About Nicolas Michellod

The Death of Processes and the Birth of High Frequency Underwriting

The Death of Processes and the Birth of High Frequency Underwriting

Let’s consider a car insurance market where all new contracts go through online aggregators. Let’s assume all the car’s information (vehicle brand, type, category, plate number, etc.) and potential insured data (driver’s name, age, address, historical claims, etc.) is standardized, packaged to include all relevant information needed by an insurer to price a motor insurance risk, and instantaneously electronically transferred to an aggregator as soon as the car is purchased (payment triggers the packaged data transfer, quoting, binding, and contract sealing). With today’s technology and connectivity, this quote and bind process can be done in less than a second.

In insurance, a process is a series of tasks to turn raw data into valuable information to make a business decision. In other words, a process requires time between its inception and its end and almost always human intervention. Indeed, today’s quote and bind process captures relevant data about a car and a driver through a questionnaire. Then insurers need to evaluate the risk involved and price it before a quote is given and potentially accepted by the driver. Even though many digital interfaces can be offered to perform the whole process, the potential customer still has to respond to a set of questions and click on a button to accept a proposal. In our extreme digital example, all the tasks are reduced to a minimum of time and fully automated; the driver doesn’t even have to fill in a questionnaire since all relevant data is packaged, transmitted, analysed, and sealed into a new car insurance contract in less than a second as soon as the car purchase is triggered. Can we still call it a process when there is an instantaneous business decision (underwriting and pricing) made and an outcome (contract sealed) produced, and this without human intervention? Well, I think with extreme digital, processes as we know and define them today are dead.

The next question is: How can insurers differentiate in a world where customer engagement is nonexistent? One might think that it would be price. Actually, it is speed. Indeed, I think that the ability to match a specific demand faster than competitors will allow an insurer to win the deal. To do so, they’ll need to support what I call high frequency underwriting in order to have their quote matched with the demand side within milliseconds (faster than competitors’ quotes). Indeed, for the same price, the fastest proposition will win the deal.

Now, let’s get back to my initial assumption: all new contracts go through online aggregators. Let’s consider an aggregator owned by an insurance player. If this insurer can get time advantage versus other insurers feeding its aggregator, it will be able to adapt its quote to optimize its margin using competitors’ information and leverage the speed advantage, even though it is about milliseconds.

This scenario is not unrealistic, because high-frequency trading is about milliseconds. So, who knows, maybe one day we will see insurers not thinking much about processes, but focusing more on speed.

Long Live Legacy and Ecosystem Transformation

Long Live Legacy and Ecosystem Transformation

When I started working at Celent back in November 2007, one of the research topic we were covering extensively was the legacy system modernization or replacement topic. Nowadays, legacy modernization remains a topic that has still a high importance in insurance CIOs’ agenda across the globe. Indeed based on our 2017 insurance CIO survey and out of 150 responses received across the globe, 57% of insurers are currently working on legacy modernization system projects. Another 10% are in the planning process and 11% will begin new legacy transformation projects next year.

It is therefore important for us to help our insurance customers understand what embarking in a core system replacement or modernization project means. While the benefits of modernizing core legacy systems are clear and compelling (gaining a competitive advantage — or achieving competitive parity, reducing operational and IT costs, making better underwriting and claims decisions, seizing analytic advantages when information and processes become completely digital), there are a lot of factors at play from the definition of the new system requirements, the approach to be chosen between the development of a new system and the purchase of a package or a best-of-breed component, to the selection of the optimal partners. Another crucial part of a legacy system replacement is the implementation of the new system as it can represent a major challenge notably in terms of project management, customization effort and migration. Implementations are particularly challenging when they involve multiple vendors and integrations.

To help our insurance customers figure out all the factors at play, every year we describe some cases in the frame of our Model Insurer program. This year we will be presenting the three cases we have received among more than 20 submissions in the frame of our Innovation & Insight Day event, which will take place in Boston on the 4th of April 2017. In addition to presenting the legacy modernization category award winners, we will also explain why they have decided to replace their legacy systems and what opportunities have been identified. We will also describe the implementation effort and draw out lessons learned. For those of you who will not be able to make it in person, we will publish a report profiling the three winners but I hope to meet you in big number at our event in Boston.

