Phone:
+91 96558 14047 (India)
+65 8237 9397 (Singapore)
+1 315 532 7622 (USA)
+27 11 886 1707 (South Africa)
+61 8 4634 1736 (Australia)
+44 (0) 208 123 3459 (UK)

Email: comms@neutrinos.co

Safeguarding customer data across New Business processes 

Introduction

The insurance sector deals with a vast amount of personal data, including information about individuals’ health, finances, and personal identification. This data is often handled by multiple individuals, including insurance agents, underwriters, and claims adjusters.

A breach of this sensitive data can have serious consequences, including financial losses and damage to the company’s reputation. Customers may lose trust in the company if they feel their personal information has not been properly protected, leading to a decline in business and damage to the company’s reputation.

Designing processes with technology can substantially reduce or eliminate privacy risks by limiting information access at each stage to only what is necessary for the human decision maker or system. Insurance companies must also implement robust data protection measures and train employees in data protection best practices such as secure storage, use of strong passwords, and timely reporting of breaches.

What is sensitive customer data in insurance?

Sensitive customer data in the insurance sector typically includes personal information about individuals that is collected and used for the purpose of providing insurance products and services.

This includes, but is not limited to: –

  • Personally identifiable information: Most commonly known as PII, this includes information such as an individual’s name, address, phone number, family details, etc.
  • Financial information: Insurance companies may collect financial information such as income, credit history, and bank account numbers in order to assess an individual’s risk and determine the cost of insurance coverage, support payment transactions, etc.
  • Health information: Insurance companies also need to collect health information, including medical history and current health conditions, in order to assess an individual’s risk and offer personalized insurance packages. Health information also determines the cost of the insurance coverage, cost and duration of premium to be paid, etc.
  • Policy information: Insurance companies may also collect information about an individual’s insurance policies, including the types of coverage they have, the premiums they pay, and the terms and conditions of their policies. This may include policies sold by other insurers, as well as policies held by family members of the customer. 
 

Why are customers concerned about their personal information?

Business is more personalized than ever in today’s technology-driven era. Transparency is the “New Trust” and the better a business handles its customer’s information security and privacy, the more trust its customers will have. Customers, despite their trust, want to know how their data is handled and stored. Some of the reasons for continuing to be concerned are as follows:

  • Privacy: Customers may be concerned about the insurer sharing or using their personal information without their consent.
  • Security: Customers may be concerned about the security of their personal information, especially if they have previously experienced a data breach.
  • Identity theft: Customers may be concerned about their personal information being used for identity theft, which can result in financial losses and other serious consequences.
  • Discrimination: Customers may also be concerned about their personal information being used to discriminate against them, for example, by denying them coverage or charging them higher premiums based on their personal characteristics.

How can data in New Business be misused?

Personal data can be misused in a variety of ways. Some examples include:

  • Unauthorized sharing of information: Insurance agents or other employees may improperly share an applicant’s personal information with third parties without the applicant’s consent. This can lead to privacy violations and may also result in the applicant being contacted by unscrupulous individuals seeking to sell them products or services.
  • Data breaches: Insurance companies may suffer from data breaches, which can result in personal information being accessed or stolen by unauthorized individuals. This can have serious consequences for the affected individuals, including identity theft and financial losses.
 

Government and industry policies for handling consumer data

There are a number of government and industry policies in place for handling consumer data in the insurance sector. These policies are designed to protect the privacy and security of personal information and to ensure that it is used ethically and transparently.

Some examples of government and industry policies that may apply to the handling of consumer data in the insurance sector include:

  • The General Data Protection Regulation (GDPR)
  • The California Consumer Privacy Act (CCPA)
  • The Health Insurance Portability and Accountability Act (HIPAA)

In addition to these laws, industry organizations such as the National Association of Insurance Commissioners (NAIC) The Insurance Information Institute (III) and The Insurance Regulatory and Development Authority of India have their own guidelines and best practices for handling consumer data in the insurance sector.

Effects of Data abuse on businesses

Data abuse can have serious adverse effects on businesses, including, but not limited to legal consequences and loss of customer trust.

