Financial Data Management in the Age of Maximum Volume and Velocity
Growth-related challenges are what attracted DataSeers to the financial services space.
The core of any data solution lies in financial data management. What is needed is a solution that will integrate and coordinate compliance, reconciliation, fraud monitoring, and visualization. This research brief provides a senior executive level look at the problems presented by the current state of financial data management in the face of compliance concerns. The white paper describes methods to improve data management in the age of machine learning and artificial intelligence. Its focus is the prepaid business, which has become a new target for fraud, in part because it lacks the predictability and strict regulation of the credit card business.
“The prepaid industry has seen a slew of bad actors. The fraudsters are not only smart, but they have more advanced technology than some of the processors. Hence, rule-based fraud or compliance monitoring is a thing of the past. The only way banks can keep up with fraudsters and make a meaningful effort against it is by using AI and ML. Machine learning works on a simple “garbage in, garbage out” basis, so the most important piece of any ML-based algorithm is to have clean and actionable data. Our platform is different in this way because while most platforms struggle getting clean data, this is what we do ahead of time.”
Adwait Joshi, Chief Seer at DataSeers