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May 23, 2016 · 26m · mad

Big Data in Insurance // Louis DiModugno, Chief Data Officer at AXA US [FirstMark's Data Driven]

Louis DiModugno · 17m spoken Matt Turck · 4m spoken
0:00 / 0:00
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In this Data Driven NYC talk, Louis DiModugno, Chief Data & Analytics Officer at AXA US, discusses how global insurance enterprises modernize operations through predictive analytics, big data infrastructure, and workforce transformation. He details the integration of machine learning, telematics, startup partnerships, and organizational strategies needed to scale data innovation within highly regulated environments.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Matt holds 19.1% of the talking time here. How this is scored →

Matt as informed peer 1.9 Guest teaching 2.8 Guest disagreement 0.0 Matt pushing back 0.0
05100:0010:0020:000:50–3:41 · Matt as informed peer 3/10 Louis DiModugno's Role and AXA's Global Data Overview Matt opens with a warm introduction highlighting the challenge of building a data culture in a legacy enterprise and asks how actuarial work is evolving. Louis explains how AXA converts young actuaries into big data scientists fluent in R and Python.3:41–6:21 · Matt as informed peer 2/10 Big Data Applications and Predictive Underwriting Matt prompts Louis for concrete examples of big data in action across business units. Louis details auto repair shop fraud detection in Europe and predictive underwriting for life insurance in the US.6:21–9:58 · Matt as informed peer 4/10 Telematics and Autonomous Vehicles Matt brings up telematics, IoT device integration, autonomous vehicle liability, and call center analytics. Louis outlines hardware OBD port usage, liability legalities, and customer routing based on policy complexity.9:58–14:52 · Matt as informed peer 5/10 AXA's Global Tech Stack and Data Architecture Matt demonstrates knowledge of startup ecosystem players like Dataiku and its founder's background while asking how startups can partner with AXA. Louis explains how AXA works with vendors to extract value from legacy paper microfiche applications and HIPAA forms.14:52–17:51 · Matt as informed peer 1/10 Data Governance, Preparation, and Team Structure Matt asks about team composition and hiring needs. Louis provides deep context on organizing data and analytics under a single executive to counter C-suite skepticism, noting that 90% of project time is data prep.17:51–20:34 · Matt as informed peer 0/10 Audience Q&A: Business Collaboration and Internal Politics Matt fields audience questions regarding cross-functional collaboration and internal politics. Louis describes how embedding data scientists in business units and sharing COO reporting lines with the CIO smooths organizational friction.20:34–23:39 · Matt as informed peer 0/10 Audience Q&A: Pitches, Asset Management, and IoT Health Data Audience members pitch actuarial software, inquire about asset management, and ask about health IoT devices. Louis manages pitches cordially and shares ongoing trials in diabetes monitoring and wearable health tracking.23:39–25:37 · Matt as informed peer 0/10 Audience Q&A: Document OCR and Customer Feedback Louis answers audience questions on document text extraction software and customer adoption of automated underwriting decisions before closing with a recruiting note.0:50–3:41 · Guest teaching 3/10 Louis DiModugno's Role and AXA's Global Data Overview Matt opens with a warm introduction highlighting the challenge of building a data culture in a legacy enterprise and asks how actuarial work is evolving. Louis explains how AXA converts young actuaries into big data scientists fluent in R and Python.3:41–6:21 · Guest teaching 3/10 Big Data Applications and Predictive Underwriting Matt prompts Louis for concrete examples of big data in action across business units. Louis details auto repair shop fraud detection in Europe and predictive underwriting for life insurance in the US.6:21–9:58 · Guest teaching 3/10 Telematics and Autonomous Vehicles Matt brings up telematics, IoT device integration, autonomous vehicle liability, and call center analytics. Louis outlines hardware OBD port usage, liability legalities, and customer routing based on policy complexity.9:58–14:52 · Guest teaching 3/10 AXA's Global Tech Stack and Data Architecture Matt demonstrates knowledge of startup ecosystem players like Dataiku and its founder's background while asking how startups can partner with AXA. Louis explains how AXA works with vendors to extract value from legacy paper microfiche applications and HIPAA forms.14:52–17:51 · Guest teaching 4/10 Data Governance, Preparation, and Team Structure Matt asks about team composition and hiring needs. Louis provides deep context on organizing data and analytics under a single executive to counter C-suite skepticism, noting that 90% of project time is data prep.17:51–20:34 · Guest teaching 2/10 Audience Q&A: Business Collaboration and Internal Politics Matt fields audience questions regarding cross-functional collaboration and internal politics. Louis describes how embedding data scientists in business units and sharing COO reporting lines with the CIO smooths organizational friction.20:34–23:39 · Guest teaching 2/10 Audience Q&A: Pitches, Asset Management, and IoT Health Data