In today’s data-driven environment, many banks and financial organizations struggle to successfully manage their data – too often, leaving valuable insights and unrealized opportunities on the cutting room floor. However, it does not have to be this way. AI is rapidly changing the world around us, and this change extends to the way that we do business. Banking is an industry that is well-positioned to benefit from this AI-backed revolution.
From data quality management to anti-money laundering, the use cases for AI and machine-learning based solution in banking (and finance) are far-reaching and powerful. Topics highlighted in this white paper include:
- A step-by-step analysis of challenges in the data management pipeline (with machine learning-based solutions)
- A look at how process mining can help companies obtain transparency into their workflows and improve operational efficiency
- How data mining and machine learning can provide insights on everything from consumer buying behavior to default rates for credit applicants
- Anti-money laundering applications for AI and natural language processing (NLP), which can improve predictive fraud analysis capabilities