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- Coming up, whether you are in human resources,
a compliance officer, or IT admin,
regardless of your industry or sector,
we'll take a look at new intelligence
supervision capabilities Microsoft 365
designed to help you monitor communication
in your digital environment,
and encourage the right behavior
as people work together in chat and Microsoft Teams,
in email and Outlook and more.
Monitoring digital communication
is critical to mitigating inappropriate
conduct, reputational, and financial risk.
The new supervision capabilities
in Microsoft 365 give you built-in
cross industry supervisory capabilities
over specific content in communication
that could impact both individuals
and your organization.
For example, you may have a corporate
policy for anti-harassment in the work place
or cyber-bullying in education.
Or a need to catch and prevent leaks
for confidential projects as part
of your risk management.
Or demonstrate that you have measures
in place to mitigate insider trading
to fulfill regulatory compliance.
The new built-in supervision capabilities
in Microsoft 365 allow you to define
the type of communication violation
that require your attention
while greatly simplifying the review process
and eliminating the need to journal
data outside of Microsoft 365.
Under Supervision you can quickly see
what needs your attention.
You can see top policy violations
and you can see how many items
have been flagged as compliant,
resolved, questionable, or non-compliant.
Let me start with incidents
flagging communication associated
with out anti-harassment policy.
Click on the policy,
click on open,
and click on the items
that are pending review.
Now I can quickly see that there are
some repeat offenders with respect
to this policy.
Now this message has been flagged
for signs of inappropriate language.
There's no profanity in this message
but there's definitely questionable intent.
And that's where a machine learning model
really shines,
by tuning in to the sentiment
within the message.
As a human resource manager I can
make the final assessment on how
I judge the communication.
I can flag it as non-compliant
and I can add a comment for my colleague
to review for further action.
Now let me give you another example
related to regulatory compliance,
specifically this anti-money laundering
policy I've got.
I can see this instant Bloomberg message
has been flagged for review.
There's a bank routing number,
along with trigger words,
and I'll show you how to define
these type of conditions in a minute.
I can see similar patterns in this
instant message from Microsoft Teams.
To save time in review you can
bulk resolve multiple items with just
one click saving you time and effort.
Also all supervision reviewed activities
and policy rule changes are fully audited.
Here I can see all activities
by reviewer, by policy, over time.
So you're always ready for regulatory audits.
Now let's switch gears to show you
how easy it is to create a policy.
First click on create.
You'll see the key steps articulated
on the left pane.
You start by naming the policy,
Insider Trading,
you then choose the target audience
you want to supervise, which is
typically represented as a group
in your active directory.
We'll select the All Brokers group.
Next you can choose the communication
modality to be included in review.
Email and Teams are selected by default.
And as I showed you earlier
with the Bloomberg example
you can also supervise
non-Microsoft communications.
Now where this gets interesting
is where you define conditions
or filters and patterns you're looking for.
You can choose to monitor inbound
or outbound communications
or even communications between individuals.
You can also use our intelligent filters
with built-in classifier such as
the offensive language that you saw
in our anti-harassment example.
We have a lot more coming
around machine learning
over the next couple months.
First we'll continue to deliver
out of the box classifiers such as
attorney-client privilege.
Secondly you will be able to create
your own classifier based on your own
data set in the future.
Equally, you can use advanced sensitive
types for exact match.
You can leverage from over 100 templates
that we have out of the box ranging
from privacy, medical, health, or financial.
For instance I can easily narrow down
for the US specific patterns related
to financial data such as credit card
number or routing number,
again some from the examples that we used earlier.
Additionally you can define your own
lexicon of terms and patterns for supervision.
Then with advanced message filters
you can further reduce what type of communications you're looking for.
For example you can exclude common
email traffic from a specific source
such as a recurring email newsletter
so that they don't get surfaced
during the supervision or block specific domains.
And once you are done specifying
your conditions you can determine
the percentage of communications
you'll like to review.
For corporate policy you might want
to monitor 100% of communications
since you have zero tolerance for harassment.
Whereas for regulatory compliance
you might only want to monitor 10%
due to the sheer volume of communications.
Next you need to define the reviewers
that will have access to the review process
we defined earlier.
And from there you can review the policy
you've defined and voila you are done.
The supervision capabilities of Microsoft 365
are available today and we've seen
by just notifying users and having
the supervision capabilities turned on
in your environment can act as a deterrent
to inappropriate behavior while giving
you insights into communication trends.
And we have lots more supervision updates
coming up ranging from meta-support
for additional content types for monitoring
such as Skype online, Bloomberg, or Facebook,
new intelligent policies
with out of the box classifiers
and our organization-specific classifiers,
as well as keyword highlighting and
threaded instant messages to shorten
the review process.
To learn more please visit aka.ms/supervision
Microsoft 365 today
just try it.
Thank you for watching.
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