The digital transformation of financial services has produced never-before-seen volumes of data growing at an unprecedented rate. Along with bringing great potential, the openness and accessibility of the new landscape increase challenges around fraud detection, risk management, customer retention, and more. These challenges compound the strain of fulfilling ever-changing regulatory requirements.
SQream helps financial institutions overcome big data challenges, so they can transform their massive data stores from a burden to a business driver by delivering critical insights faster. SQream propels data-driven systems to meet new and emerging organizational demands, compliance requirements, and governance regulations.
Dig deeper into historical data to build more accurate models of customer behavior, optimize pricing for financial products, and offer the right products to the right clients.
By combining siloed data and accelerating data preparation and analysis, SQream significantly reduces the time for risk management and regulatory compliance.
Minimize losses from fraudulent activities and claims by feeding AI/ML models much larger datasets, for more accurate and effective predictions.
“Combine the query performance of SQream on large datasets, and the vast scale that it can support on limited hardware, and SQream is certainly a candidate worth considering.”
GPU-Accelerated Databases: Addressing FRTB and Other Performance-at-Scale Challenges in Financial Services, Citihub
“We are always looking for new and better ways to analyze our huge data stores. SQream DB allows our Data Science team to generate the insights we need with a lean and performant addition to our existing Hadoop system.”
Multinational credit card and payment services provider