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Thomas Stoesser l Oct 12, 2023 l Data Protection, Business Value, Insurance


HOW INSURERS CAN GROW THEIR DATA-CENTRIC BUSINESS THROUGH IMPROVED CYBERSECURITY

Data and users are what usually attract cyber-criminals to specific sectors and
organizations. And the insurance industry has both in droves. While carriers
play an integral role in helping their customers to transfer financial liability
for serious security breaches, they risk themselves becoming a target.

Effective data-centric security is therefore critically important—not just to
help insurers avoid big-name breaches that can cause severe financial and
reputational damage, but also to protect their main driver of growth: data
analytics.


DATA IN DEMAND

Insurance is a data-driven business. And often the data that carriers collect is
among the most sensitive information around. It includes customers’ financial
and personally identifiable information (PII) and often medical details that
could be used to commit identity and insurance fraud. As they come to rely
increasingly heavily on cloud-based services and homegrown code, insures are
also unwittingly expanding their own cyber-attack surface—offering more gaps in
protection for threat actors to probe. At an estimated global market size of $6
trillion, the insurance sector therefore represents a large and extremely
attractive target.

This is far from a theoretical threat. Among big-name companies in the vertical
that have already been breached this year area:

Managed Care of North America (MCNA) Dental: One of the largest US
government-sponsored dental care insurance providers had PII on nearly nine
million customers compromised.

Latitude Financial: An estimated 14 million customer records were stolen from
the financial services and insurance giant, making it the largest breach ever
recorded in New Zealand. This included around eight million driver’s license
details.

Aflac and Zurich: Around two million customers in Japan were impacted by a
supply chain breach impacting the same US sub-contractor shared by these
insurance multinationals. Compromised data included age, gender, last name,
policy number, insurance type number and coverage amount/premium.  


GROWING THROUGH DATA

Fundamental to the success of any insurer is its ability to derive insight from
large data volumes. That makes protecting this data absolutely critical to their
business model. The organization must have confidence that data hasn’t been
tampered with, and it must be able to analyze and process it without breaking
strict regulatory compliance rules.

Data analytics is big business. Insurers are estimated to have invested $3.6bn
in the technology in 2021 alone. It’s easy to see why. By deriving intelligent
insights from large data volumes, insurers can drive enhanced:

Lead generation: By understanding where to invest their money, for the lowest
customer acquisition costs.

Customer experience and satisfaction: By understanding where customer pain
points are most acute and helping to fix them, such as via self-support tools.
Analytics can also help insurers to personalize their offerings more effectively
for each customer.

Fraud prevention: By combining historical customer data with external contextual
data to flag suspicious activity with greater certainty. Predictive analytics
can even be brought in to alert which customers are most likely to submit
fraudulent claims. This is a big deal considering over $300bn is lost annually
to insurance fraud in the US alone.

Enhanced underwriting: Predictive analytics are helping to transform the complex
business of assessing customer risk profiles and pricing policies fairly.
They’re not only improving the accuracy of this process but also speeding it up,
which means insurers are less likely to lose prospective customers to rivals.

All of the above adds up to happier customers, more leads to target, reduced
fraud losses and, ultimately, improved revenue and growth.


ANALYZING DATA SECURELY

Yet as mentioned, this data must be secured in compliance with industry and
international standards and regulations without affecting its utility.
Technologies like tokenization help to do exactly that, ensuring data analytics
experts working in the sector can satisfy their compliance and security teams
whilst extracting the insights they need to drive value and growth.

This is where comforte’s Data Security Platform can help. It automatically and
continuously discovers and classifies data, wherever it is in the
organization—including in the cloud-based data stores used by analytics tools.
Then it applies tokenization or other optional data protection techniques to the
data to keep it secure throughout its lifecycle. This is data security first and
foremost for competitive advantage and growth.

--------------------------------------------------------------------------------

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CASE STUDY: FORTUNE 500 INSURANCE COMPANY AUTOMATES
DISCOVERY AND CLASSIFICATION OF SENSITIVE DATA:

Click the button below to download the case study:

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