Audience members pitch actuarial software, inquire about asset management, and ask about health IoT devices. Louis manages pitches cordially and shares ongoing trials in diabetes monitoring and wearable health tracking.23:39–25:37 · Guest teaching 2/10 Audience Q&A: Document OCR and Customer Feedback Louis answers audience questions on document text extraction software and customer adoption of automated underwriting decisions before closing with a recruiting note.0:50–3:41 · Guest disagreement 0/10 Louis DiModugno's Role and AXA's Global Data Overview Matt opens with a warm introduction highlighting the challenge of building a data culture in a legacy enterprise and asks how actuarial work is evolving. Louis explains how AXA converts young actuaries into big data scientists fluent in R and Python.3:41–6:21 · Guest disagreement 0/10 Big Data Applications and Predictive Underwriting Matt prompts Louis for concrete examples of big data in action across business units. Louis details auto repair shop fraud detection in Europe and predictive underwriting for life insurance in the US.6:21–9:58 · Guest disagreement 0/10 Telematics and Autonomous Vehicles Matt brings up telematics, IoT device integration, autonomous vehicle liability, and call center analytics. Louis outlines hardware OBD port usage, liability legalities, and customer routing based on policy complexity.9:58–14:52 · Guest disagreement 0/10 AXA's Global Tech Stack and Data Architecture Matt demonstrates knowledge of startup ecosystem players like Dataiku and its founder's background while asking how startups can partner with AXA. Louis explains how AXA works with vendors to extract value from legacy paper microfiche applications and HIPAA forms.14:52–17:51 · Guest disagreement 0/10 Data Governance, Preparation, and Team Structure Matt asks about team composition and hiring needs. Louis provides deep context on organizing data and analytics under a single executive to counter C-suite skepticism, noting that 90% of project time is data prep.17:51–20:34 · Guest disagreement 0/10 Audience Q&A: Business Collaboration and Internal Politics Matt fields audience questions regarding cross-functional collaboration and internal politics. Louis describes how embedding data scientists in business units and sharing COO reporting lines with the CIO smooths organizational friction.20:34–23:39 · Guest disagreement 0/10 Audience Q&A: Pitches, Asset Management, and IoT Health Data Audience members pitch actuarial software, inquire about asset management, and ask about health IoT devices. Louis manages pitches cordially and shares ongoing trials in diabetes monitoring and wearable health tracking.23:39–25:37 · Guest disagreement 0/10 Audience Q&A: Document OCR and Customer Feedback Louis answers audience questions on document text extraction software and customer adoption of automated underwriting decisions before closing with a recruiting note.0:50–3:41 · Matt pushing back 0/10 Louis DiModugno's Role and AXA's Global Data Overview Matt opens with a warm introduction highlighting the challenge of building a data culture in a legacy enterprise and asks how actuarial work is evolving. Louis explains how AXA converts young actuaries into big data scientists fluent in R and Python.3:41–6:21 · Matt pushing back 0/10 Big Data Applications and Predictive Underwriting Matt prompts Louis for concrete examples of big data in action across business units. Louis details auto repair shop fraud detection in Europe and predictive underwriting for life insurance in the US.6:21–9:58 · Matt pushing back 0/10 Telematics and Autonomous Vehicles Matt brings up telematics, IoT device integration, autonomous vehicle liability, and call center analytics. Louis outlines hardware OBD port usage, liability legalities, and customer routing based on policy complexity.9:58–14:52 · Matt pushing back 0/10 AXA's Global Tech Stack and Data Architecture Matt demonstrates knowledge of startup ecosystem players like Dataiku and its founder's background while asking how startups can partner with AXA. Louis explains how AXA works with vendors to extract value from legacy paper microfiche applications and HIPAA forms.14:52–17:51 · Matt pushing back 0/10 Data Governance, Preparation, and Team Structure Matt asks about team composition and hiring needs. Louis provides deep context on organizing data and analytics under a single executive to counter C-suite skepticism, noting that 90% of project time is data prep.17:51–20:34 · Matt pushing back 0/10 Audience Q&A: Business Collaboration and Internal Politics Matt fields audience questions regarding cross-functional collaboration and internal politics. Louis describes how embedding data scientists in business units and sharing COO reporting lines with the CIO smooths organizational friction.20:34–23:39 · Matt pushing back 0/10 Audience Q&A: Pitches, Asset Management, and IoT Health Data Audience members pitch actuarial software, inquire about asset management, and ask about health IoT devices. Louis manages pitches cordially and shares ongoing trials in diabetes monitoring and wearable health tracking.23:39–25:37 · Matt pushing back 0/10 Audience Q&A: Document OCR and Customer Feedback Louis answers audience questions on document text extraction software and customer adoption of automated underwriting decisions before closing with a recruiting note.

