While financial services organizations have spent significant time and money collecting data on products, customers, and transactions, they have put only fractional amounts of that information to work. Now is the time to make big data smart data. In this post, we provide 4 considerations to ready your organization.
Enhance profitability, build new products, minimize exposure to risk, and deepen customer relationships by transforming your bank from a legacy organization into an information-based, data-driven enterprise.
Architected data platforms provide a foundation for automated modeling and forecasting to reduce cycle times and ensure well-managed data inputs.
Beyond our credit-meets-technology expertise, part of what differentiates Flying Phase from our competitors is how we attack clients’ problems. Yes, the results stand on their own, but the way in which we get there – iteratively and with a focus on incremental value – plays a huge role in shaping the end result.
Allowing for loan losses during COVID: Banks prepared for delinquencies during COVID uncertainty, but the expected wave of losses has not come. Will it?
Robust coding practices and streamlining the process and reduces delays and errors in model development and implementation for critical CCAR stress testing execution.
Bringing production quality methods and controls to the quarterly impairment allowance created a fully compliant allowance process that reduced cycle time and resource needs by 80%.
Automation delivers higher accuracy and speed in $60 million in annual incentive payouts to telecommunication field technicians.