Trustworthy AI in banking
Explain, analyze, and monitor ML models.
Improve quality. Build trust. Scale up.
Scaling AI in banking is hard
Artificial Intelligence and Machine Learning (AI/ML) are transforming banking, and is now a key battleground between incumbents and challengers. However, in most banks, uptake remains slow and impact limited.
One key barrier – for business leaders, control functions, regulators and customers – is the quality and trustworthiness of AI/ML models, particularly where the stakes are high.
TruEra’s AI Quality solutions help explain, analyze and monitor AI/ML models – to ensure quality, build trust and enable impact at scale.
TruEra helps banks capture real business value from AI and ML at scale
Use cases in banking
- Help customers understand why their loan application was rejected
- Assess if the credit model is unfairly discriminating against particular groups
Financial Crime Compliance
- Convince regulators that the system to automate investigations is reliable
- Help investigators understand why the system has flagged a particular transaction as suspicious
- Monitor the performance and stability of a fraud-detection algorithm over time
- Explain how customers can reduce the risk of their transactions getting blocked erroneously
- Assess if the marketing engine is mis-selling products to customers (e.g. loan to a vulnerable customer)
- Explain to a Relationship Manager why they are being advised to promote a particular product
- Demonstrate that a trading algorithm does not pose a systemic market risk
- Get buy-in for a new (ML) pricing model by providing meaningful comparison with existing (non-ML) model
- Provide early warning when data drift is likely to impact the accuracy of models used to automate operational processes
- Assess the reliability of model to determine the appropriate level of human supervision
Why use TruEra for banking?
Find out what you can do with TruEra
Get in touch with one of our experts