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DIGITAL UNDERWRITING: RIDING THE INSURANCE TRANSFORMATION WAVE WITH MONGODB
Try MongoDB Atlas for Free Today
Jeff Needham and Silvio Sola
August 25, 2022
#Industry#Insurance
In our previous article about digital underwriting, “A Digital Transformation
Wave in Insurance,” we covered the main challenges insurers face when it comes
to streamlining and modernizing their underwriting processes, along with key
areas that can be improved by leveraging the power of data and artificial
intelligence.
We analyzed how modern IT trends require a complete redesign of manual
underwriting processes to enable insurers to leverage new market opportunities
and stay relevant in an ever-changing risk landscape. We explored how the full
underwriting workflow — from the intake of new cases to risk assessment and
pricing — can be redesigned to ease the burden on underwriting teams and enable
them to focus on what matters most.
In this second article, we’ll expand on how new technology paradigms can support
transformation initiatives in this space and describe the pivotal role MongoDB
plays in disrupting the industry.
THE IMPORTANCE OF DATA AND NEW TECHNOLOGY PARADIGMS
For digital underwriting transformation initiatives to succeed, organizations
must move away from monolithic applications, where data is siloed and
functionality is fragmented across different technologies. However, as many
organizations have additionally come to realize, lifting and shifting these
monolithic applications to the cloud does not automatically bring them closer to
achieving their digital objectives.
Organizations that are successful in their transformation efforts are
increasingly adopting MACH architecture principles to modernize their
application stacks. The acronym stands for Microservices, API-first,
Cloud-based, and Headless, and, combined, those principles enable developers to
leverage best-of-breed technology and build services that can be used across
multiple different business workflows and applications.
These principles allow software delivery teams to reduce the time it takes to
deliver new business features and promote significant reuse and flexibility far
beyond the monolithic applications that pre-date them.
From an insurance perspective, this approach enables underwriting systems to be
decoupled into business and capability domains, each working independently, yet
sharing data as part of an event-driven design and microservices architecture.
Often overlooked, shared capability domains can provide significant value to an
organization's business domains, as seen in the visual below.
Figure 1. Key business and capability domains.
Each function of the application should be owned by the team holding expertise
in that particular domain and be loosely coupled with the others. Services can
communicate with each other via APIs, as well as listen for and consume one
another's events.
Building a domain-based data modernization strategy can also enable a phased
migration away from legacy systems. This allows for immediate realization of the
organization's digital objectives, without first engaging in a costly and timely
legacy system replacement effort.
An event-driven, and API-enabled architecture allows for real-time data
processing, a core component of digital enablement.
Figure 2. Microservices and event-driven architecture.
Read the previous post in this series, "A Digital Transformation Wave in
Insurance."
DECISION SUPPORT SERVICES
Once monolithic systems are decomposed into finer-grained domains and services
and begin interacting via APIs and events, it is possible to focus on the most
crucial component that brings all of them together — the decision support
domain. Its role is to streamline and, where possible, automate underwriting and
other decision-making processes that traditionally require heavy administrative
and manual work in order to reduce operational expenses and enable critical
underwriting staff to focus on highest priority work.
Effective underwriting processes require pulling together multiple teams and
capability domains (e.g., claim, customer, pricing, billing, and so forth) to be
able to reach a decision on whether to insure a new customer or define an
adequate pricing and coverage model, among other factors. A decision support
engine has the power to fully automate those steps by automatically triggering
workflows based on specific events (e.g., a new claim is submitted in the
system) as part of the event-driven design referenced earlier to enable
real-time decision making.
WHY MONGODB
With the added burden of integrating and working with various sources of data —
from APIs to events to legacy databases — and doing so in real time, software
delivery teams need a developer data platform that allows them to tame
complexity, not increase it.
Refactoring systems that have been around for decades is not an easy feat and
typically results in multi-year transformation initiatives. MongoDB provides
insurers with the same ACID capabilities of relational databases, while
introducing new tools and flexibility to ease transformation by increasing
developer productivity and fully supporting the MACH principles.