speaking balance: gold is Matt, purple is the guest (3 minute bins)

0:00 · Matt 40.7% · guest 59.3%0:00 · Matt 40.7% · guest 59.3%3:00 · Matt 9.2% · guest 90.8%3:00 · Matt 9.2% · guest 90.8%6:00 · Matt 26.5% · guest 73.5%6:00 · Matt 26.5% · guest 73.5%9:00 · Matt 41% · guest 59%9:00 · Matt 41% · guest 59%12:00 · Matt 16.6% · guest 83.4%12:00 · Matt 16.6% · guest 83.4%15:00 · Matt 9.1% · guest 90.9%15:00 · Matt 9.1% · guest 90.9%18:00 · Matt 2.1% · guest 97.9%18:00 · Matt 2.1% · guest 97.9%21:00 · Matt 17.2% · guest 82.8%21:00 · Matt 17.2% · guest 82.8%24:00 · Matt 5% · guest 95%24:00 · Matt 5% · guest 95%
Sharpest disagreement ▶ 21:59 Clarifying scope boundary on asset management

In a generally agreeable dialogue, Louis cleanly corrects an audience member's assumption by noting asset management and investments fall under finance and risk rather than his domain.

 Hardest push from Matt ▶ 13:46 Probing startup partnership mechanics

Matt presses Louis beyond general advice to specify the practical operational steps and expectations a startup faces when initiating a relationship with AXA.

 Biggest teaching moment ▶ 15:45 The 90/10 data preparation reality

Louis educates the room on C-suite misconceptions about data, explaining that 90% of analytics work is raw data access and cleanup while modeling accounts for only 10%.