Some serious consequences of data abuse for businesses include:

  • Financial losses: If a business’s data is compromised or used improperly, it may incur direct financial losses as a result. If a business’s customer data is stolen and used for fraudulent purposes, the business may have to pay for credit monitoring services for affected customers, and may also face charges related to the investigation of the data breach.
  • Damage to reputation: Data abuse can also damage a business’s reputation and undermine customer trust. Eventually, if a business is seen as not protecting customer data properly, it may lose customers as a result.
  • Legal consequences: Data abuse can also lead to legal consequences for businesses, including fines and penalties for failing to protect customer data. In some cases, businesses may be sued by customers or other parties for data abuse.
  • Business Closure: The cost of mitigating, handling and course-correcting the business after a data breach can be immense, especially when the data lost is of a huge quantum. Reports suggest that close to 60% of small businesses close down after a data breach incident.

To prevent these negative effects, it is important for businesses to take steps to protect their data, including implementing strong security measures, training employees on data protection best practices, and regularly reviewing and updating their data protection policies.

Data access on a “need to know” basis

The 1st step in setting up ethical data handling policies and processes is to allow data access on a “need to know” basis. Some initial steps include: –

  • Implementing access controls: Access controls allow businesses to restrict access to sensitive data to only those individuals who have a legitimate need to access it. This can be done through the use of user accounts, passwords, and other security measures.
  • Defining data access roles: Businesses can define different data access roles for different employees, depending on their job responsibilities and the type of data they need to access. For example, an insurance agent may need access to customer policy information, but may not need access to confidential medical records.
  • Using data classification systems: Businesses can use data classification systems to categorize data based on its sensitivity and to assign different levels of access to different employees. For example, highly sensitive data such as financial or medical records may only be accessible to a small group of trusted employees.
  • Monitoring data access: Businesses can also use logging and monitoring tools to track who is accessing what data and when. This can help to identify any unauthorized access and ensure that data is being accessed only on a “need to know” basis.
 

Use of technology and tech-enabled solutions to handle customer data

Adopting technology has helped businesses streamline data handling, provide relevant information to underwriters, and grant them greater decision-making authority. Some tech-enabled features that insurance companies use is: –

  • Data management platforms: These platforms allow businesses to store, organize, and analyze data in a centralized location. This can make it easier to access and use data in compliance with governance and regulatory policies, and can also help underwriters make more informed decisions by providing them with a more complete picture of an applicant’s risk profile.
  • Data governance tools: These tools can help businesses manage and enforce their data governance policies, by tracking data access and use, automating data classification and tagging, and enforcing data retention and destruction policies.
  • Risk assessment and modeling tools: These tools can help underwriters assess an applicant’s risk profile by analyzing data from a variety of sources, including credit reports, insurance claims data, and other relevant information. This can provide underwriters with a more accurate assessment of an applicant’s risk, allowing them to make more informed underwriting decisions.
  • Artificial intelligence and machine learning: These technologies can help automate the process of analyzing and interpreting data, freeing up underwriters to focus on more complex tasks.
  • Data masking: This involves replacing sensitive data with fake or “masked” data that can be used for testing or training purposes, while still preserving the overall structure and integrity of the data. This can be useful for tasks like testing software or training machine learning models without exposing sensitive data to humans.
  • Data de-identification: This involves removing or “anonymizing” personal information from data sets, making it impossible to identify individuals based on the data. De-identified data can be used for a variety of purposes, including research, analysis, and reporting.
  • Data encryption: Encrypting data makes it unreadable to anyone without the proper decryption key. This can be used to protect data while it is being transmitted or stored, preventing unauthorized access to sensitive information.
  • Access controls: Implementing access controls can help prevent unauthorized access to sensitive data. For example, using role-based access controls can ensure that only authorized individuals have access to specific data sets, while activity logging and monitoring can help detect and prevent unauthorized access.

An insurer’s reputation is heavily dependent on how it handles customer data. Customers are increasingly aware of the importance of data privacy and security, and they expect their personal data to be treated with care. As such, insurers that handle customer data poorly or suffer data breaches may face negative consequences, including loss of customer trust and damage to their reputation.

On the other hand, insurers that handle customer data well and take steps to protect it can build customer trust and improve their reputation. Technology can play a significant role in this process by helping insurers streamline data collection, improve data handling efficiency, and retain customer trust.

Start typing and press Enter to search