[Guide] Responsible AI: 5 Principles for Fighting Fraud for Financial Institutions

Prioritize Responsible AI principles in your fight against fraud.

Here are the 5 key principles:

  • Ensuring transparency
  • Mitigating bias by nature
  • Providing explainability
  • Delivering high confidence results
  • Safety and privacy to all users

Learn the 5 Principles of Responsible AI

Responsible AI principles enable enterprises to rethink risk management, and build out a fraud and risk management strategy so that AI behaves as expected and aligns with corporate and ethical values. The result? Robust fraud prevention, non-discriminatory decision-making, and reduced risk of reputational or regulatory damage. With DataVisor’s multilayered approach to fraud prevention, you can prioritize Responsible AI principles in a scalable, efficient manner, while building out a high-performing fraud and risk management program that protects your customers and your brand.

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About DataVisor

DataVisor is the leading fraud and risk management platform powered by transformational AI technology. Using proprietary machine learning algorithms, DataVisor restores trust in digital commerce by enabling organizations to proactively detect and act on fast-evolving fraud patterns, and prevent future attacks before they happen. Combining advanced analytics and an intelligence network of more than 4B global user accounts, DataVisor protects against financial losses and reputational damage across a variety of industries, including financial services, insurance, marketplaces, ecommerce, and internet platforms.