Data in insurance is not only about technology

Data in insurance is not only about technology
In October 2015, I explained that insurers had to hire more data experts if they wanted to better leverage all sorts of data sources they can access nowadays. As I raised this point, I shared the result of a survey we launched in 2015 to identify whether insurance companies were hiring new types of profiles to complement their teams looking at data. For more on this, read the following post: Why the insurance industry needs more data scientists. In March last year, I explained that insurers attempt to hire more data expert had become a clear trend: Insurers are investing in data scientists. With the growing importance of data in insurance and taking into consideration all the activities currently happening around data notably supported by InsurTech companies, we identify that not only insurers are hiring highly qualified data experts but also that these people are getting more and more influential within their organization. Indeed when asked about the level of influence on key business decisions these experts (internal or external consultants) have in their organization it seems that data scientists are gaining more power ​(in % of insurance respondents; n=135): Actually, two categories of experts are gaining influence in insurance: data scientists and user experience specialists. We are not surprised by this result. Insurers deal with a greater amount of data and more sophisticated technologies, therefore they need to hire highly educated experts in order to valuably leverage this data and these technologies. In addition, insurers consider customer interaction to be a key element of their digitization efforts and this is the reason why they are giving more responsibilities to user experience specialists. We will soon publish a report detailing the result of an insurance survey on the use of consumer data and smart technologies. I recommend you take some time to read our report to better understand what insurers are doing around this topic.

When plumbers sell insurance

When plumbers sell insurance

Digital and digitization in insurance are terms that have been increasingly used in the insurance industry over the past decade and not only by insurers but also by consultants, IT vendors and research firms. I have already provided my high level definition of digital and digitization in this blog.

While attending RGI's Next event, where an innovation for the connected home was presented, I reflected on the visibility of the relationship between the insurer and the end-consumer. Many innovation and digital gurus claim that with digitization insurance will become invisible. At the first sight, it sounds like an interesting idea and of course it would be logical to believe that if there is less or no human intervention then it would be difficult for a consumer to get a physical representation of an insurance product and the company behind it. However, I don’t like the idea of insurers becoming invisible. Insurance is a difficult product to understand for average consumers because it is not something they can touch and feel. In addition, risk is a concept that is highly conceptual especially for young people. Many consumers, who buy insurance for the first time, do so because it is compulsory and in general they don’t try to analyse the details of the product, which is nothing more than a list of benefits, terms and conditions that are painful to read and difficult to understand. I think digitization represents a great opportunity insurers have to seize to better productize insurance products. Making insurance invisible does not properly address the consumers’ needs and expectations I think. In our open world where information is so easily accessible and transferrable and where transparency is important, insurers need to make insurance more palpable and digitization is a great opportunity to democratize the knowledge of insurance and risk among the public. Let’s take the example of home insurance. What if home insurance is sold on top of a box (an Apple TV style one) that controls various sensors that monitor home parameters including thermostats, smoke detector, video surveillance and water usage? The insured would be able to regularly check these sensors via a smartphone app and be informed quickly about abnormal events. With this box, the insurer would add home insurance at a preferred price (maybe included with the box warranty). The connected home model is an interesting example demonstrating that digital transformation can contribute to making insurance products more palpable and risk easier to understand and to monitor from a customer point of view. So when will we see plumbers and electricians sell home insurance!

Using private consumer data in insurance: Mind the gap!

Using private consumer data in insurance: Mind the gap!

Insurance is no different to other industries when it comes to capturing valuable data to improve business decisions. At Celent we have already discussed how and where in their operations insurance companies can leverage private consumer data they can find on social networks, blogs and so on. For more information you can read a report I have published this year explaining Social Media Intelligence in insurance.

Actually there are various factors influencing insurers' decision to actively use private consumer data out there including among others regulation, resources adequacy, data access and storage. I think that an ethical dimension will play a more important role going forward. More precisely I wonder whether consumers and insurers' perceptions about the use of private consumer data are divergent or similar:

  • What do consumers really think about insurance companies using their private data on social networks and other internet platforms?
  • What about insurers; does it pose an issue for them?

