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October 18, 2013 at 11:01 AM
Purchasing a prospect list or subscribing to some lead generation service is one of the more mundane activities of financial advisors seeking to build their business.
But that unremarkable activity flies in the face of a powerful emerging new trend across the economy — the rise of “big data” — whose very essence is analyzing and understanding the data assets you already own.
That is one of the findings of a new study of big data based specifically on financial professionals. The global survey, conducted jointly by the American Institute of CPAs (AICPA) and the Chartered Institute of Management Accountants (CIMA), might have been inspired by the needs of the accounting profession, but its lessons should apply equally to other financial professionals.
Respondents included more than 2000 CFOs and other finance professionals from more than 80 countries, and the feedback included interviews with senior executives.
One such interview was with Matthew Keylock, a top executive with dunnhumby, a data analytics company that helps companies better understand their customers.
Keylock made the key point that “your own data is the place to start,” adding that “buying third-party data may be fine for prospecting activity, and can add color to your own customer records, but it is not the foundation you want to build on.”
By sifting through your own data assets, financial professionals can, for example, “identify and address declining client accounts, but also…reward desirable behaviors,” Keylock is quoted as saying.
To financial professionals who may be intimidated by the notion of big data, Keylock counsels a phased approach: “A massive data project with the hope of some future value is a high-risk undertaking.”
But financial professionals ignore at their peril the insights they can glean from their data. That is because the benefits of that data, according to the surveyed financial professionals, include opportunities to identify cost savings and efficiencies; the ability to track your performance; forecasting capabilities; risk monitoring; and increased revenues — through factors such as better customer segmentation.
