Data is one of the most valuable assets financial institutions have in today’s market. But as more data is collected and consumed, we must all grapple with new concerns about how to do so ethically and responsibly. A strong data ethics strategy is now an essential part of any successful business strategy, and organizations need to make it a priority.
Financial institutions (and businesses in other industries) can – and must – re-frame their data approaches to make data ethics the foundational element that underpins all data and AI operations. When that happens, they unlock the potential to position themselves as leaders in a space where regulations and consumer expectations are rapidly evolving.
At Deloitte, we’re hearing more about this from clients who want to seize this exciting opportunity to implement data controls, policies, and procedures that minimize risk and prepare their organizations for future regulatory changes. That’s why we’ve developed a roadmap that financial institutions and other organizations alike can take to actionably realize this potential by developing a more robust data ethics strategy. Below are a few key learnings.
Data ethics is key to reducing reputational risk and increasing efficiencies in scaling
Recent data shows consumers are growing more concerned with how organizations are using their data. In a world of unlimited choice, decision-makers must ask themselves “why should individuals choose our organization, over all the others, to give their data to?”
In this sense, data ethics is not just matter of compliance, but an opportunity for financial institutions to enhance their public reputation with consumers. It’s an essential risk mitigation tool your organization can leverage to implement the best controls, policies, and procedures tailored to your company’s specific needs, ensuring regulatory compliance, and minimizing the likelihood of impact to reputation.
Leadership in data ethics will also enable your organization to scale operations more effectively, efficiently, and securely by decreasing the amount it takes a new customer to realize value for your product. Viewed from a wider lens, data ethics is not about hindering innovation but safeguarding it.
Where to start: Leadership and accountability matter
The biggest challenge facing organizations that want to implement a data ethics strategy is moving from intent to implementation. How can organizations make these principles a reality?
It starts with leadership. Adopting a strong data ethics framework is about doing more than just having a member of the organization’s legal or regulatory team provide input on basic regulatory compliance. A robust data ethics strategy should have accountability and leadership with direct oversight from the department of the Chief Data Officer (CDO), but it is also essential that this accountability does not stop at the CDO’s doorstep.
The CDO can ensure that data ethics is not siloed into one department but embedded into every part of the organization. A good place to begin is assessing how data ethics currently fits into your organization’s operations at every stage of the data lifecycle. Deloitte’s Trustworthy AI Impact Tool offers a framework for financial institutions that want to adopt a stronger data ethics system.
Focusing on leadership that is accountable for implementing data ethics across your entire organization will help your organization avoid risk from regulatory bodies or face potential reputational damage if any data misuse practices become public.
How data ethics mitigates risk
Risk mitigation is at the centre of any strong data ethics framework. Regulatory bodies worldwide are increasing pressure on how they respond to organizations’ ethical data infractions, and rules and regulations are changing on a regular basis.
However, data ethics must be about more than meeting the regulatory floor. When organizations prioritize data ethics, it can set a new bar in the industry, and help a company position itself as an innovator with which competitors must catch up to.
For example, a global tier one bank recently approached Deloitte to help it operationalize the roll out of its data ethics program. Using the Impact Assessment Tool, Deloitte first assessed the current state of data ethics at the financial institution and identified key actions to be taken across each stage of its data lifecycle, based on the organization’s specific risk profile.
This assessment stage is a crucial beginning step for any company looking to implement data ethics into its operations. Once you have assessed an organization’s risk profile from its AI operations, you can begin to understand where there is room to improve, not only to avoid potential pitfalls but also to uncover opportunities to increase operational efficiency.
In this bank’s specific case, Deloitte implemented a robust data ethics framework tailored to the financial institution’s key needs. It proactively identified data ethics risks across the financial institution’s operations. It also ensured effective measurement and monitoring of the data ethics processes and principles that aligned with the global nature of the bank – key for any strong data ethics framework to remain effective.
Data ethics is an ongoing journey
As illustrated above, a tailored and robust data ethics framework can be implemented across every stage of the organization’s data lifecycle, but it is important to view data ethics as a revolving door that must be continually walked through.
AI systems are in a constant state of flux as patterns in the data are tracked and responded to accordingly. To ensure potential risks from this ongoing process are mitigated, there needs to be constant monitoring to catch and address any new changes to the data that arise from these constantly evolving AI operations.
Data is a powerful tool financial institutions and other businesses rely on in today’s digital economy. As this reliance on AI operations only continues to grow, it is imperative every department of an organization’s executive branch make data ethics a priority.
For organizations who want help in implementing this kind of framework, Deloitte’s Trustworthy AI Impact Assessment Tool is a great place to start and can be embedded into an organization’s AI development lifecycle to identify, mitigate, and manage relevant regulatory concerns, and then create a robust made-to-measure data ethics system.
Learn more about how to implement a strong data ethics framework
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