Uncertain, fearful, anxious, untrusting -- these are just a few words that can be used to summarize the emotional psyche of today's investor. As the stock market grows increasingly volatile and as corporate accountability issues drive investor blood pressure levels to an all-time high, investors are increasingly looking to their investment managers and advisors as their "guiding lights."
Surely, the shaky stock market has depressed business activity for investment managers and advisors. But to a certain degree, today's market presents a golden opportunity to investment managers and advisors to transform their perceived role from that of "stock pusher" to strategic, trusted counselor. Quite paradoxically, in these uncertain times, investment managers and advisors can "turn the tide" and effectively grow client assets under management, instead of watching them dry up.
Fortunately, today's brokerages are leveraging enterprise applications -- namely customer relationship management (CRM) -- to provide a more comprehensive view of clients, enabling them to offer more valuable wealth management services and increase assets under management, even in these uncertain economic times. But today's CRM technologies feature capabilities that extend far beyond the creation of unified views. They include advanced analytic capabilities for leveraging a brokerage's rich repository of centralized data, including investors' portfolios and financial planning histories.
CRM -- Where We Were
In years past, a unified view of an investor's financial holdings -- also known as the '360 degree' or 'investor-centric' view -- was espoused as the key to complete, personalized investment services and investor relations. For instance, in order for an investment manager to provide sound, personalized financial advice, he/she needs to see and understand the full scope of an investor's assets, no matter what form they are in -- 401K holdings, individual stocks and bonds and even life insurance.
By now, many of us have heard about the virtues of the unified view. Indeed, many brokerage firms have made great strides in integrating investor information across a wide variety of accounts and holdings. But while a unified view can provide a complete view of an investor's financial assets, what it cannot do is deliver an intimate level of investor knowledge, which ultimately helps to transform "stock pushers" into true "relationship managers." Some would argue that without this intimate level of knowledge, a view that is supposedly "360 degrees" is actually only "180 degrees." In actual fact, the unified view is only one of the tools that a trusted investment advisor needs.
Analytics are the key to extracting an intimate level of investor knowledge that leads to a true "360 degree" view. As investor confidence remains shaky at best, unified views combined with analytics are likely to emerge as a key factor in the battle to increase assets under management and share of wealth. When seamlessly integrated into financial planning services, analytics enable brokerage firms to understand, anticipate and influence investor behavior.
How Analytics Works
When advanced analytic capabilities -- or business intelligence applications targeted at investor relationships -- are applied to extremely rich, centralized stores of historical, account holdings, risk tolerances and third-party demographic data, the usefulness of the mined data increases exponentially. With the right tools and a little intuition, investment managers and advisors can increase assets under management -- and fees for managing those assets -- by leveraging analyzed data to anticipate investors' needs and influence their behavior.
Predictive analytics leverage a brokerage firm's wealth of historical investor information to generate models targeting the likelihood of future behavior in a given segment. They help investment managers and advisors understand their investors, anticipate investors' needs and influence investor decision making through well-aligned programs. Opportunities to increase assets under management are often rare and fleeting, and for this reason, investment managers and advisors rely on instant desktop access to actionable, analyzed data.
Three Steps To Predicting Investor Behavior
Investor behavior analytics use the predictive analytics process to identify investor segments, predict investor behavior and ultimately help make investor interactions more effective and profitable for brokerage firms. Predicting investor behavior involves three steps:
--Profiling: Brokerage firms first build a profile of information about investors who have previously exhibited a targeted behavior. Profiling requires rich investor data, including enterprise-wide transactional and behavioral data such as financial holdings information and risk tolerance. Other data sources include third-party demographics, such as customer segmentation by zip code. Profiling also helps to identify potential extended relationships -- for instance, spouses, children and businesses -- which can be particularly valuable to increasing assets under management.
--Modeling: By using data mining on the profile information, analytics can uncover the most relevant characteristics of the investor segment being analyzed.
--Scoring: Brokerage firms use predictive analytics to score investors by comparing them to the model. Those most closely matching the characteristics included in the model are most likely to exhibit the targeted behavior. A brokerage firm can rate its investors numerically to indicate how closely they match the model, and tailor their interactions (such as marketing campaigns) accordingly.
Analytics in Action
Consider the example of an investor who consults his investment manager with the question of whether or not he should add more aggressive stocks to his portfolio. The investment manager is charged with giving sound financial advice in a way that will ultimately increase assets under management, fees for managing those assets and build longer term goodwill and confidence on the part of the investor. Analytics can determine, from the combination of internal data, customer risk profile and third party data, the profile of a resident in that particular zip code -- in this instance, affluent, professional, suburban and middle-aged.
Next, by using data mining on the profile information, analytics can perform modeling, thus uncovering the most relevant characteristics of the investor segment being analyzed. For example, modeling may predict common attributes of investors fitting this profile -- in this instance, that they tend to be into "active sports" such as golf and tennis and that home ownership is over 90 percent.
Predictive analytics is then applied to score the investor at hand by comparing him to the model. In this instance, let's assume that given historical data, the customer closely matches the characteristics included in the model. At this point, the investment manager knows that this investor is a prime target for moderately aggressive stocks (investors in their 40s who like golf and tennis typically balance their portfolios between aggressive and conservative stocks). At the same time, the investment manager leverages the opportunity to increase assets under management even further -- by proactively offering and selling a home equity line of credit.
By modeling and predicting investor behavior, brokerage firms are beginning to use the wealth of information gathered by their systems to tap the potential of extremely rich pools of historical investor data. The brokerage firms that leverage this data by skillfully applying analytics are well-poised to increase assets under management and share of investors' wealth. In addition, they will be better able to transition their role from that of "stock pusher" to strategic relationship manager and long-term partner.
As investors and brokerage firms alike continue to face rocky times, investment managers and advisors need to maximize their interactions with investors and lay the groundwork for an ongoing and fruitful future relationship. Both brokerage firms and the investors they serve stand to benefit.