Technology
The Data Divide
Data ethics and data governance need to be part of every employee’s onboarding, highlighting their responsibility along the supply chain.
Organizations need to view data as a supply chain, examine exposures and adopt risk mitigation efforts at every stage, including collection, manipulation and consumption.
Pat Saporito
The digital world is built on data-enabling analytics. Data abounds, but with great data wealth comes great data responsibility, especially in the insurance and financial services industries where data is one of the most valuable corporate assets.
We are stewards of the data we own and use. Organizations must consider the ethics of data collection, manipulation and use. We have the duty to protect it and to use it fairly as well as transparently. Given how rapidly and completely we are living in a data-driven world, data ethics should be taught in educational institutions and made part of every business, IT and data science program in all organizations, including our professional associations.
Data security and privacy guidelines are part of the baseline. The General Data Protection Regulation (GDPR) is a good standard to adhere to not only in Europe but to adopt in other countries as well. However, data ethics go beyond merely protecting the data. It also includes the algorithms that we create potential bias in and how we apply them.
Data ethics should be part of corporate security policies, but the mandate goes beyond the chief information security officer or chief information officer. It needs to go further than data security, starting with data governance. Organizations need to view data as a supply chain, examine exposures and adopt risk mitigation efforts at every stage, including collection, manipulation and consumption. This should be a board-level initiative, given the corporate risk exposure and enterprise scope.
A data supply chain includes data acquisition and storage; data aggregation and analysis; and applied usage, sharing and disposal. Managing this supply chain will require a strategy as well as best practices to operationalize it. People, processes and technologies are all required. Data ethics policies and cyber security policies must be continuously reviewed and adhered to, and data governance must be given more visibility and importance. Data ethics and data governance need to be part of every employee's onboarding, highlighting their responsibility along the supply chain. Technologies like block chain can help address data auditability and immutability.
Some practices are already in place but are stove piped across different areas within the organization. Others, such as data governance, lack widespread awareness and resourcing. They need to become part of an organization's enterprise data analytics strategy and under the purview of the chief data officer or analytics officer. Successful organizations can improve their data ethics by reviewing their data strategy and their current processes, identifying gaps, defining initiatives to address gaps and building a prioritized risk-based road map with assigned resources.
As industries become more digital and part of broader ecosystems, and technologies like artificial intelligence become more pervasive, data ethics will grow in importance. Organizations should build data ethics programs to simultaneously manage risk and build trust. Failure to do so will impact their reputation, brand, and customer and partner trust and put them at a true competitive disadvantage.
Best’s Review columnist Pat Saporito is an analytics thought leader and author of Applied Insurance Analytics: A Framework for Driving More Value from Data Assets, Technologies and Tools. She can be reached at pat.saporito@gmail.com.
