White Paper
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 complianceCompliance is used to refer to the adherence to laws, regulations and industry standards within a specific business or financial context. Compliance can involve implementing policies and procedures to ensure… concerns. The white paper describes methods to improve data management in the age of machine learningIs a particular sector within Artificial Intelligence that programs a machine to comb through vast swathes of data and make decisions and insights based on that with very little human… and artificial intelligenceAI is a ground-breaking technology that will change the shape of technology and how humans interact with it and business in general. Encompassing machine learning to make a machine ‘think’…. Its focus is the prepaid business, which has become a new target for fraudFraud is defined as a deliberate and deceptive act carried out with the intent to gain an unfair or unlawful advantage. Fraud is mostly associated with deceit, misrepresentation or concealment…, in part because it lacks the predictability and strict regulation of the credit cardA credit card is a form of payment card that allows a cardholder to make purchases on credit. The card works on the promise that the cardholder will repay the… 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
