Understand the difference between machine learning and the tools of advanced AI
In the competitive financial industry, organizations are monitoring for compliance, fraud, debt default and money laundering while still providing excellent customer experience. Many banks have implemented artificial intelligence (AI) to help meet these rigorous demands, but unfortunately are caught in the misperception that machine learning is always AI.
Technology is becoming more sophisticated and commercially viable by the day, evolving to be capable of far more than standard data mining. Institutions need access to a wide array of highly-advanced learning tools including not just deep learning, but also actual AI systems with unsupervised, real-time updates.
The AI Gap Study: Perception Versus Reality in Payments and Banking Services draws its data from an extensive survey that investigated how FIs leverage a wide variety of supervised and unsupervised learning systems to optimize various business operations, including payments, cash flow management, regulatory and credit risk, and financial fraud. We interviewed 200 senior executives at commercial banks, community banks and credit unions, whose assets were valued anywhere from $1 billion to more than $100 billion.
By downloading this white paper, you will:
- Learn how banks optimize their operations with learning systems.
- Learn the benefits and limitations of learning solutions.
- Understand how Brighterion’s Smart Agents technology takes machine learning to true AI.
- Learn how unsupervised learning can drive revenue, decrease false positives, and substantially reduce manual labour.
It’s time to access the next-generation AI. Download the white paper by filling out the form.