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Model governance can help address these problems. This overall process has become increasingly important in financial services and other industries as the use of models and broader analytics continues to expand rapidly. It helps organizations control access, implement policies, and provide oversight of their model systems. As models based on AI are seeing broader use, the checks and balances governance provides is imperative. Model governance puts guardrails around generative AI use by monitoring the various models used by AI systems. It provides a means for auditing and testing to avoid inaccuracy and bias, and enforce the standardization and transparency that regulators (and sound model management practitioners) look for. To do this, companies need a platform that enables complete end-to-end management, monitoring, facilitation, and governance of their generative AI models.
Building responsible frameworks to guide responsible AI use can be daunting. Turning to a trusted resource with experience in this emerging tech can be invaluable when setting priorities and implementing generative AI strategies. Building in trust and ethics from the start—and considering tech-enabled solutions—can help companies execute on their plans. Model Edge, a PwC product offers the transparency and governance needed to use generative AI more responsibly and with less risk. Model Edge combines industry-leading practices with PwC’s proven frameworks and methodologies to establish next-generation AI model governance and help organizations consider ethics and implications at the onset.
With its ongoing monitoring frameworks, Model Edge can continuously monitor models’ performance against industry standards in order to reveal biases that models may be prone to. Using these controls built directly into Model Edge, organizations can gain confidence in their modeling programs.
By visualizing the model’s operating processes, Model Edge makes the models more interpretable. And exhaustive documentation features help organizations demonstrate their use of AI/ML programs with confidence.
Model Edge’s advanced reporting and document automation capabilities further mean that key decisions are documented and that updates are seamlessly captured.
In Model Edge, PwC has collaborated with financial institutions to help safeguard their work and data; the framework was recently named a leader in the IDC MarketScape for Worldwide Responsible Artificial Intelligence for Integrated Financial Crime Management Platforms. Model Edge has already supported large banks and other financial institutions in creating a sustainable program that helps them grow and evolve.
Model governance and validation need to be nimble and sustainable; financial institutions shouldn’t have to move to new tools every few years. They need a solution that can grow with them and that can keep them ahead of possible problems.
“Fighting the sophistication of financial crime and fraud with responsible AI is table stakes for risk managers in today’s environment,” says Agarwal. “The ‘responsible’ piece is key. Mitigating AI risks requires transparency, accountability, bias mitigation, privacy, and data protection. You need to inspire confidence with customers and regulators that when it comes to something like lending decisions that they’ll be handled with fairness. Now more than ever, businesses should evaluate their practices around responsible AI to get ahead of future regulations. That means layering in human oversight and control into your processes.”
Building and maintaining trust with stakeholders, from board members and customers to regulators, is key. Financial institutions and other businesses need to be ready to demonstrate ongoing governance over data and performance and be responsive to emerging issues. It’s beyond compliance with regulation—building trust is also good for business and brands.
PwC’s Responsible AI is built into Model Edge to help guide organizations through ethical and fairness considerations that foster responsible and unbiased use of AI-based decisions.
Reaping the benefits
As organizations consider the use of generative AI, they should take precautionary steps now, implementing model governance to put the proper guardrails in place to mitigate the risks of which we’re already aware.
Using generative AI successfully involves building models more effectively, considering unintended consequences, appreciating potential risks, and identifying where model performance may fall short. Through responsible AI use and rigorous model governance, companies can be better prepared to reap the benefits of this exciting new technology while responsibly limiting their risk.
This story was produced by WIRED Brand Lab for PwC.
