repair” to “predict and prevent”, transforming every aspect of the industry in the process. Facing 4 main AI technology trends, the insurance value chain will change dramatically at about 2030. How does the role of the insurance agents, underwriters, claimers change? How dees the insurance industry prepare for this change?
Autonomous Vehicles
Is your car a bounty hunter?
Hannah Smith
The Fast Lane: What Driverless Cars Mean for Innovation and Risk
The One Brief
It’s coming quickly down the road: a world where we can get in a car anytime we want to but don’t own one. Where we’re all passengers. Where accidents are drastically reduced, and we don’t have to worry about dangerous drivers on the road.
The Race to Autonomous Driving: Winning American Consumers' Trust
Craig A. Giffi, Joe Vitale, Ryan Robinson, Gina Pingitore PhD.
Deloitte Review. January 2017.
Are US consumers ready for self-driving cars? Our survey shows that they’re increasingly interested in automation, particularly if it improves safety. The bad news: They’re less and less willing to spend their own money to make the future of mobility a reality.
A Reality Check on Advanced Vehicle Technologies
Craig A. Giffi, Joe Vitale, Thomas Schiller, Ryan Robinson
Deloitte Review. January 2018.
The idea of self-driving and electrified vehicles is gaining acceptance among global consumers, but is this enough to make our utopian dreams come true?
Big Data Solutions
Google Secretly Tests Medical Records Search Tool On Nation’s Largest Nonprofit Health System
Forbes
Google and Ascension have been partnering to allow Google to apply its deep-learning AI know-how to Ascension’s electronic health data so as to try and predict variables such as patient outcomes and length of hospital stays.
Actuaries Look Beyond the Hype to Find the Promise in Big Data
Kate Niswander
Casualty Actuarial Society. December 2014.
How big data has changed the industry.
Big Data Analytics: A Practical Application for MPL Insurers
Chad C. Karls
Insight. January 2016. PDF. 5 pgs.
Defense cost trends in medical professional liability (MPL) have significantly outpaced indemnity trends to the point where, for many companies, defense costs have become their single largest expenditure. How do rising defense costs in the medical professional liability industry fit into the broader discussion about big data analytics?
Big Data: Big Opportunity or Big Risk for Actuaries?
Jenny Lyon
Actuaries Digital. March 2016
‘Big Data: Big Opportunity or Big Risk for Actuaries’ was the title of the final Plenary session at the 2016 IFoA Asia Conference. In addition, there were two sessions which addressed big data or data analytics, highlighting the level of interest in this field for actuaries globally.
Big Data in Practice
Sonal Shah
The Actuary. December 2016.
Book review presents case studies of diverse companies embracing the use of big data analytics.
Insurance Big Data - Float Like a Butterfly, Sting Like a Bee
Elinor Friedman, Andrew Harley and Klayton Southwood
Emphasis. August 2016. PDF. 4 pgs.
Recent Willis Towers Watson surveys in the U.S. have shown that P&C and life insurers in developed markets are taking seriously the potential of big data and predictive analytics to improve their businesses. Nimbleness and agility, rather than brute force, are likely to be key to realizing that potential.
Predictably Inaccurate: The Prevalence and Perils of Bad Big Data
John Lucker, Susan K. Hogan, Trevor Bischoff
Deloitte Review. July 2017.
When big data contains bad data, it can lead to big problems for organizations that use that data to build and strengthen relationships with consumers. Here are some ways to manage the risks of relying too heavily—or too blindly—on big data sets.
What data science means for the future of the actuarial profession: Abstract of the London Discussion
British Actuarial Journal, Vol. 23. 2018.
Summary of a meeting discussion on big data issues for actuaries.
Blockchain
Blockchain—Is The Newest Kid On The Block Going To Be All Right?
By Helen Duzhou and Jeff Guo
Conceptualizing Blockchains: Characteristics & Applications
Karim Sultan, Umar Ruhi, and Rubina Lakhani
11th IADIS International Conference Information Systems 2018. 2018. PDF. 9 pgs.
This paper presents an overview of blockchain technology, identifies the blockchain’s key functional characteristics, builds a formal definition, and offers a discussion and classification of current and emerging blockchain applications.
A method for obtaining digital signatures and public-key cryptosystems
R. L. Rivest, A. Shamir, L. Adleman
Association for Computing Machinery. Sept. 1, 1977. PDF. 15 pgs.
An encryption method is presented with the novel property that publicly revealing an encryption key does not thereby reveal the corresponding decryption key.