THE MONGODB APPLICATION DATA MODEL
MongoDB provides a developer data platform leveraged by some of the world’s
largest insurers. It possesses key capabilities that allow it to:
* Integrate legacy siloed data into a new single view. The flexibility of the
document model enables the integration of separate, legacy data stores into
an elegant, single-view data model that reduces rather than increases
complexity. Without the complexities of another canonical, relational model,
application development and data migration efforts are dramatically
simplified, and delivery timelines shortened.
* Manage the full lifecycle of containerized applications. MongoDB’s Enterprise
Operator for Kubernetes lets you deploy and manage the full lifecycle of
applications and MongoDB clusters from your Kubernetes environment for a
consistent experience regardless of an on-premises, hybrid, or public cloud
topology.
* Automate workflows, leveraging events in real-time. MongoDB provides the data
persistence at the heart of event-driven architectures with connectors and
tools that make it easy to move data between systems (e.g., MongoDB Connector
for Apache Kafka), providing a clear separation between automated
underwriting workflows and those requiring manual intervention.
* Enable business agility using DevOps methodologies. MongoDB Atlas, the global
cloud database for MongoDB, provides users with quick access to fully managed
and automated databases. This approach allows development teams to add new
microservices and make changes to application components much more quickly.
It also saves a substantial amount of operations effort, since database
administrators are not required in every sprint to make and manage changes.
* Work quickly with complex data. Developers can analyze many types of data
directly within the database, using the MongoDB Aggregation Pipeline
framework. And, with the power of Atlas Federation, developers can do this
without the need to move data across systems and complex data warehouse
platforms, providing real-time analytics capabilities that underwriting
algorithms require.
MongoDB offers a flexible developer data platform that maps to how developers
think and code, while allowing data governance when needed. It is strongly
consistent and comes with full support for ACID transactions.
Figure 3. The MongoDB developer data platform.
The MongoDB developer data platform addresses a range of use cases without added
complexity, including full-text search, support for storing data at the edge on
mobile, data lake, charts, and the ability to deliver real-time analytics
without moving data between systems. It also provides developers with a powerful
yet simplified query interface suitable for a variety of workloads, enabling
polymorphism and idiomatic access.
Contact us to find out more about how the MongoDB developer data platform can
help you streamline your insurance business.
← Previous
4 WAYS TELCOS DELIVER MISSION-CRITICAL NETWORK PERFORMANCE AND RELIABILITY
Tech leaders like Google, Apple, and Netflix set a new standard for customer
service. Today’s customers expect intuitive, always-on, seamless service that
challenges telecommunications companies’ network performance and reliability.
This article examines several ways that companies can meet these challenges
through an automated, data-driven approach. How a modern data platform can help
A fully integrated, customer-centric, and data-driven approach to service
delivery and assurance is needed to remain competitive. Modern
telecommunications enterprises are tackling this problem by investing in areas
like AI and machine learning, for example, which can help them identify
correlations between disparate, diverse sources of data and automate end-to-end
network operations, including: Network security Fraud mitigation Network
optimization Customer experience Furthermore, by adopting a modern data
platform, companies can easily answer questions, such as the following, that are
nearly impossible to resolve when relying on legacy technology: Is an event
likely to have a customer impact? Are customer-facing service SLAs being met?
Where should cell sites be placed for maximum ROI? Is new equipment deployed and
configured correctly? MongoDB’s developer data platform can help companies
provide the necessary performance and reliability to meet customers’
expectations in four key areas: reducing data complexity, service assurance
automation, network intelligence and automation, and TM Forum Open APIs.
Reducing data complexity One recent study found that data scientists spend about
45% of their time loading and cleansing data . For a true impact to your
organization, you need to free up that time to enable data scientists to focus
on mission-critical projects and innovation. Additionally, architectural
complexity, with bolted-on solutions and legacy technology, prevents you from
harnessing your data and having a true impact on network performance and
reliability. MongoDB’s developer data platform solves the great complexity
problem by supporting a diverse range of workloads from a single data platform.