 Matt holds his own ▶ 11:15 Connecting vendor ecosystem connections

Matt demonstrates industry fluency by pointing out Dataiku's previous presentation at the event and noting the founder's history with French search engines.
the scores for every segment, with the reasoning behind each
ChapterTopicMatt as informed peerGuest teachingGuest disagreementMatt pushing backWhy
Louis DiModugno's Role and AXA's Global Data Overview 3300 Matt opens with a warm introduction highlighting the challenge of building a data culture in a legacy enterprise and asks how actuarial work is evolving. Louis explains how AXA converts young actuaries into big data scientists fluent in R and Python.
Big Data Applications and Predictive Underwriting 2300 Matt prompts Louis for concrete examples of big data in action across business units. Louis details auto repair shop fraud detection in Europe and predictive underwriting for life insurance in the US.
Telematics and Autonomous Vehicles 4300 Matt brings up telematics, IoT device integration, autonomous vehicle liability, and call center analytics. Louis outlines hardware OBD port usage, liability legalities, and customer routing based on policy complexity.
AXA's Global Tech Stack and Data Architecture 5300 Matt demonstrates knowledge of startup ecosystem players like Dataiku and its founder's background while asking how startups can partner with AXA. Louis explains how AXA works with vendors to extract value from legacy paper microfiche applications and HIPAA forms.
Data Governance, Preparation, and Team Structure 1400 Matt asks about team composition and hiring needs. Louis provides deep context on organizing data and analytics under a single executive to counter C-suite skepticism, noting that 90% of project time is data prep.
Audience Q&A: Business Collaboration and Internal Politics 0200 Matt fields audience questions regarding cross-functional collaboration and internal politics. Louis describes how embedding data scientists in business units and sharing COO reporting lines with the CIO smooths organizational friction.
Audience Q&A: Pitches, Asset Management, and IoT Health Data 0200 Audience members pitch actuarial software, inquire about asset management, and ask about health IoT devices. Louis manages pitches cordially and shares ongoing trials in diabetes monitoring and wearable health tracking.
Audience Q&A: Document OCR and Customer Feedback 0200 Louis answers audience questions on document text extraction software and customer adoption of automated underwriting decisions before closing with a recruiting note.

Statements from this episode (8)

Disclosure
AXA converts younger actuaries into internal data science roles
“What we found is that, quite frankly, we had some data scientists essentially within our midst, and so the actuaries that we had within our organizations, especially some of the younger ones, it was a very nice conversion for them to be able to pick up R codin…”
Louis DiModugno May 23, 2016 ▶ 2:59
Disclosure
AXA leverages telematics in Europe for auto insurance pricing adjustments
“Ah, we also have a big, ah, initiative in Europe as well with telematics right now. So in the property and casualty space, specifically in auto, we get a much better, ah, capability to get better pricing based on how How people are using their automobiles and …”
Louis DiModugno May 23, 2016 ▶ 4:31
Disclosure
AXA augments point-of-sale customer data with external sources for predictive underwriting
“Our actuary, ah, efforts and our predictive underwriting efforts have really started to take advantage of the information that we're collecting at the point of sale, augmenting it with additional information that's accessible maybe through prescription databas…”
Louis DiModugno May 23, 2016 ▶ 5:30
Disclosure
AXA US builds its analytics infrastructure on a Cloudera Hadoop stack
“So the one that we've got here in the U.S., it's primarily a Cloudera Hadoop stack that we've used a blueprint that was essentially blessed by our brethren over in French, in France and with that, we've got R and Python and Spark. We use some Dataiku along the…”
Louis DiModugno May 23, 2016 ▶ 10:44
Assertion Not checkable as stated
AXA spends 90% of data project time on preparation, 10% on modeling
“One of the biggest challenges that we've had in this two years of existence is that of the biggest projects that we've been working on, it's been, you know, 90% data access and preparation, 10% model building.”
Louis DiModugno May 23, 2016 ▶ 16:32
Opinion
DiModugno: Diabetes patients are a heavily underserved community in the insurance industry
“In the insurance space, it's a very underserved community.”
Louis DiModugno May 23, 2016 ▶ 22:56
Disclosure
AXA's opt-in customer data sharing initiatives remain on the drawing board
“We're looking at opportunities for customers to opt in, and provide us that data, so that we could then go ahead and provide them some benefit as well. But we have not progressed to that fact. It's still on the drawing board.”
Louis DiModugno May 23, 2016 ▶ 23:23
Disclosure
AXA aims to deploy algorithmic risk scoring across its entire book by 2017
“Our intent is that within the next, ah, year to 18 months, this scoring mechanism will be essentially across our entire book of business.”
Louis DiModugno May 23, 2016 ▶ 25:27
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