An Overview of Blockchain Technology: Architecture, Consensus, and Future Trends
Zibin Zheng, Shaoan Xie, Hong-Ning Dai, Xiangping Chen, Huaimin Wang
2017 IEEE 6th International Congress on Big Data. June, 2017. PDF. 8 pgs.
This paper presents a comprehensive overview on blockchain technology. We provide an overview of blockchain architecture firstly and compare some typical consensus algorithms used in different blockchains.
Understanding Blockchain Technology and How to Get Involved
Carmen Holotescu
The 14th International Scientific Conference eLearning and Software for Education. April 2018. PDF. 8 pgs.
Offering a fresh perspective over blockchain technology and educational initiatives, the paper could be useful for educational actors and policy makers wanting to explore and to integrate blockchain in institutional projects and curricula.
What is Blockchain Technology? A Step-by-Step Guide for Beginners
Blockgeeks. March 2019.
This is a nice layperson explanation of blockchain for anyone with little to no familiarity. There is an online tutorial, video clips, and visual examples of how it works.
Cloud Computing
Making Cloud a Business Asset
Chad Duncan, James Struntz
Insurance Cloud. 2018. PDF. 20 pgs.
This report describes how North American insurers are using the cloud to access new and disruptive technologies and to differentiate themselves from competitors, turning the cloud into a true business asset.
Parallel Cloud Computing: Making Massive Actuarial Risk Analysis Possible
Joe Long, Dan McCurley
Predictive Analytics and Futurism. April 2018. PDF. 3 pgs.
This article describes a cloud use case where the authors were able to cut a three-month machine learning exploration project down to just under four days using a mixture of open source tools and the Microsoft Azure cloud
Cyber Risk / Cyber Insurance
AI-augmented Cybersecurity: How Cognitive Technologies can Address the Cyber Workforce Shortage
Deborah Golden, Ted Johnson
Deloitte Review. June 2017.
As the cybersecurity talent shortage continues, adding cognitive technologies into the mix can help automate routine tasks, increase responsiveness, and allow cyber professionals to focus more on tasks requiring human ingenuity.
Are Silent Cyber and Behavioral Risks in Your Line of Sight?
Adeola Adele, Anthony Dagostino and Mark P. Synnott
Emphasis. December 2017. PDF. 4 pgs.
With silent cyber exposure and related behavioral risks on the rise, how do insurers get better visibility into the full spectrum of cyber risks?
Beyond The Cyber Basics: Bug Bounties And Simulated Attacks
The One Brief
The WannaCry ransomware attacks exploited an operating system vulnerability, corrupted data on some 200,000 computers across 150 countries, then demanded payment for restored access. The cost of damages has been estimated in the billions of dollars.
Cyber And The C-Suite: Breaking Down Silos To Take On The Hacker
The One Brief
Aon’s 2018 Cybersecurity Predictions report found that last year businesses suffered significant financial damage as a result of cyber attacks. Data breaches led to the resignations of several top executives and sparked big falls in market capitalizations.
End Of The Wild Wild Web: Navigating Cyber Regulations
The One Brief
The question of how to regulate the internet more effectively is high on government agendas. In part, this is because cyber risks are becoming more prevalent.
From Malware To Phishing: Your Guide To Cyber Crime
The One Brief
In May 2017, computer users around the world were greeted with a worrying red screen and a message demanding the payment of up to $600 in bitcoins to unlock their computers. This was “WannaCry”, one of the biggest ransomware attacks in history.
How Can We Manage the Dynamic Nature of Cyber-risk?
Adeola Adele, Patrick Kulesa, Kevin Madigan and Alice Underwood
Emphasis. August 2016. PDF. 6 pgs.
Given the dynamic nature of cyber-risk, taking a multidimensional approach that integrates board governance, technology solutions, behavioral change and risk transfer solutions can help reduce risk to a manageable level.
Protecting Data & Information: How To Close The Cyber “Air Gap”
The One Brief
It’s no longer a case of if, but when your organization will be hit by cyber crime. Fallout from cyber attacks remains dramatically under-insured compared to the more traditional, physical risks.
Silent Cyber’s Specter is Casting a Larger Shadow on Insurers
Anthony Dagostino, Jess Fung, Mark Synnott
Emphasis. March 2019. PDF. 4 pgs.
The Willis Re 2018 Silent Cyber Risk Outlook global survey included close to 700 participants. All respondents were asked to assess the extent to which, over the next 12 months, cyber exposure would increase the likelihood of a covered loss.