Reducing the channels for data flow allows companies to establish a single
source of truth, achieve a customer-centric approach that is critical for
competitive advantage, and increase service assurance. Figure 1. MongoDB’s
developer data platform reduces complexity in telecommunications workloads,
resulting in more reliable network service for customers. With continuous uptime
and advanced automation, MongoDB’s developer data platform ensures performance,
no matter the scale. Service assurance automation In telecommunications,
always-on, always-available service both for the end user and internal IT teams
is critical. While outdated service assurance processes may have been viable
decades ago, the volume of data and number of users have grown exponentially,
making manually intensive processes of the past no longer possible. This volume
increase will continue to stress existing business support systems, and without
modernization, it will hamper the development of new revenue streams. Moving
from a reactive to proactive and then predictive model, as shown in Figure 2,
will enhance service assurance and enable organizations to meet the expectations
of the digital-native customer. Figure 2. The transition from a reactive to
proactive to predictive data model opens up new opportunities to use innovative
technologies like artificial intelligence. Network intelligence and automation
Consider the essential task of configuration and management of radio access
networks. On a daily basis, engineers change the angles of antenna towers, the
configuration of the radio, the nearest neighbor relations, and other events
your system tracks and manages. With an intuitive developer data platform, any
change in the configuration is saved in the data mediation layer (DML) for
anyone to see and track, making it easy for engineers to go to the DML to check
the configuration for a particular tower. Information that was previously
captured in one snapshot per day is now propagated in real time. Another example
— intent-based automation — abstracts the complexity of underlying
software-defined networking components by allowing intent to be specified and by
providing automatic translation. This type of automation allows teams to process
intent generated either by end user activity or via service assurance processes,
and that intent is translated into the underlying network state. Network events
determine whether the network is in the desired, stable state, and that
unintended states are addressed via automation, potentially using TM Forum
Network-as-a-Service APIs. TM Forum Open APIs The TM Forum (TMF) is an alliance
of more than 850 companies that accelerates digital innovation through its TMF
Open APIs, which provide a standard interface for the exchange of different
telco data models. The use of TMF Open APIs ranges from providers of
off-the-shelf software to proprietary developments of the largest
telecommunications providers. In working with many of the world’s largest
communication service providers (CSPs) and their related software provider
ecosystems, MongoDB has seen a significant number of organizations leverage
these APIs to develop new microservices in days, rather than weeks or months.
Through exposing common interfaces, CSPs are able to adopt a modular
architecture made up of best-of-breed components (either internally or
externally developed) while minimizing the time, effort, and cost required to
integrate them. The TMF Network-as-a-Service APIs, in particular, hold
significant potential for network automation. This API component suite supports
a set of operational domains exposing and managing network services. The
abstraction layer between network automation tooling and the underlying network
infrastructure provides a flexible, modular architecture. Network optimization
is vital to the survival of telcos in today’s competitive market. However, with
a modern developer data platform underpinning your network, you’ll be equipped
to meet and exceed customer expectations. Read our ebook to learn more about
implementing TM Forum Open APIs with MongoDB .
