IBM Cloud Packs Transform Auto Claims
Key Points
- Insurance auto‑claims processing is currently slow, costly, and error‑prone, leading to high payouts, poor customer experiences, and pressure from disruptive tech‑focused insurers.
- IBM’s Cloud Packs provide a flexible, modern application platform that enables insurers to transform legacy claim‑management systems into data‑driven, automated workflows.
- An intelligent claims workflow can automate roughly 75 % of claim steps, using chatbots for data collection, AI models for fraud evaluation and complexity scoring, and automated task routing.
- In a demo, a policyholder initiates a claim via a mobile app, the system automatically populates the claim, presents repair options, and delivers a settlement offer, with only the minimal human interactions highlighted in red.
- The solution integrates with the insurer’s existing data‑center infrastructure, preserving mission‑critical legacy investments while adding the flexibility needed for rapid modernization.
Full Transcript
# IBM Cloud Packs Transform Auto Claims **Source:** [https://www.youtube.com/watch?v=bGwy98ra_E4](https://www.youtube.com/watch?v=bGwy98ra_E4) **Duration:** 00:05:57 ## Summary - Insurance auto‑claims processing is currently slow, costly, and error‑prone, leading to high payouts, poor customer experiences, and pressure from disruptive tech‑focused insurers. - IBM’s Cloud Packs provide a flexible, modern application platform that enables insurers to transform legacy claim‑management systems into data‑driven, automated workflows. - An intelligent claims workflow can automate roughly 75 % of claim steps, using chatbots for data collection, AI models for fraud evaluation and complexity scoring, and automated task routing. - In a demo, a policyholder initiates a claim via a mobile app, the system automatically populates the claim, presents repair options, and delivers a settlement offer, with only the minimal human interactions highlighted in red. - The solution integrates with the insurer’s existing data‑center infrastructure, preserving mission‑critical legacy investments while adding the flexibility needed for rapid modernization. ## Sections - [00:00:00](https://www.youtube.com/watch?v=bGwy98ra_E4&t=0s) **IBM Cloud Packs Transform Auto Claims** - The demo shows how IBM's Cloud Packs enable insurers to automate 75% of auto claim processing, using a data‑driven workflow, chatbot, and mobile app to speed resolutions and improve customer experience. ## Full Transcript
i'm dirk deroos lead cloud pack demo
architect
we're going to take a look at how ibm's
cloud packs can help insurance companies
modernize their approach to automotive
claims processing
today processing auto insurance claims
is inefficient slow
and costly the claims adjustment
workflow is filled with manual tasks
and this is a huge factor in keeping the
average time to resolution for claims
high
also adjusters under time pressure need
to make judgment calls based on limited
information
this results in many claims having
higher than needed adjustment payouts
these delays and error-prone processes
lead to poor customer experiences
at the same time traditional insurers
are under pressure from insurer tech
startups who are disrupting the auto
insurance space
so to help insurers ibm has developed an
intelligent workflow for processing auto
claims
at the center of this are ibm's cloud
packs which enable you to build flexible
modern applications this represents a
transformative change in the way
insurers handle claims
so basically we're setting a data driven
approach to support decision making
and we're automating 75 percent of the
claims processing steps
we have a simulated insurance company
that has provided its customers with
this mobile app
caitlyn smithers has just been in an
accident where someone rear-ended her
car so she's starting this claim from
her phone
we can see a chat bot engage with her
and gather information as the claim
progresses
on the agent dashboard we can now see a
new claim being initiated
the app actually pushes a request to
open the claim in the existing claim
management application
sitting in the data center there's no
agent driving this process
all the blue dots to the right of the
tasks you can see here represent
fully automated work and the red dots
show tasks that a human needs to do
for example where we see caitlyn
responding to requests for information
as she does this we can see the
dashboard light up with data points and
get fleshed out
we can also see green dots next to some
tasks as well
like invoke fraud investigation these
are tasks performed using ai
capabilities
so here the system feeds information
about the claim to a fraud evaluation
model
and as a more complete picture of the
claim emerges the models actually
predict
a low likelihood of fraud and that this
claim has low complexity
based on this evaluation the insurer has
now authorized the repairs
and presents caitlyn with repair choices
towing and transportation from the
accident site
and back in the app caitlyn is presented
with a settlement offer which she can
then accept
so let's look at what's behind these
apps in the intelligent claims workflow
we're going to start with the insurance
companies data center now for any
established insurance company
their existing it infrastructure is
mission critical it's got decades of use
investment and keeps their business
running every day there are always needs
for increased flexibility
but there's very little appetite to
build this in because migrating from
that established infrastructure
is expensive and disruptive as a
starting point for the solution we just
saw
we're going to leave the established
claims management application and any
supporting software like databases in
place
next up is the cloud pack for business
automation one of its major components
is the business automation workflow
tooling what we're looking at here
is a detailed graph of over 70 tasks
that make up the claims adjustment
process
a business process analyst and this
isn't a coder has built this out as an
automated workflow
and in the app that we just saw it's
actually this workflow that drives the
whole automated claims adjustment
process
so now we're looking at cloud pack for
data which is an ecosystem for everyone
whether you're a data scientist or a
business user
to work together on data projects this
is one of the tools
auto ai which is training our fraud
evaluation model
a really important design point that's
baked into this tooling is trust
your data stewards can make sensitive
data available for data scientists to do
their work and at the same time
define policies that actually hides
customers private information
and trust doesn't just apply to data it
also has to apply to machine learning
models
we saw in the agent dashboard for
example that caitlin's claim had a low
likelihood for fraud
and with club pack for data's model
explainability we can show the claims
adjuster the reasons behind that
and now we're looking at watson
assistant which powers that chatbot that
we saw engaging with caitlin
it integrates with our automated
workflow giving caitlin an easy customer
experience
which ultimately helps her deal quickly
with the accident
cloudpack for integration is the glue
that ties all these pieces together
integration developers use appconnect
api connect and kafka flows to enable
the mobile app and the claims dashboard
to talk with the claims management
application in the backend data center
and finally application developers have
built a set of cloud native
microservices that use all the
capabilities that we've looked at
to power the mobile app and the claim
agent dashboard
everything in this architecture diagram
except the original infrastructure in
the data center
is running in openshift here i'm looking
at the openshift container service
i can see all the pods that are powering
the cloud packs and also the new claims
processing microservices for the
dashboard and the mobile app this
container platform has a common
interface for devops
and administration of this whole
solution since it's based on openshift i
can deploy and run this anywhere i want
it can be in the same data center as the
existing infrastructure
i can be on ibm's cloud where i'm
running it now or some other vendors
cloud
and what's worth calling out here is
that while we've greatly modernized the
claims processing practice
we've kept the original systems intact
this saves us money
time and reduces risk and disruption
what we've built here is an almost
entirely automated process
and this frees customer service agents
and claims adjusters to focus on higher
value work
the insurance company provides a faster
and more flexible clean process for
their customers
and also embeds machine learning models
in the workflow that helps the claims
adjusters
25 of adjustment tasks are aided with
these models
this means adjusters can make much
better decisions for difficult areas
like
assessing total loss amounts and the
likelihood of liability
by taking advantage of their existing
customer base and wealth of data
we've used ibm's cloud packs to help
traditional insurance companies set a
solid competitive advantage
over new companies encroaching in this
market
you