Data Analytic Tools
#Insurtech is a Launch Pad to Unimagined Possibilities for Insurers: Think It, and It Can Be
Magdalena Ramada and Andrew Harley
Emphasis. June 2017. PDF. 4 pgs.
Insurtech is where the insurance industry’s future begins, a starting point that is unfathomable, challenging and yet well within reach.
The Essential Eight: Your Guide to the Emerging Technologies Revolutionizing Business Now
Scott Likens
Research & Insights. July 2016.
This article lists the following eight technologies as essential: Artificial Intelligence, Augmented Reality, Blockchain, Drones, Internet of Things, Robotics, Virtual Reality, and 3-D printing.
Harnessing the Potential of Data in Insurance
Air Libarikian, Kia Javanmardian, Doug McElhaney, and Ani Majumder
McKinsey & Company. May 2017.
Insurers collect a wealth of data, but few have found a way to monetize this asset. New “data as a business” models point the way forward.
Insurers: Avoid the InsurTech Autoimmune Disorder
Kevin J. Gregson
Emphasis. June 2018. PDF. 4 pgs.
Management tenents that protect an insurance company’s core business are not always compatible with innovation. How must insurers adapt to thrive in the InsurTech age?
Insurers Testing New Analytics Frontiers Face Meaningful Change
Nathalie Bégin, J.J. Ihrke and Charlie Samolczyk
Emphasis. June 2018. PDF. 4 pgs.
Emerging data sources and advanced analytics offer insurers the promise of unimagined value creation for those who navigate this new universe effectively.
Legacy-free Markets in Asia are Becoming InsurTech Incubators
Mark Hvidsten
Emphasis. December 2017. PDF. 4 pgs.
Asia, free of many unwieldly legacy constraints, is the prime example of how emerging markets may more immediately offer favorable conditions for InsurTech breakthroughs.
Making the Impossible Possible
Sally Percy
Reporting. November 2017. PDF. 6 pgs.
Technology is transforming finance – and audit and assurance along with it. This article investigates the potential impact on businesses, auditors and regulators.
Why Collaboration is the Future of InsurTech
The One Brief.
Our day-to-day lives – from how we hail a cab, to how we pay our bills – have transformed in the last few years. The insurance industry – long seen as a traditional sector – is also currently undergoing a significant period of innovation and disruption.
InsurTech Financing
Global Fintech Report Q3 2019
CB Insights fintech experts take a data-driven look at the current state of the global fintech market to spot the top trends and latest disruption.
2019 Insurance Outlook - Growing economy bolsters insurers, but longer-term trends may require transformation
Sam Friedman, Andrew N. Mais, Michelle Canaan, Nikhil Gokhale, Prachi Ashani
Insurance Outlook. 2018. PDF. 40 pgs.
Deloitte's Insurance Outlook looks at the state of the insurance market and key trends, including technology trends.
9 trends structuring the European InsurTech Scene
Discusses the main trends currently impacting European InsurTech.
Capgemini Top 10 Life Insurance Trends 2018
Raghunandan Kothamasu, Kumaresan A, Saurav Swaraj and Krithika Venkataraman
2018. PDF. 28 pgs.
Capgemini Top 10 Life Insurance Trends 2019
Saurav Swaraj
2019. PDF. 30 pgs.
Digital Insurance in 2018 - Driving real impact with digital and analytics
McKinsey & Company. December 2018. PDF. 72 pgs.
McKinsey has synthesized some of their most interesting articles from 2018. Taken together, they extend the discussion in two areas: reinventing the core of insurance and pushing our thinking on disruption and on what the future holds for the industry.
Online Insurance in China
Flora Shao
GenRe. December, 2017.
Discusses the rapid growth of online insurance products in China.
Quarterly InsurTech Briefing 2018 – Q1
Stephen Cox, Andrew Johnston, Matthew Wong
Willis Towers Watson Quarterly InsurTech Briefing. May 2018. PDF. 63 pgs.
1. Q1 2018 Industry Theme - Landscape of InsurTech Venture Capital Investors
2. InsurTech Investor Strategy - Venture Capital Investor Survey
3. Transaction Spotlight - Rebuilding the Insurance Model from the Ground Up: Root Insurance’s Series C Funding Round
4. Thought Leadership - Relevance of Traditional Insurance Models in the Digital Age
5. The Data Center - InsurTech by the Numbers
Quarterly InsurTech Briefing 2018 – Q2
Stephen Cox, Andrew Johnston, Matthew Wong
Willis Towers Watson Quarterly InsurTech Briefing. September 2018. PDF. 56 pgs.
