resulting NGP enables Octo Telematics to store, process, and analyse data
generated by over 5.3 million drivers totaling 175 billion driven miles, and
that increases by over 11 billion additional data points daily. It also allows
for complete flexibility in the selection of sensors, analysis and output of
data for all insurance and automotive services.
Telematics has transformed the vehicle
insurance industry over the past few years. Insurers are increasingly offering
usage-based insurance (UBI) products, based on the data gathered from GPS-connected
Telematics, a portmanteau of telecommunications
and informatics, enables the real-time transmission, receiving and storage of
data and information from remote objects such as vehicles. The information
could include location tracking of vehicles, driver behaviour, maintenance
requirements and data on accidents.
Now, developments in Internet of Things
(IoT) technology present a further opportunity for insurers to move beyond
connected vehicles and offer new insurance propositions in the home, commercial
property, life, and other insurance lines. IoT can connect insurers to the
assets they are insuring, whether that is a vehicle, a property, or a person.
This allows insurers to understand the exact status of any insured items and
potentially take action in response to an abnormal situation, such as detecting
a fire, a vehicle collision, or an abnormal heartbeat.
To take advantage of these next generation
IoT-based insurance propositions, Octo
Telamatics, a market-leading telematics service provider, developed a new
platform, which they called the Next Generation Platform (NGP).
pioneer in vehicle telematics
Established in Italy in 2002, Octo
Telematics was one of the first companies to support insurers in the then
vehicle telematics space. Since then, the company has established itself as the
global leader in the telematics service provider (TSP) space. It has one of the
largest global database of telematics data, with over 186 billion miles of
driving data collected and 438,000 crashes and insurance events analysed (as of
31 December 2017).
Octo Telematics captures a comprehensive
set of data from a vehicle, including the speed, location, and journey
duration, as well as aspects of a driver's behavior, such as how harshly they
accelerate or brake and how quickly they corner. This data is combined with
further contextual information, such as the local weather conditions, road
type, and current traffic situation, and analysed to provide the insurer with a
detailed profile of the true risk posed by a specific driver at any particular
learning, the company can make more accurate predictions and risk models, thus allowing the insurer to calculate a premium level that accurately
reflects the risk and usage to the level of the individual policyholder.
Telematics also offers the ability to
detect and respond to crash and claim incidents in real time, and to react in
the most appropriate way, by alerting emergency services or dispatching
roadside assistance. The telematics data captured during a claim incident also
provides insurers with a precise view of a claim, enabling decisions about
liability, the likelihood of fraud, and estimated cost of repair to be made in
a fraction of the time. As claims expenses typically account for between 70%
and 80% of an insurer's costs, this can have a significant effect on an
insurer's profitability. In addition, it can dramatically improve the
customer's experience of the whole process, and boost customer retention.
of dealing with growing volumes and variety of IoT data
Octo Telematics had developed a proprietary
telematics platform that had evolved over the last 15 years. However, with the
growth of IoT and an order of magnitude increase in the number and types of
connected sensors, Octo Telematics foresaw that the current platform would
increasingly become a constraint on the company's growth ambitions.
One of the biggest challenges was that the
existing platform was designed around the needs of vehicle telematics and could
not easily accommodate other types of sensors, such as wearables, smart
watches, smart locks, smoke detectors, and surveillance devices, which are
becoming increasingly important components in IoT insurance propositions.
The growth in sensors also implied the need
to monitor data from potentially tens of millions of connected devices in the
near future. Though the old platform was able to support over 5 million
vehicles, the platform was reaching the limits of scalability.
The data management platform also needed to
accommodate a broad range of inbound data types, ranging from real-time streams
from in-vehicle telematics devices to bulk uploads from other sources, such as
third-party weather data. There is also significant variation in the formats of
stream data depending on the application and capabilities of the sensor. This
can vary from relaying a simple journey start and finish time through to
detailed crash reconstruction data from units incorporating sophisticated
sensors, such as six-axis accelerometers with very high sampling rates. This
data diversity will increase further, potentially to include images and video
The increased number of items being
monitored would also require significant growth in the compute and storage
capability needed to support real-time analysis across many millions of sensors.
The data captured by the platform, whether
from vehicles, properties, or people, needed to be closely coupled to the
incident response and claims processes to enable insurers to offer
policyholders a fully integrated IoT insurance proposition. The existing
platform lacked this high degree of integration.
In addition to capablities of accommodating
potentially orders of magnitude, the data management and analytics
infrastructure would also have to ensure the total security of all inbound data
or "data in motion," as well as that of data within the platform
residing on disk and other storage media ("data at rest"). The challenge
is compounded by the sheer volume of data from connected sensors, numbering in
the millions, distributed across a wide geography.
and implementing a co-innovation approach
Due to the scale, complexity, and
criticality of the development needed to realise the NGP in a time frame that
would allow Octo Telematics to capture the emerging IoT opportunity, the
company decided to adopt a co-innovation development model.