August 25, 2022
Next →
TEMENOS BANKING CLOUD SCALES TO RECORD HIGH TRANSACTIONS WITH MONGODB ATLAS AND
MICROSOFT AZURE
Banking used to be a somewhat staid, hyper-conservative industry, seemingly
evolving over eons. But the emergence of Fintech and pure digital players in the
market paired with alternatives in technology is transforming the industry. The
combination of MACH , BIAN and composable designs enables true innovation and
collaboration within the banking sector, and the introduction of cloud services
makes these approaches even easier to implement. Just ask Temenos, the world's
largest financial services application provider, providing banking for more than
1.2 billion people . Temenos is leading the way in banking software innovation
and offers a seamless experience for their client community in over 150
countries. Temenos embraces a cloud-first, microservices-based infrastructure
built with MongoDB, giving customers flexibility, while also delivering
significant performance improvements. Financial institutions can embed Temenos
components, like Pay-as-you-go, which delivers new functionality to their
existing on-premises environments, on their own cloud deployments or through a
full banking as a service experience with Temenos Transact powered by MongoDB on
various cloud platforms. This new MongoDB-based infrastructure enables Temenos
to rapidly innovate on its customers' behalf, while improving security,
performance, and scalability. Fintech, payments and core banking Temenos and
MongoDB joined forces in 2019 to investigate the path toward data in a
componentized world. Over the past few years, our teams have collaborated on a
number of new, innovative component services to enhance the Temenos product
family, and several banking clients are now using those components in
production. However, the approach we've taken allows banks to upgrade on their
own terms. By putting components “in front” of the Temenos Transact platform ,
banks can start using a componentization solution without disrupting their
ability to serve existing customer requirements. From May 2023 onwards, banks
will have the capability to deploy Temenos Infinity microservices as well as the
core banking Temenos Transact exclusively on the developer data platform from
MongoDB and derive even more value. Making the composable approach even more
valuable, Temenos implemented their new data backend firmly based on JSON and
the document model . MongoDB allows fully transparent access to data and the
exploitation of additional features of the developer data platform. These
features include Atlas Search , application-driven analytics , and AI through
workload isolation. Customers also benefit from the geographic distribution of
data based solely on the customer requirements, be it in a single country driven
by sovereignty requirements or distributed across continents to ensure always-on
and best possible data access and speed for trading. Improved performance and
scale In contrast to the retail-centric benchmark last year , the approach this
time was to test broader functionality and include more diverse business areas –
all while increasing the transaction volume by 50%. The benchmark scenario
simulated a client with 50 million retail customers, 100 million accounts and a
Banking-as-a-Service (BaaS) offering for 10 brands and 50 million embedded
finance customers on a single cloud instance. In the test, Temenos Banking Cloud
processed 200 million embedded finance loans and 100 million retail accounts at
a record-breaking 150,000 transactions per second. In doing so, Temenos proved
its robust and scalable platform can support banks’ business models for growth
through BaaS or distributing their products themselves. The benchmark included
not just core transaction processing, but a composed solution combining
payments, financial crime mitigation (FCM), a data hub, and digital channels.
"No other banking technology vendor comes close to the performance and
scalability of Temenos Banking Cloud. We consistently invest more in cloud
technologies and have more banks live with core banking in the cloud than any of
our peers. With global non-cash transaction volumes skyrocketing in response to
fast-emerging trends like BaaS, banks need a platform that allows them to
elastically scale based on business demand, provide composable capabilities
on-demand at a low cost, while reducing their environmental impact. This
benchmark with Microsoft and MongoDB proves the capability of Temenos’ platform
to power the world’s biggest banks and their BaaS offerings with hundreds of
millions of customers, efficiently and sustainably in the cloud." Tony Coleman,
Chief Technology Officer, Temenos This solution landscape reflects an
environment where everyone on the planet runs two banking transactions a day on
a single bank. This throughput should cater to any Tier 1 banking deployment, in
size and performance, and cover any future growth plans that they have. Below
are the transaction details that comprise the actual benchmark mix. As mentioned
above it is a broad mix of different functionalities behaving like a retail bank
and a fintech institute, which provides multiple product brands, e.g. cards for
different retails. Besides the sheer performance of the benchmark, the ESG
footprint of the overall landscape shrunk again versus last year’s configuration
