Trends Poised to Disrupt the Wealth Management Industry

wealth management


By Alex Koles/ Evolve Capital Partners

Competition in the wealth management industry is increasing. Looming on the horizon is a significant evolution in how business is conducted. Big data and advanced analytics technologies are key elements driving transformation in operations, risk, and compliance. Incumbents are using advanced analytics to garner insight from historical data, forecast behavior patterns, and predict outcomes and emerging trends.

According to Boston Consulting Group, approximately 75% of wealth managers are planning to increase their use of big data and smart analytics. Asset managers, investment firms, and securities exchanges are aggressively acquiring or partnering with specialized front-end analytics businesses who have critical internally-developed front-end analytics capabilities.

Wealth management firms and asset managers sit up and take notice

Analytics capabilities are creating better opportunities for wealth managers seeking alpha in areas like marketing and problem-solving. Even wealth managers not seeking alpha can use analytics to better match their services and recommendations to their clients’ needs. Man Group PLC, an investment management firm, is using multiple alternative data sources such as satellite imagery, social media sentiment, consumer transactions, geolocation, online reviews, and web-crawled data to generate alpha.

Several leading wealth management firms are now investing heavily in building big data and advanced analytics capabilities. These descriptive and predictive technologies allow firms to assess existing or potential clients’ propensity to purchase various products and services, as well as understand their investment style and risk tolerance. Nearly all core management processes—from prospecting, sales, advice, and portfolio construction, to risk management and supervision—can be made significantly more efficient and effective.

Unconscious bias often affects trading and investing decisions. By using advanced analytics, researchers have been able to identify and measure the role played by bias in suboptimal trading decisions. Such discoveries have created the basis for effective countermeasures and debiasing methods that can result in significant performance improvement for asset managers.

Analytics platforms improve data governance, compliance, and asset allocation

A PwC report found that 90% of the asset and wealth managers they surveyed considered data analytics to be an “important” or “very important” trend that will impact their ability to compete. Data governance and compliance activities are central to wealth management operations, and  wealth managers have identified a need to improve the quality and breadth of data captured in order to provide superior service to clients.

Wealth managers are also utilizing data analytics for the automation of asset allocation. Machine learning and usage of predictive analytics with accurate data help wealth managers develop better insights and tailored recommendations. Today, wealth managers are using technologies such as natural language processing and client sentiment analysis to understand client risk tolerance better and make appropriate asset allocation and product recommendations based on that knowledge.

A technology-focused client/wealth manager relationship offers valuable data

Digital and mobile channels have become ubiquitous in financial services. Consequently, wealth managers have been forced to change their business models and invest in technology. Clients are increasingly using digital channels to monitor their portfolios in real time and communicate with their wealth managers. While the removal of a human element may seem odd, these digital tools offer a proliferation of data for wealth managers to use. Future success in wealth management will revolve around strategies that harness the potential of these large datasets. By using analytics to analyze customer channel and product preferences, wealth managers will be able to better target products and services and generate higher returns from clients.

Client conversations, meeting notes and CRM data are valuable sources of information that have been used in industry-leading predictive analytics use cases. They can address client attrition, next best action, or even alert a wealth management firm to an advisor defection. Unstructured data from client meeting notes and email correspondence from a CRM can undergo text analysis and client sentiment analysis to help wealth managers make better-informed business decisions and product recommendations to clients.

Recent M&A deals, key partnerships, and company initiatives

Deloitte expects 2018 to be the year that records the highest average M&A deal value for the investment management sector. The exponential rise in innovative and alternative data and increasing processing power have been instrumental in convincing wealth managers to invest in innovative computer models and technologies such as artificial intelligence and machine learning algorithms.

  • European wealth managers are strategically investing in technologies such as artificial intelligence and behavioral analysis to develop internal data analytics teams that drive fund performance. Whether it is Man Group investing in data and technology, Schroders expanding its Data Insights team or Jupiter analyzing the behavioral biases of its fund managers, they all seek to give their fund managers an informational advantage over peers.
  • IBM Wealth Management Solutions is helping financial firms leverage cognitive computing to improve client service, retention, and profitability. IBM Watson Client Insight for wealth management helps firms understand client behaviors and provides a data-driven approach to personalized financial advice.
  • In May 2017, UBS partnered with BlackRock Solutions to provide UBS Financial Advisors and Home Office professionals with BlackRock’s Aladdin Risk for Wealth Management platform. This partnership will allow UBS to analyze portfolios with the same sophisticated risk and return analytics that BlackRock Solutions provides to its institutional clients.
  • In January 2018, Interactive Brokers, an online trading platform, integrated with robo-advisor platform Emotomy. Emotomy’s platform helps advisors and investors streamline onboarding and transforms their investment decision-making, trading, reporting, and communications. Advisors can optimize their operations and focus on serving their clients with this platform.
  • In 2017, Nasdaq Inc. acquired Sybenetix, a leading surveillance provider that combines behavioral analytics and cognitive computing with financial markets expertise. Sybenetix also provides institutional-quality risk management tools.
  • Addepar, a leading provider of portfolio management and client reporting software to wealth management and asset management firms, recently raised $140 million in a Series D financing round co-led by Valor Equity Partners, 8VC, and QuantRes founder Harald Pike.

Wealth management has many traditional players who would benefit from embracing technological opportunities that will keep them in the game. Adopting a technology-focused strategy and investing in big data and analytics will help address changing client needs and enhance existing client relationships. Whatever the cultural and organizational differences, it is inevitable that tradition and technology will work together to improve wealth management.


Alexander Koles is the CEO / Founder / Managing Director of Evolve Capital Partners, a specialized investment bank focused on businesses that operate at the intersection of financial services and technology (FinTech). Koles has 14+ years of extensive advisory experience with private and public FinTech companies and global corporations.