1. Q2 2018 Industry Theme - How InsurTech is Impacting the Global Life & Health Landscape
2. Life & Health InsurTech Subcategories - Devices and Data Generation, Customer Centric Products and Digital Advisory Services
3. Transaction Spotlight - Investment in InsurTech Life Distribution Accelerates
4. Thought Leadership - InsurTech in the Life & Health Sector: Commentary from the InsurTech Grand Prix
5. The Data Center - InsurTech by the Numbers
Quarterly InsurTech Briefing 2018 – Q3
Stephen Cox, Andrew Johnston, Matthew Wong
Willis Towers Watson Quarterly InsurTech Briefing. December 2018. PDF. 46 pgs.
1. Q3 2018 Industry Theme - A New Insurance Paradigm: Event-Based Insurance
2. Start-Up Company Profiles - Event-Based Insurance Offerings for the Connected World
3. Transaction Spotlight - Munich Re’s Acquisition of Industrial Internet of Things (IIoT) Start-Up
4. Thought Leadership - A Trip to the Future Where Hyper-Granular Data Meet New Governance Paradigms
5. The Data Center - InsurTech by the Numbers
Quarterly InsurTech Briefing 2018 – Q4
Andrew Johnston, Matthew Wong
Willis Towers Watson Quarterly InsurTech Briefing. February 2019. PDF. 56 pgs.
1. Q4 2018 Industry Theme - Cyber InsurTechs – helping incumbents make sense of the threat and maximize the opportunity
2. InsurTech CompanyProfiles - Innovative solutions for an industry headache – Modeling, Risk Scoring, Mitigation Procedures, Digital Products, Post-Event Services and Firmware Vetting
3. Transaction Spotlight - Europe’s First InsurTech IPO – Deutsche Familienversicherung
4. Thought Leadership - Cyber – Opportunity or Threat?
5. The Data Center - InsurTech by the Numbers
Internet of Things
Extracting Tax Value from the Internet-of-Things
Emma Purdy, Devin Yaung, Brad Silver
Research & Insights. January 2017.
This looks at the tax implication of IoT investment. It argues that companies must consider tax up front when deciding on investments in IoT capabilities and services.
From Blueprint To Open For Business: How “Infratech” Has Become a Key Building Material
The One Brief
Internet connectivity, coupled with the ever-advancing ability to gather and analyze data, is finding its way into the construction industry. As a result, we’ll live and work in structures that are “aware,” and cities that are “smart.”
Leading-Edge Logistics: How Tech Can Strengthen The Supply Chain
The One Brief
As with GPS and the smartphone, when new technologies such as blockchain and AI make their way into supply chains, they do so as part of a larger “ecosystem” of technological innovation.
Machine Learning
Deep Learning Onramp: A free, 2-hour deep learning tutorial
Effective model validation using machine learning
Jonathan B. Glowacki, Martin Reichhoff
Insight. May 2017. PDF. 4 pgs.
Recent developments in technology and open-source software have increased computational power, allowed for more effective data-processing algorithms, and created a surge in demand for more advanced predictive solutions.
Personal Health Monitoring / Wearable Devices
Facts & Figures 2020 Reports Largest One-year Drop in Cancer Mortality
This article discusses the large drop in cancer mortality from 2016 to 2017. (January 2020)
Genetic Testing in Insurance: Challenges and Opportunities
Genetic Testing in Insurance: Challenges and Opportunities I
Genetic Testing in Insurance: Challenges and Opportunities II
These articles from RGA provide a good background to the challenges and opportunities of using genetic testing for insurance purposes. (January 2020)
New gene editing technology could correct 89% of genetic defects
Jessie Yeung
It might be possible to reverse a person’s biological age
Amit Malewar
The Birth of a Word
Deb Roy
TED Talk. 2011. 19:46
This TED Talk considers the work of MIT scientist, Deb Roy, who may have the most documented and analyzed family in the world.
Checking The Pulse Of Personal Tech: How mCare Is Changing Health
The One Brief
The market for mobile health technology, or “mHealth” apps, is projected to reach $28.3 billion in global market value in 2018.
Connected But Alone?
Sherry Turkle
TED Talk. 2012. 19:42
This TED Talk by celebrated MIT digital behavior psychologist considers how disconnecting our social media culture can be.
‘Depends on Who’s Got the Data’: Public Understandings of Personal Digital Dataveillance
Deborah Lupton & Mike Michael
Surveillance & Society 15(2): 254-268. 2017. 15 pgs.