as the MongoDB Atlas environment was the sole database and no secondary systems
were required. Temenos Transact optimized with MongoDB The JSON advantage
Temenos made significant engineering efforts to decapsulate the data layer,
which was previously stored as PIC, and make JSON formatted data available to
their user community. MongoDB was designed from its inception to be a database
focused on delivering a great development experience. JSON’s ubiquity made it
the obvious choice for representing data structures in MongoDB’s document data
model. Below you can see how Temenos Transact stores data vs Oracle or MSSQL vs
MongoDB. Temenos and MongoDB have an aligned data store – Temenos Transact
application code operates on documents (JSON) and MongoDB stores documents in
JSON in one place, making it the perfect partnership. MongoDB enables the user
community through its concept of additional nodes in the replica set to align
further secondary applications integrated into the same database without
interrupting and disturbing the transactional workload of Temenos Transact. The
regular occurring challenge with legacy relational database management systems
(RDBMS) where secondary applications suddenly have unexpected consequences to
the primary application is a problem of the past with MongoDB. Workload
Isolation with MongoDB MongoDB Atlas will operate in most cases in three
availability zones, where two zones are located in the same region for pure
availability and a single node is located in a remote region for disaster
recovery. This environment provides the often required RPO/RTO “0” while
delivering unprecedented performance. Two nodes in each of the first
availability zones provision the transactional replica set and ensure the
consistency and operation of the Temenos Transact application. In each
availability zone, a third isolated workload node is co-located with the same
data set as the other two nodes but is excluded from the transactional
processing. These isolated workload nodes provide capacity for additional
functionalities. In the example above, one node provides access to the MongoDB
Atlas Federation and a second node provides the interface for MongoDB Atlas
Search. As the nodes store data in near real-time – replication is measured in
sub milliseconds as they are in the same availability zone – this allows
exciting new capabilities like real-time large language model (LLM), e.g.
ChatGPT, or machine learning connecting to a Databricks lake house. The design
is discussed in more detail in this article . The below diagram shows a typical
configuration for such a cluster setup in the European market for Microsoft
Azure: one availability zone in Zurich, one availability zone in Geneva, and an
additional node out of both in Ireland. Additionally, we configured isolated
workloads in Zurich and Geneva. MongoDB Atlas allows the creation of such a
cluster within seconds, configured to the specific requirements of the solution
deployed. Typical configuration for a cluster setup for the European market for
Microsoft Azure Should the need arise, MongoDB can have up to 50 nodes in a
single replica set so for each additional isolated workload, one or more nodes
can be made available when and where needed. Even at locations beyond the
initial three chosen! For this benchmark the use of a MongoDB Atlas cluster M600
was utilized which was oversized based on the CPU utilization of 20-60%
depending on the node type. Looking backward a smaller MongoDB Atlas M200 would
have been easily sufficient. Nonetheless MongoDB Atlas delivered the needed
database performance with one third of the resources of last year's result, but
delivering 50% more throughput. Additionally MongoDB Atlas performed two times
faster in throughput per transaction (measured in milliseconds). Signed, sealed,
and delivered. This benchmark gives clients peace of mind that the combination
of core banking with Temenos Transact and MongoDB is ready to support the needs
of even the largest global banks. While thousands of banks rely on MongoDB for
many parts of their operations ranging from login management and online banking,
to risk and treasury management systems, Temenos' adoption of MongoDB is a
milestone. It shows that there is significant value in moving from a legacy
database technology to MongoDB, allowing faster innovation, eliminating
technical debt along the way, and simplifying the landscape for financial
institutions, their software vendors, and service providers. PS: We know
benchmarks can be deceiving and every scenario in each organization is
different. Having been in the benchmark business for a long time, you should
never trust just ANY benchmark. In fact, my colleague, MongoDB distinguished
engineer John Page, wrote a great blog about how to benchmark a database . If
you would like to learn more about how you can use MongoDB to move towards a
composable system, architecting for real-time adaptability, scalability, and
resilience, take a look at the below resources: Componentized core banking built
upon MongoDB Tony Coleman, CTO at Temenos and Boris Bialek, Global Head,
Industry Solutions at MongoDB discuss the partnership at MongoDB World 2022
Remodel your core banking systems with MongoDB
May 9, 2023
© 2023 MongoDB, Inc.
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