Octo Telematics used its understanding of
the evolving insurance market to define the functional requirements of an NGP
capable of supporting a broad range of new IoT-based insurance propositions.
Key technology partners were identified for
the development of the NGP: Cloudera, Software AG, Salesforce, SAS, and SAP.
Using this co-innovation approach, Octo Telematics and its partners were able
to accelerate the design and implementation of the NGP, delivering a complex
and challenging development project in under 24 months.
The initial phase of formulating the
approach and conducting a dialogue with the partners to refine and improve the
architecture of the NGP took seven months. A jointly agreed co-innovation
roadmap was created. The implementation took 18 months of development, with an
initial prelaunch version being released to key existing Octo Telematics
clients at the end of 2016. Following the beta testing phase, the full
commercial version of the NGP was released in July 2017. All new Octo
Telematics clients are now supported on the NGP, with a migration plan in place
to move the majority of existing clients to the new platform.
11 billion additional data points daily
The resulting NGP enables Octo Telematics
to store, process, and analyse data generated by over 5.3 million drivers
totaling 175 billion driven miles, and that increases by over 11 billion
additional data points daily. It also allows for complete flexibility in the
selection of sensors, analysis and output of data for all insurance and
And the backbone of this NGP is powered by
Cloudera’s machine learning and analytics platform. The Cloudera Enterprise suite
includes a set of tools to provide security, governance, and workload
management functionality operating within an integrated data and platform
model. The platform provides the underlying infrastructure to ingest, process,
and analyse huge volumes of structured and unstructured data, while being able
to perform analytics on both streaming and static data sources. All inbound
data, data moving between multiple clusters, as well as data stored within the
platform, is encrypted.
A "scale out" hardware approach was
adopted, as opposed to “scale up”. Scale-up is done by adding more resources to
the existing nodes of a system, while scaling out involves adding additional
infrastructure capacity in the form of new nodes, which can be done through the
use of commodity on-premises and cloud-based hardware. This avoids the need for
investment in expensive high-performance servers, as storage and compute
The NGP also utilises Cloudera's Shared
Data Experience (SDX)
module to define and enforce unified user and role-based access and security
policies, as well as provide auditing capabilities at the application, cluster,
and environment level.
Using Apache Spark, Octo Telematics is able
to leverage the huge volumes of data, the compute power of multiple clusters,
and a resilient distributed data set (RDD) structure to quickly implement,
train, and test machine learning models.
These models allow Octo Telematics and its
insurance customers to better understand, model, and price risk, and can form
the core of new innovative insurance products.
Inherent in the Cloudera Enterprise
platform's distributed computing model is the ability to operate the NGP both
on-premises and across private or public cloud. The ability to flexibly use
major cloud service providers such AWS, Google Cloud Platform, and Microsoft
Azure means the NGP can support transient but compute-intensive projects, such
as testing new pricing algorithms or risk model development, on a usage-based
The NGP has resolved the capacity issues of
the previous platform and is now continuously scalable. It will only require
additional cloud-based compute and storage resources to accommodate the growth.
The enhanced functionality in areas such as
CRM and incident analytics, as well as the increased capacity of the NGP, means
that Octo Telematics can offer all insurance clients detailed, real-time crash
reconstruction capability. This will allow users to drive significant
efficiency improvement in claims processing, identify potential fraud, and
enhance the customer's claims experience.
Octo Telematics' insurance clients also benefit
from the additional functionality of the NGP by being able to introduce new
types of IoT-based insurance products. For instance, one client introduced a
property insurance product that uses a home hub, developed by Octo Telematics,
that is equipped with smoke, heat, flood, and intrusion sensors. Another
insurer introduced a pet insurance product using IoT-based GPS tags worn by the
pet. Yet another is piloting the use of smart watches as part of a health and
life insurance offering.
Furthermore, the NGP is reducing time to
market for new product launches by more than 50%. The time to implement a new
UBI product has been reduced from two to three months to four weeks.
Currently, most insurers implement UBI offerings
as stand-alone projects requiring parallel core administration and claims
systems. To address the inefficiencies and complications from this, Octo
Telematics is working with core insurance software vendors to develop a range
of connectors that will allow direct integration between the NGP and an
insurer's core processing systems. This direct integration will significantly
reduce the cost of entry and complexity for insurers wanting to offer IoT-based
As of November 2017, Octo Telematics had
developed a connector allowing direct integration of the NGP with the policy
administration and claims suite of Guidewire, a software for property and
casualty (P&C) insurance providers.
Octo Telematics is also looking at
extending vertical-specific functionality to the NGP beyond the telematics
sector, in support of a wider spectrum of industries, such as the telecoms,
energy and utilities sectors.
All information from customer
success story and Ovum
case study at www.cloudera.com.
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