Big data, digital transformation, and business intelligence are all phrases that have become increasingly popular over the last few years. Financial institutions have embraced this new trend and have adapted business models to integrate data analytics into daily operations.
The benefits of leveraging the massive amounts of data created and stored by financial institutions translates into tangible benefits. By meticulously mining data, these organizations have identified new opportunities for cross-selling key products and increasing share of wallet. An additional offshoot is an increasingly more granular understanding of customer segments, which creates triggers for decision-making, planning and the development of predictive analytics.
As financial institutions start to reap the benefits of data analytics, it has become increasingly clear that these gains can be multiplied if business intelligence practices are implemented in different areas of the organization, including wealth management.
The big question is why should investment advisors care about data analytics?
Advisors are experiencing pressure from various directions, increasing competition from automated solutions, clients who demand more competitive pricing, institutions who are consistently looking for better performance and strategies to mitigate risk. Despite the complexity and the risk associated to an advisor’s business, the investment industry continues to evaluate the success (or failure) of advisors using two simple metrics, assets under management (AUM) and revenue. These two numbers have traditionally provided the basis for an advisor to build a business strategy and identify opportunities for growth.
Does this make sense?
If these same metrics were applied to retailer, would a business owner in any other industry, have enough business management tools, information and analysis to make informed decisions and track business growth?
For example, a hardware store that would use the same metrics as an investment advisor, would simply track total sales and inventory value. There is no measure of costs, margin, profitability, salary costs, fixed costs, inventory turn, average transaction cost, cash flow, pricing, seasonality, client demographics, product marketing, etc.
Clearly, retailers need to capture and manage a complex set of data points in order to maximize business and revenue growth, control costs and generate profits. All these metrics provide insight into different operational areas and provide a business owner with a comprehensive view of performance.
Advisors need to move beyond metrics such as AUM and revenue as a basis for decision-making. Innovations in technology and data management now allow wealth advisors access to a wide range of data sources that can be combined to produce a consistent integrated view of their total business. Advisors can see how their business is performing, what factors drive growth, which products are the most efficient, which clients are the most profitable, how the business is evolving, where the opportunities/threats exist and how the business compares with peers/leaders in the firm. This is a radical change for wealth management – advisors are managing a complex business with significant risk, they need the business management tools to manage and grow that business.
In a technology-driven world, advisors as well as financial institutions continue to adapt to the various factors that are forcing their business to change. Business intelligence is one of these factors that may actually propel an advisor’s business forward by providing the knowledge to be more competitive.