It’s vital to verify data across sources to create a comprehensive 360-degree view of specific businesses.
Browsing: Big data
Four ways for banks to integrate emerging financial crimes technology.
Consolidation over the last several decades has led to disparate sources of raw data locked up in legacy systems and proprietary formats.
The siloed and slow, often manual, processes of the past are giving way to new efficiencies of automation and cloud-based solutions.
AI, machine learning and alternative data are helping banks and nonbanks alike make faster decisions and expand access to credit. While fair lending concerns about “black boxes” have impeded wider adoption of these technologies, the regulatory environment is shifting.
Two challenges for today’s anti-money laundering professionals: focusing on high-value functions and eliminating false positives that consume unnecessary resources. Nicholas Piccininni, who leads a 1,500-person financial crimes risk management team at Wells Fargo, explains how Wells puts technology to use to tackle these challenges.
The key question that will determine who wins and who loses in this digital age of banking: “Who controls the customer relationship?”
Understanding the past is important but extracting value from risk reports and applying the results is critical to the organization’s future. Risk reporting has far more to offer.
In a statement submitted for the record in tomorrow’s House Financial Services Committee fintech task force hearing, ABA highlighted the importance of protecting consumers when they choose to share their financial data with third parties.