Insight Engines in Wealth: How to Build Tomorrow’s Opportunities Today
McKinsey feels pessimistic. In their recent report, On the cusp of change: North American wealth management in 2030, McKinsey forecast the future of wealth management.
It’s a useful, thoughtful report. But you don’t have to wait until 2030. Most of the opportunities they sketch can be built today, with an insight engine.
Unsurprisingly, McKinsey provides a useful framework to think about the future of wealth management. They ask three big questions:
- What will happen to advice?
- What will happen to advisors?
- What will wealth management firms do?
Insight engines — available today — can help provide answers to several of these questions. For context, I will explain insight engines briefly, covering their origins and what they do. Then, we can move on to explore how insight engines apply to wealth management today.
Insight engines: enterprise search evolved
Insight engines are enterprise search evolved. Gartner retired the category of enterprise search in 2016. In 2017, they unwrapped Insight Engines to reflect the profound changes in customer needs and technology capabilities.
Insight engines differ from enterprise search both in what they offer and the technologies used. In their inaugural 2018 report, Gartner highlights how Insight Engines are different:
And they explain how the underlying technologies differ as well:
These capabilities stem from the use of artificial intelligence (AI) technologies, specifically natural-language processing, graph-based data structures, and machine learning.
Sinequa, a provider of insight engines to financial institutions, has been a leader in Gartner’s Magic Quadrant for Insight Engines since the category began.
Sinequa evolves enterprise search and insight engines even further. Coupling two decades of research in natural language processing with the latest deep learning approaches means users get immediate, relevant, auto-improving answers to their questions. Users have a complete view of customers or products or risks or contracts or deals all within a single view, created instantly from the most up-to-date content.
On advice, McKinsey makes three predictions:
- Hyper-personalized advice model built on data and continuous access.
- Bite-sized “fit-nance.” This means developing a granular ability to track customer investments, education, retirement, and broader financial wellness.
- Big tech will capture a large share of industry economics by providing core technology infrastructure.
The best investment advice comes from distilling mounds of data down into recommendations tailored to the client’s risk appetite and return objective. Sinequa’s Insight Engine delivers the investment insights required. The platform can search across all data sources including internal and external, cloud and on-premise, along with structured and unstructured data. Sinequa simplifies assessing financial wellness by providing a unified view of client assets and liabilities, irrespective of where the data is stored.
For advisors, McKinsey thinks their working lives will change in three ways:
- Advisors remit expands to provide coaching on broader wealth and life issues. And McKinsey expects the industry to shed a fifth of its total advisors.
- The face of the advisor will become much more diverse, spanning increased numbers of women, minorities, and mid-career changers.
- User ratings will become ubiquitous, making advisor performance transparent.
Increasing advisor productivity remains a perennial challenge. Things will get worse as the current generation of wealth advisors retire. Routine work needs automating, so advisors can focus on adding value through relationship management and advice.
Sinequa’s Insight Engine augments wealth advisors by saving their time foraging for data. And it applies decades of R&D in natural language processing, so advisors don’t have to read reams of documents.
Wealth management firms
McKinsey expects wealth management firms to have to make the most changes:
- Industry talent becomes more digital as wealth firms function as technology platforms.
- Several-at-scale firms will serve everyone while the rest will focus on providing differentiated service to ultra- and high-net-worth clients.
- Operational excellence will be required to protect margins from increasing transparency and falling fees.
- Integrated banking-wealth management ecosystems will emerge.
Insight engines can help wealth management survive and succeed in several ways:
- Accelerate wealth firms build-out of their technology platforms with reduced risk using Sinequa’s multi-use-case Insights Engine.
- Provide a unified view of clients to provide differentiated service to the extreme expectations of ultra- and high-net-worth clients.
- Achieve operational excellence by applying All the Alphas. Historically, the wealth management industry has over-focused on the most transient of the alphas – the quest for above-market returns or investment alpha. However, this has resulted in overlooking the value hidden inside other internal functions, such as distribution and service. Delivering exceptional performance (alpha) in these functions can create competitive advantages more durable than investment alpha.
- Find information and insight across any ecosystem, irrespective of the type, number, or location of ecosystem partners.
If you work at a wealth management firm and would like to learn more about how you can build tomorrow’s opportunities today, please attend one of our briefings.
Here’s how it works.
You choose how much time you want to spend and where you want to spend it. We have an Executive Briefing Center on West 30th in New York City or in Paris or we can come to your office. We customize each briefing to your objectives and business challenges. We’ll start the briefing sharing our perspectives on insight engines in financial engines, learn more about your business, and discuss topics tailored to you.