Big Data is directly tied to the rising importance of information management as a function within financial institutions. Regulatory, client and internal drivers have forced most firms to reevaluate the core reference data sets on which they base their trading, risk management and operational decisions. Accessing, sorting, compiling and leveraging that information is increasingly important in fast-paced markets and changing regulatory landscapes.
This whitepaper describes the business and regulatory drivers that are forcing financial services organizations to implement strategic, enterprise-wide data initiatives. It examines why the legacy approaches to data management that have resulted in the current fragmented and loosely governed data architectures are not appropriate for these initiatives, and describes a new approach – one that combines organizational structure, a common lingua franca, and a technology architecture based on semantic technology, that combines a top down organizational approach with a bottom up implementation methodology to generate near-term ROI while incrementally enabling a strategic, comprehensive enterprise-wide data initiative.
While adhering to regulatory requirements, Anzo provides a flexible infrastructure that seamlessly connects all your customer information. Armed with this data, you’ll be ready to productively and legitimately meet your customer’s needs.
The needs of regulators, executives, and compliance officers are often unanticipated. Anzo will prepare you with the tools necessary to quickly automate, systematize, and integrate existing compliance data and processes for updated regulations.
Anzo can help compliance officers investigate compliance violations by linking and aggregating account activities, web logs, email and phone archives, IM communications, and other sources.
Anzo is the only end-to-end, semantic knowledge, graph-based solution for automating the delivery of critical data to business users, BI tools, and other systems. It provides a breakthrough approach to making data instantly accessible.
Most large financial organizations are wrestling with fundamental data management challenges. Traditional technologies are struggling to meet these challenges and they demand a new approach. Forward thinking organizations are deploying semantic Knowledge Graphs as a powerful option.
In this blogpost, we discuss Cambridge Semantics' FIBO project to harmonize State Street's Interest Rate Swap data with Dun & Bradstreet's entity hierarchy data.
In this blogpost, we discuss how leveraging semantic technology to create a data ecosystem can allow financial institutions to satisfy regulatory reporting requirements, including BCBS 239.