How entity verification shapes AI deployment in risk management

Moody’s has unveiled findings in their recent study, indicating that Entity Verification is crucial for improving AI accuracy in risk and compliance sectors.

As the EU’s AI Act is set to be enforced from August 1, the study emphasises the importance of integrating AI tools with existing regulatory measures, including anti-money laundering and anti-fraud programmes, to promote ethical usage and enhance operational efficiencies.

The study reveals that over a quarter of respondents (27%) consider Entity Verification essential to enhance AI’s accuracy in risk-related functions, with a further 50% acknowledging its value in boosting accuracy levels. Such verification processes are vital in preventing compliance issues, ensuring that AI systems are equipped with accurate, real-time data to avoid incorrect or biased decisions.

With the rising adoption of AI in risk and compliance, Moody’s reports an increase in active AI use among organisations surveyed, up 2% from last year to 11%. Additionally, 29% of respondents are currently experimenting with AI applications, marking an 8% rise from previous findings. The acceptance of Large Language Models (LLMs) has also grown, with active encouragement for their use increasing to 17%, up from 8% in 2023, while acceptance rates have risen to 27%, up by 7%.

Keith Berry, General Manager, Compliance and Third-party Risk Management Solutions at Moody’s, highlighted the strategic importance of Entity Verification. “Entity Verification is emerging as the cornerstone for successful AI deployment in risk and compliance. Highly accurate and actionable data are needed to train systems so they can be trusted and ensure fairness while helping compliance professionals understand who they are doing business with,” Berry stated.

He further added, “The EU’s AI Act is also driving a major imperative for accuracy in AI’s use across a variety of different compliance functions. Organisations that have effective Entity Verification in place may find the same highly accurate data can be used to help adhere with this regulation.”

As AI continues to embed itself within the regulatory and risk management frameworks, the emphasis on robust data verification processes will only become more pronounced, ensuring that AI technologies are leveraged in a manner that is both effective and compliant with evolving regulatory standards.

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