Friday, December 06, 2019

Results-Driven Claims Innovation

Results-Driven Claims Innovation: Unlock the Real Value of Claims Tech with AIG, Ameriprise and Metromile



In an age where customers are demanding their Insurance Carrier be more like Amazon or PayPal with a smooth, touchless customer experience, Insurance Carriers face multiple obstacles to satisfying this demand. Chief among them is the overwhelming multitude of technologies available to reach that touchless claims goal. 

77% of insurance carriers will invest in automation in the next few years to achieve seamless claims. The incredible potential to leverage technology stretches across the claims landscape, from chatbots to AI, FNOL to payment.
However – the endless opportunity does make it difficult to prioritize, integrate and fully maximize the power of Claims Tech.
To discuss how to leverage the value of technology to improve customer experience and deliver efficiencies, Insurance Nexus is bringing together a team of experts including Eric Spencer (Chief Claims Officer, Ameriprise)Amrish Singh (Head of Product, Metromileand Fred Lemire (Director of Claims Adminstration, AIGas well as our moderator Bryan Falchuk (Best-selling Author,  for a live webinar, Results-Driven Claims Innovation: Unlock the Real Value of Claims Tech‘ on December 10th at 11:00am ET.
• Achieve Impact Amongst Innovation: Prioritize tech depending on the potential scale of impact, aligning outcomes with business goals
• Put the Human Touch in Touchless: Balance empathy with efficiency in the race towards automated claims
• Solve the Pain Points: Combine long-term transformation with quick wins to erase the biggest customer pain points immediately
It’s an exciting and challenging time as we craft the design to meet the needs of the “service-touch” generations to “techno-service” generations.  As leaders, we live in a world where we are led by or lead through change, regardless understanding the intersection of design and technology deliveries is at the core.” – Eric Spencer, Chief Claims Officer at Ameriprise  
Register for this webinar today – those who register will be sent the recordings, even if they cannot join live. 
We have so many options at our disposal today to evolve how we serve our insureds. The greatest complexity lies in plotting a path forward and executing on it to take advantage of those options effectively, driving better customer experiences, improved loss results and higher employee engagement. Despite the headwinds we face as an industry and in Claims specifically, we can still navigate the path forward successfully rather than being disrupted into irrelevance.” – Bryan Falchuk, Best-Selling Author/Speaker/Executive 
This webinar is being run in conjunction with Insurance Nexus’ upcoming Fourth Annual Connected Claims USA Summit, taking place June 24th–25th, at McCormick Place. Welcoming over 1500 senior attendees, Connected Claims USA is the world’s largest gathering for claims executives striving for efficient, customer-centric claims processing. More information can be found on the website at https://events.insurancenexus.com/connectedclaimsusa/

Sunday, December 01, 2019

Free Oracle Cloud Services

Today I was looking for a cloud based Oracle database service. Oracle's "Cloud Free Tier" offers always free for VM instance, Database and Data Warehouse. I signed up for the free service and will share my experience as I try them.

Sunday, October 27, 2019

Optimizing Inventory Level: Reduce the Inventory Value and Increase Customer Satisfaction Simultaneously

For a large part manufacture company in the transportation industry, maintaining the optimal inventory level in their warehouses is crucial to its bottom line. When too many parts are produced and stored, it costs the company excessive financial investment and previous warehouse spaces. On the other hand, if not enough parts in the warehouses, customers will become dissatisfied when orders may not get fulfilled in time. Thus, there are two conflicting goals to balance when planning the inventory: reducing inventory value and increasing customer satisfaction. The optimal strategy is to find the sweet spot of inventory level for each individual part that is most economical and maintaining high level of customer satisfaction at the same time. In a recent project that Dr. Jay Zhou has preformed, he is able to reduce the inventory level for his client company by $16 million and still maintain the same level of customer satisfaction. This work is highly received by the client.

In this project, Dr.Zhou takes advantage of machine learning models and reduces huge number of parts to a much smaller number of homogeneous groups. The "Demand Satisfaction" are calculated for these groups.

Thursday, August 01, 2019

CALL FOR PAPERS

CALL FOR PAPERS

Workshop on Data Mining in Industrial Internet of Things (DMIIOT)

to be held in conjunction with the IEEE International Conference on Data Mining 2019 in Beijing

Data generated by industrial internet of things (IIOT) have been growing at an exponential rate. Data mining plays an essential role in deriving actionable information from these raw data. By applying a variety of data mining technologies to historical and real time IIOT data, building supervised or unsupervised models, deploying them into the production environment to help business make better decisions, significant value can be created resulting in reduced waste, improved efficiency and broaden opportunity.  The marriage between data mining and IIOT has found applications in industries such as manufacturing, energy, healthcare, retail, smart city and transportation.