In order to assess this ethical dimension, we have asked both insurers worldwide and also consumers (in the US, UK, France, Germany and Italy) what where their view on this topic. To insurers, we simply asked them what best described their opinion about using consumer data available on social networks (Facebook, Twitter, LinkedIn, etc.) and other data sources on the internet (blogs, forums, etc.). To consumers, we asked what were their opinions about insurers using these open data sources for tracking people potentially engaged in fraud or criminal activity.

The following chart shows the result and indicates that there is a big gap between the two sides:

UseConsumerData

Overall what is good for consumers is not necessarily good for insurers. In the same way, what insurers want is not always in line with what consumers expect from their insurers. Going forward the question for insurance companies will be the find the right balance between the perceived value of private consumer data and customers' satisfaction. In addition, it will be tough for them to figure out the impact (pros and cons) of all factors at play in the decision to invest in technologies allowing for the efficient use of private consumer data accessible on the Internet.

At Celent, we are trying to define a framework that can help them structure their reasoning and make an optimal decision. So more to come in the coming weeks on this topic…

Insurers are investing in data scientists

Insurers are investing in data scientists
A few weeks ago I described a few results of a survey we have launched during the last quarter of last year around the role and importance of data in insurance. My blog post can be found here. Since then we have published a report summarizing the findings of this survey that our members can find here. An interesting trend we identified based on this survey was the need for insurers to hire more data scientists with advanced degrees and strong background in data and computer science. Indeed we think technology is not enough nowadays and insurers need to also invest in people with deep skills in this domain. I recently came across the following article from INN: Sentry Insurance Gifts $4 Million to Grow Data Science. It seems to validate our findings and I expect to see more of these kinds of initiatives going forward.

Social media intelligence and insurance – don’t listen to everything if you want to hear something

Social media intelligence and insurance – don’t listen to everything if you want to hear something
In a 2011 report titled Using Social Data in Claims and Underwriting: Creating a Social Risk Profile, Celent looked at how insurers could leverage social networks to do a better job in claims and underwriting. Since then, we have been looking at vendors who can complement insurers internal data with external data sources including social media data and this in the frame of different applications that go beyond underwriting and claims. We notably have profiled and will continue to profile vendors active in the predictive analytics space and for which data sources are as important if not more important than pure features and functions they offer as part of their system. Using social media data in insurance has become more important over the past few years and what can be called now social media intelligence goes beyond a simple technology that taps in all sorts of social network data sources. Indeed for many people social media intelligence or what people also call social media listening purely consists in screening social networks to get data that can complement internal data to make a better business decision. Actually this definition is too succinct and does not include all key phases a proper social media intelligence strategy should include: ScreenHunter_496 Feb. 29 10.29 So we define social media intelligence as the strategy consisting in:
  1. Defining strategic objectives that are dependent not only on internal but external data,
  2. Defining a referential or a group of topics, relevant social media platforms as well as a geographic and language scope to be considered for the analysis,
  3. Filtering and analyzing social media data regularly (real time, daily, monthly but it is generally a continuous process)
  4. Implementing an action plan leveraging findings derived from the data analysis to achieve the strategic objectives initially defined.
We think insurers can learn from project and use cases other industries have gone for in the Social Media Intelligence space and we are interested to better understand how these examples can generate fruitful ideas for insurers. Stay tuned as Celent will be covering this topic in more detail in the near future.

