Kurt Salmon partners with financial services firms to develop their data capabilities, enabling firms to identify and capitalize on specific big data opportunities, increase revenues, reduce costs, and efficiently meet ever-changing regulatory compliance demands. By applying a proprietary methodology informed by deep financial industry expertise, we identify what data is available to our clients; determine what—and whom— it will take to access and analyze it; explain how to monetize and leverage big data; and, using our proven human capital assessment, recommend big data analytics team roles, responsibilities and organizational structures. We provide a detailed action plan—a roadmap to the ideal big data target state—in 60 days or less.
The ability to store, analyze and leverage big data has become the linchpin to managing risk, containing costs and innovating competitive advantages. Proactive fraud protection, for example, can be done well only with real-time analytics; effective anti–money laundering compliance now requires linking multiple data types, including fraud detection datasets, with elements such as bank and ATM usage; and all financial big data systems must soon be Volcker Rule compliant. Further, big data analysis can lead to the discovery of formerly hidden areas of competitive advantage and opportunity.
But datasets are often unstructured or so large that they obscure their underlying meaning, and many businesses have discovered that they must vastly improve or augment their employee structures and skill sets to effectively leverage such information. Any big data program must account for both existing and missing resources, technological and human alike, and be flexible enough to adjust and scale to new sources of unstructured data and new regulations.
In trying to address these needs, financial institutions are dealing with issues that include:
- Outdated systems that cannot process and store available data
- Lack of expertise on staff or inability to identify existing expertise and skill sets
- Organizational structures that are not optimized for big data
- Limited time to address expanding demands
Kurt Salmon’s big data framework identifies the data organizations currently have, measures internal talent capabilities, determines what skills employees still need and creates a step-by-step plan for uniting people and big data to meet critical business goals. We present a clear picture of what the organization can accomplish once its resources are strategically aligned toward a comprehensive big data initiative.
Our key differentiators are:
- Focus on human capital—Optimizing human capital is the most important part of any big data endeavor. We have an exclusive partnership with Battalia Winston, an established national firm with 50 years of experience in executive search and a dedicated practice in recruiting financial services big data talent.
- Holistic approach—Our accelerated methodology helps you understand all data present across your enterprise so you can find or create efficiencies in data storing, sharing and analysis.
- Agile and rigorous timeline—With our agile framework, we typically produce an end-to-end big data value proposition within 60 days.
- Participatory nature—Our clients are involved in every step and encouraged to provide feedback.
Kurt Salmon’s clients will know within 60 days how to approach a big data initiative. Our process also identifies the cost and time involved for individual big data business cases, including an assessment of quick wins and priority ranking of longer-term projects.
Financial services firms that centralize their data, optimize their human capital and enable big data discovery efforts across departments will know what skill sets they can leverage and what they must add to evolve, diversify and develop sustainable growth. They will be better able to find hidden opportunities to monetize and increase their revenue streams, reduce risk, improve efficiency and adapt to changing regulations in real time.
Kurt Salmon’s big data methodology can help financial firms address specific concerns, such as setting up a program to create nondisruptive, real-time monitoring of customer transactions that detects fraud before it generates significant financial losses or developing big data systems to track and monitor trades that are also Volcker Rule compliant.
- Big data decision matrix: outlining two or three big data business cases to highlight requirements, ranking, weighted factors and different options in order to determine how to leverage big data
- Human capital and resource plan: including clearly defined roles, responsibilities, hiring and change management transitional plans
- Compliance optimization requirements
- Vision scope document: outlining overall requirements, scope and immediate actions
Using the accelerated big data methodology gives companies a holistic picture of their opportunities, assets and weaknesses so they can approach their big data efforts correctly the first time.