The workshop will provide a venue for researchers and practitioners from both data mining and IIOT communities to exchange ideas, share best practices, discuss challenges and future directions. By fostering communication and collaboration, we drive innovative applications of data mining to IIOT. This workshop will be held along with 2019 IEEE International Conference on Data Mining, Beijing (http://icdm2019.bigke.org).

 This workshop calls for papers that cover topics including, but not limited to, the following:

  • Data mining algorithms for IIOT
  • Data mining architectures in IIOT environment
  • Data mining applications in areas including manufacturing, energy, healthcare, smart city, transportation, etc.
  • Best practices, challenges and future developments

This workshop would like to call for research papers sharing the experiences from the real data and real-world practice. We do not require technical innovations (using existing data mining techniques is totally acceptable). All accepted workshop papers will be published in formal proceedings published by the IEEE Computer Society Press indexed by EI.

Paper Submissions:

Deadline: 21 August 2019, 11:59PM Pacific Time.

Rules:

ICDM workshop follows the same submission requirement as ICDM papers.

  • Long paper (up to 8 pages) and short paper (up to 4 pages). The page limit includes the bibliography and any possible appendices.
  • All papers must be formatted according to the IEEE Computer Society proceedings manuscript style, following IEEE ICDM 2019 submission guidelines available at: http://icdm2019.bigke.org/
  • Papers should be submitted through On-Line Paper Submission.
  • All accepted papers will be included in the IEEE ICDM 2019 Workshops Proceedings volume published by IEEE Computer Society Press and will also be included in the IEEE Xplore Digital Library. Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals.

IMPORTANT DATES

Paper Submission Deadline: 21 August 2019, 11:59 PM Pacific Time.

Paper Notification: 4 September 2019

Camera Ready Version: 8 September 2019

Workshop: 8 November 2019

Steering Committee

  • Dr. Jay Lee (Univ. of Cincinnati)
  • Dr. Qi Li (Peking University) 
  • Dr. Shaofu Lin (Beijing University of Technology)
  • Dr. Shyam Varan Nath (Oracle)
  • Dr. Richard Mark Soley (Industrial Internet Consortium)
  • Dr. Honggang Wang (University of Massachusetts- Dartmouth)
  • Dr. Jiansheng Zhang (Tsinghua University)

Program Committee

  • Dr. Zhaoheng Gong (Harvard University)
  • Dr. Jay Lee (Univ. of Cincinnati)
  • Dr. Shaofu Lin (Beijing University of Technology)
  • Mr. Song Luo (China Academy of Information and Communication Technology)
  • Dr. Shyam Varan Nath (Oracle)
  • Dr. Honggang Wang (University of Massachusetts- Dartmouth)
  • Dr. Jiansheng Zhang (Tsinghua University)

Workshop Chairs

  • Dr. Ping Chen (University of Massachusetts-Boston) 

E-mail: ping.chen@umb.edu; Website: http://www.cs.umb.edu/~pchen

  • Dr. Jiang (Jay) Zhou (AI Strike LLC)

 E-mail: jay.zhou@aistrike.us; Website: http://aistrike.us

Media Partners

Wednesday, April 24, 2019

Onsite Interactive Training Session for Data Analysts/Data Scientists

Dr. Zhou is offering a brand new service: a half-day (3 hours) interactive training session to help a company's data analysts/data scientists improve their skills and productivity. The format of the interactive training session is as follows:

1. Dr. Zhou first gives a 1.5 hours presentation to describe successful cases of using data analytics to solve business problems, share best practices, and talk about challenges.
2. For the remaining 1.5 hours, the audience asks questions and is actively engaged in discussion with Dr. Zhou.  This the best part!  As one of the scientists said, "Dr. Zhou has helped me solve an issue that I had struggled with for years".

The training session is designed for all data analysts/data scientists. Dr. Zhou shares his battle-tested strategies and best practices that are useful for them regardless what specific analytics tools or programming languages they use.

On April 23, 2019, Dr. Zhou delivered the interactive training session to one of the top three property insurance company located in Boston. It was extremely well received. The picture attached shows that I am making the presentation (in addition to people in the room, there are more people joining the meeting through the phone.) 



The following are the testimonials from two persons who took the course.