A consolidation wave is reshaping the EMEA PAS vendor landscape

A consolidation wave is reshaping the EMEA PAS vendor landscape
At Celent, we have been writing reports profiling policy administration system (PAS) vendors for a long time. In the European, Middle East and African region (EMEA) we have covered up to 50 vendors in some of our bi-annual reports and we know there were approximately twice more active in this region of the world.  The most recent report focused on life PAS in EMEA can be found here. Since our first look at the PAS market in the EMEA region in 2007 we have predicted that its fragmentation and its heterogeneity would lead to a consolidation. It is fair to say that we have been wrong with our prediction or without less humility we can say we have been right but our timing was bad. Indeed, it seems that the consolidation phase we predicted has started to materialize a few year ago but certainly not as early as we thought. In other words we have observed a surge in mergers & acquisitions over the past few years and we think it will still accelerate in the coming months. The most recent acquisition that validates our view is the acquisition of the Danish vendor Edlund by  KMD Group that has been announced this week. Overall we see various kinds of acquisitions:
  • Software integrators-driven acquisitions: large software integrators are trying to diversify their service offering through the acquisition of insurance system IP. The best example of this type of strategic move is for instance the acquisition of Wyde by MphasiS a few years ago.
  • The Private Equity (PE) firms-driven acquisitions: there is a growing interest to invest in the insurance core system space for PE firms. The best examples of this type of acquisitions are the contribution of Riverside in the merger between Charles Taylor and Fadata or Waterland Private Equity investment in Keylane that now combines activities of various PAS vendors including formerly branded LeanApps, Quinity, Mantcore and more recently the German vendor called Geneva-ID.
  • The core system vendor-driven acquisitions: PAS vendors understand they can grow quicker if they merge with a competitor. Sapiens acquisition of FIS Software and IDIT or Prima Solutions acquisition of Albiran a few years ago are good examples.
As already mentioned we expect more M&A to come and we are glad to help our insurance clients to navigate this changing market.  

The schizophrenic nature of innovation in insurance

The schizophrenic nature of innovation in insurance
I have attended various conferences on innovation over the past few years. In almost all of them futurologists of all kinds and innovation experts who are invited to present tend to use the same examples, such as Uber and AirBnB, to describe how new business models can disrupt an industry. The message to insurers is strict and clear: one day the insurance industry will have its own Uber that comes in and disrupts the traditional insurance business model. They present these models as forming part of social revolution where consumers come together to demand a new style of service, based upon social equity and reinforced by free-spirited democratic principles. In some respects, they’ve taken their lead from the Internet generation of superfirms that dominate our digital lives (such as Google, Amazon, eBay, and Facebook). While I fully agree that insurers have to innovate, anticipate, and adapt to changes impacting our industry, I have to confess that I find the usual message too simplistic. What particularly strikes me is the lack of criticism towards these firms. Indeed companies have been embracing and advocating non-discriminatory values for decades in various guises (e.g., gender equality, ethnical diversity, etc.). The US has been proudly supporting these values in the global economy, and the Silicon Valley companies have been keen to promote this message. Therefore I am surprised to observe that these companies have exported their business model but neglected its social impact in new territories. The recent developments around Uber in France are a good example of this. Taxi drivers have to pay a high license authorization to be able to do their job. Many of the taxi drivers have to invest their pension to get a steering wheel. This entry tax is compulsory and supports the community, like all taxes do in every country. Don’t get me wrong, these innovative companies have brought to the market great products, services, and added value. I think they contribute to helping their industry change in a positive way. However, I think they are schizophrenic in a certain way, as they tend to forget their social egalitarian values when economic value is at stake. I am maybe naïve enough to believe that the future of our industry is not only about innovation at all costs but also about responsibility of all economic agents, including companies as well as consumers. In a world where innovation experts place schizophrenic innovators as examples, I hope consumers’ responsibility and their sense of fairness will help our industry keep a critical mind on the future of innovation and innovators. Maybe there is an innovative business model to create out of this concept?

Why the insurance industry needs more data scientists

Why the insurance industry needs more data scientists
Celent will soon be publishing an update to our 2013 report Perceptions and Misconceptions of Big Data in Insurance. In this report we looked at various elements in relation to the role and perception of data in insurance to understand where the industry was in terms of adoption of data-related technologies and more particularly Big Data. To do so we used what we call our Big Data Maturity Model. This model uses seven dimensions to categorize the industry in terms of their maturity level when it comes to adopting Big Data: Figure 1 big data   We came across an interesting article recently in the Insurance Journal that said insurers needed to hire more Big Data professionals. While we agree with this statement, we have already noticed in the early results of our 2015 survey (still in progress) that insurers have now more data scientist experts as shown in the following figure: Figure 2 data tools Technology is not enough and insurers have understood that if they want to make the most of data-related technologies they need to hire highly skilled people with solid knowledge of machine learning, statistics and predictive analytics. This is an interesting early finding and we look forward to provide our members with more on our seven model dimensions soon. Stay tuned!