In this article, we report the findings of a project in which we used cultural probes to generate discussion about personal digital dataveillance.
The Diverse Domains of Quantified Selves: Self-Tracking Modes and Dataveillance
Deborah Lupton
Journal of Economy and Society. April 2016.
This paper examines the ‘function creep’ of self-tracking by outlining five modes that have emerged: private, communal, pushed, imposed and exploited.
Does Being Connected Cost Us Our Humanity?
Chris Dancy
TED Talk. 2014. 15:16
TED Talk with Chris Dancy, often referred to as "the most connected man in the world."
Exercise as Labour: Quantified Self and the Transformation of Exercise into Labour
Chris Till
Societies 2014, 4(3), 446-462; doi:10.3390/soc4030446
The use of digital self-tracking devices has given rise to a range of relations to the self often discussed as quantified self (QS). This article proposes a consequence of this large-scale observation and analysis; that exercise activity is in the process of being reconfigured as labour.
The future is now: wearables for insurance risk assessment
June Quah
Munich Re. 2018. PDF. 4 pgs.
Wearables introduce a multitude of ways to monitor health. There is a huge opportunity for life insurance companies to change the way we interact with our customers and to improve how we manage risk.
Stratifying mortality risk using physical activity as measured by wearable sensors
Sandra Chefitz, June Quah, Adnan Haque
Munich Re. 2018. PDF. 8 pgs.
As the wearable and smartphone markets grow, there is potential for incorporating physical activity information into the life insurance underwriting process to enhance customer experience while improving risk selection.
The Transparent Self
Marjolein Lanzing
Ethics and Information Technology. March 2016. PDF. 8 pgs.
This paper focuses on a conceptual tension between the idea that disclosing personal information increases one’s autonomy and the idea that informational privacy is a condition for autonomous personhood.
Predictive Analytics
Considerations for Predictive Modeling in Insurance Applications
Eileen Burns, Gene Dan, Anders Larson, Bob Meyer, Zohair Motiwalla, and Guy Yollin
The Society of Actuaries Modeling Section, Predictive Analytics and Futurism Section, Committee on Life Insurance Research, Product Development Section and Reinsurance Section announce the release of a new report that can help to educate actuaries on how best to implement predictive modeling into relevant areas of actuarial practice.
Emerging risk analytics: Application of advanced analytics to the understanding of emerging risk
Neil Cantle
Insight. June 2017. PDF. 12 pgs.
The purpose of the study was to examine whether useful information could be extracted from social media in what is effectively real time on a key topic in a political economy.
The new era of insurance analytics
Claudine Modlin and Graham Wright
Emphasis. August 2016. PDF. 4 pgs.
Advanced analytics is helping some insurers offer innovative products and solutions. What do insurers need to know about the changing nature of analytics and whether it is worth the investment?
The Use of Predictive Analytics in the Canadian Life Insurance Industry
Jean-Yves Rioux, Arthur Da Silva, Harrison Jones and Hadi Saleh
The Canadian Institute of Actuaries and Society of Actuaries Committee on Life Insurance Research, the Product Development Section and the Financial Reporting Section, sponsored this study investigating how the Canadian life insurance industry is utilizing predictive modelling.
Software Development/Management/Training
Creating the Future: Software and Risk
Ari Ramdial
SOA, November 2018. PDF. 7 pgs.
Software is shaping a world in which there is more information to measure and more risk to manage. An increasing reliance on software as infrastructure of public and private enterprise will create demand for new forms of insurance products focused on systemic failure. Machine-originated risk will create a novel market and equally new challenges for quantifying, pricing, and pooling risk.
Telematics
A European insurance leader works with Milliman to process raw telematics data and detect driving behaviour
Rémi Bellina, Antoine Ly, Fabrice Taillieu
Insight. May 2018. PDF. 5 pgs.
This article focusses on the future of motor insurance and telematics, providing feedback on some of the projects led by Milliman's analytics team.
Usage Based Insurance
Making the business case: Telematics investment for UBI
Insight. January 2017.
A well-designed usage-based insurance program, aligned with customer needs, will produce positive return by both increasing revenue and lowering costs. Milliman tested this idea and took a conservative approach to estimating return on investment.
Usage-based insurance: Big data, machine learning, and putting telematics to work
Marcus Looft, Terry Wade, Scott C. Kurban
Insight. May 2015.
This paper suggests ways ML could help address how to get insight from the flood of data from UBI
Virtual Reality
Wish You Were Here? VR, AI And The New World Of Work
The One Brief
This article articulates how VR and AI can impact the workplace.