"We have learnt a lot from Dr.Zhou'", Gang Xu, Director, Data Science at Lincoln Financial Group
"Dr. Zhou gave us a great overview of procedures of doing a solid predictive analysis and illustrated real life AI consulting business cases. Dr. Zhou is really experienced in the AI space and his presentation was very well received by data scientists from Lincoln Financial Group. I would highly recommend any data science group to have Dr. Zhou sharing his experiences. "-  Dr. Hao Zhou, Principal Analyst,  Data Science at Lincoln Financial Group

The following are testimonials about my previous talks and training activities.

"It was a fortune to have Jay come to our computer science department to share his experience in solving business problems with predictive analytics on February 28, 2017. What Jay had presented in his 3 talks, each lasting for 1 hour in different topics of data mining, was totally impressive and beyond our wildest expectation. Having built competition-winning predictive models for some of the biggest companies and produced hundreds of millions of dollars’ savings, Jay shared the secret of his success with students and faculty without reservation. His strong presentations were such an inspiration for our computer science students and faculty and his methodology was innovative and powerful , even for very seasoned data scientists among the audience. Jay, thank you so much for your hard work preparing and delivering these presentations! " - Dr. Wei Ding, Professor at University of Massachusetts Boston

"Jay is more than just a coder, he is a great trainer, and a good presenter of theoretical data mining concepts so that they can be understood by most. "-James Lukenbill, Director of IT Project Management, Optum

Bio of Dr.Jiang Zhou
Dr. Jiang Zhou has two decades of experience building predictive models across industries including telecommunication, banking, insurance, and smart city. These solutions have resulted in over $200 million savings for clients. Dr. Zhou has been involved in three real world competitions to build best predictive models, i.e., a customer credit risk model for a top three cell phone company, a bank card fraud detection model for a top 15 bank, and a direct sales model for a marketing company. Dr. Zhou's models have won all these competitions. He has founded/co-founded data analytics companies, including Business Data Miners, Smart Credit and AI Strike. Previously, he was a chief statistician at Lightbridge, a vice president at Citizens Bank and a consulting member of technical staff at Oracle. Dr. Zhou is the author of an award-wining blog on data analytics https://www.deep-data-mining.com/

The normal price for the training service is $6,500. If your company is interested in the service, please contact Dr. Zhou at jay.zhou@deep-data-mining.com 

Wednesday, April 17, 2019

CALL FOR PAPERS

Workshop on Data Mining in Industrial Internet of Things (DMIIOT)
to be held in conjunction with the IEEE International Conference on Data Mining 2019 in Beijing
Data generated by industrial internet of things (IIOT) have been growing at an exponential rate. Data mining plays an essential role in deriving actionable information from these raw data. By applying a variety of data mining technologies to historical and real time IIOT data, building supervised or unsupervised models, deploying them into the production environment to help business make better decisions, significant value can be created resulting in reduced waste, improved efficiency and broaden opportunity.  The marriage between data mining and IIOT has found applications in industries such as manufacturing, energy, healthcare, retail, smart city and transportation.
The workshop will provide a venue for researchers and practitioners from both data mining and IIOT communities to exchange ideas, share best practices, discuss challenges and future directions. By fostering communication and collaboration, we drive innovative applications of data mining to IIOT. This workshop will be held along with 2019 IEEE International Conference on Data Mining, Beijing (http://icdm2019.bigke.org).
 This workshop calls for papers that cover topics including, but not limited to, the following:
  • Data mining algorithms for IIOT
  • Data mining architectures in IIOT environment
  • Data mining applications in areas including manufacturing, energy, healthcare, smart city, transportation, etc.
  • Best practices, challenges and future developments
This workshop would like to call for research papers sharing the experiences from the real data and real-world practice. We do not require technical innovations (using existing data mining techniques is totally acceptable). All accepted workshop papers will be published in formal proceedings published by the IEEE Computer Society Press indexed by EI.

Paper Submissions:

Deadline: 7 August 2019, 11:59PM Pacific Time.

Rules:

ICDM workshop follows the same submission requirement as ICDM papers.
  • Long paper (up to 8 pages) and short paper (up to 4 pages). The page limit includes the bibliography and any possible appendices.
  • All papers must be formatted according to the IEEE Computer Society proceedings manuscript style, following IEEE ICDM 2019 submission guidelines available at: http://icdm2019.bigke.org/
  • Papers should be submitted in PDF format, electronically, through email to paper@aistrike.us.
  • All accepted papers will be included in the IEEE ICDM 2019 Workshops Proceedings volume published by IEEE Computer Society Press and will also be included in the IEEE Xplore Digital Library. Therefore, papers must not have been accepted for publication elsewhere or be under review for another workshop, conferences or journals.
IMPORTANT DATES


Paper Submission Deadline: 7 August 2019, 11:59 PM Pacific Time.
Paper Notification: 4 September 2019
Camera Ready Version: 8 September 2019
Workshop: 8 November 2019
Steering Committee
  • Dr. Jay Lee (Univ. of Cincinnati)
  • Dr. Qi Li (Peking University) 
  • Dr. Shaofu Lin (Beijing University of Technology)
  • Dr. Shyam Varan Nath (Oracle)
  • Dr. Richard Mark Soley (Industrial Internet Consortium)
  • Dr. Honggang Wang (University of Massachusetts- Dartmouth)
  • Dr. Jiansheng Zhang (Tsinghua University)


Program Committee
  • Dr. Zhaoheng Gong (Harvard University)
  • Dr. Jay Lee (Univ. of Cincinnati)
  • Dr. Shaofu Lin (Beijing University of Technology)
  • Mr. Song Luo (China Academy of Information and Communication Technology)
  • Dr. Shyam Varan Nath (Oracle)
  • Dr. Honggang Wang (University of Massachusetts- Dartmouth)
  • Dr. Jiansheng Zhang (Tsinghua University)

Workshop Chairs
  • Dr. Ping Chen (University of Massachusetts-Boston) 
  • Dr. Jiang (Jay) Zhou (AI Strike LLC)

Thursday, March 07, 2019

From Hype to Reality – Powering the AI-Driven Future of Insurance at Insurance AI and Analytics USA - by Ira Sopic



With 2018 witnessing unprecedented advances in the investment and deployment of artificial intelligence within the insurance industry, Insurance Nexus is delighted to announce that the Insurance AI and Analytics USA Summit will return to Chicago for a sixth time in 2019, welcoming more than 450 senior attendees to the Renaissance Chicago Downtown Hotel, May 2-3.
Featuring an agenda designed to tackle the biggest challenges and opportunities in AI and advanced analytics, Insurance AI and Analytics USA is a must-attend for any analytics, underwriting, claims or marketing innovators seeking to both achieve efficient and seamless operations and deliver valuable and relevant products and experiences. 

It’s impossible to open a magazine without seeing hype about analytics changing every aspect of your life,” says Will Dubyak, VP Analytics for Product Development & Innovation, USAA. “The Insurance AI & Analytics USA Summit is the optimal place to cut through the noise, hear the latest thinking from industry leaders in analytics, and compare best practices with your colleagues
Across three in-depth tracks, more than 40 expert speakers from leading North American carriers will explore and discuss the latest strategies and approaches being deployed to maximize the impact of AI, machine learning and advanced analytics across the insurance value chain.
Featuring a whole session dedicated to case studies, the practical retelling of success stories will ensure attendees discover how, and where, technological innovations are having the biggest impacts on insurance and walk away with a holistic roadmap for success.
Confirmed speakers so far include Tilia Tanner, Global Head of Analytics, AIG, Eugene Wen, VP of Group Advanced Analytics, Manulife and Jerry Gupta, SVP, Digital Analyst Catalyst, SwissRe, as well as:
  •        Thomas Sheffield, SVP and Head of Specialty Claims, QBE
  •          Glenn Fung, Chief Research Scientist, AI and Machine Learning Research Director, American Family Insurance
  •         Laurie Pierman, Vice President, Claim Operations, Amerisure Insurance
  •          Michiko Kurahashi, Chief Marketing Officer, AXIS Capital

Attendees to Insurance AI and Analytics USA will also become part of a truly international insurance community, with over 25 hours of networking and interactive discussions aplenty. In addition, our ‘Open Design Workshops’ will see attendees attempt to live-solve industry challenges, giving insight into how peers and competitors alike approach a challenge, and how their own methods might be improved.

At QBE, we’ve spent a great deal of time figuring out how we can strategically deploy artificial intelligence in practical use cases to drive immediate value for business,” states Ted Stuckey, Managing Director, QBE Ventures. “We’re excited to share some of our experience at the Insurance AI and Analytics Conference in Chicago on May 2-3!”

In short, however you are seeking to leverage AI, Insurance AI and Analytics USA is the event for you. Don’t miss this unparalleled opportunity. Join us in making 2019 the year AI insurance changes, forever.

Ira Sopic