One of the most fascinating parts of being a consultant these days is helping shape the continued importance of technology in a firm’s overall strategy. Firms with a right to win in the next decade should be those that have mastered technology’s illusive potential to better automate the mundane, enable their workforce, and ultimately provide the next level of service to clients.

Artificial intelligence—one of the most hyped technologies over the last several years—is a prevailing topic of conversation I have with many clients, particularly around its real potential in wealth. And the overarching theme in most of those discussions is not a surprise—how to scale AI effectively. This meshes with Accenture research that shows 84% of C-suite executives believe they must leverage AI to achieve their growth objectives*.

Beyond that overarching goal, my conversations with clients usually center around three key areas. Let’s dive into these to merge some real-world insights with what survey data says.

#1 Wealth management firms are still in the early stages of achieving broader business value with AI, lagging other financial services areas.

More than three out of four (76%) wealth executives in a recent Accenture survey said they’re struggling to scale AI across the business. Shrinking discretionary investment budgets and advisor uncertainty about end results exacerbate that struggle. To their credit, though, they are launching things: 60% of survey respondents are already deploying AI across their organization, roughly 3 out of 10 (28%) are scaling and 12% are planning and experimenting.

But of the many paths to launch AI, all require getting the right data to get started. Some firms may jump right into gathering as much potentially relevant data as possible. In fail fast/learn fast mode, they would learn some lessons up front and then become wiser and more selective about which data to include in their analysis. Others might start selectively aggregating data in the cloud, using a cloud data warehouse that can be catalogued. This would allow them to have some quick wins and necessary learning early in the process.

#2 Data quality, management and security are among the top challenges.

The amount of information to be cleansed, quality checked, and extracted across legacy siloes before it can be further parsed, integrated and analyzed can feel like an avalanche. While data quality and management are age old issues, many wealth management executives are grappling with not only how to manage and secure their own firm’s data, but also to integrate it securely with external sources of data—from business partners and third parties.

We help clients use AI tools like cloud-based data lakes that can enhance trusted AI governance. Governance is taking center stage, as data privacy is core to responsible wealth management. Regulatory requirements stemming from the General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA) have sped up wealth managers’ quest for the proper controls and tools to protect client data. The remote work environment spurred by COVID-19 has made that protection more complex, adding a host of personal devices to the mix. And even further, recent events have made it clear what an ongoing threat cyber continues to be—a risk that is only exacerbated when dealing with individuals’ personal finances.

#3 Wealth is all about enabling the advisor, so keep humans part of the mix as you add AI.

In wealth management, advisors are the lynchpin to the client relationship—given this, it’s no surprise that almost half (49%) of the industry is focused on front-office use cases. However, this is a dual edge sword. First, if advisors are not part of the AI design and implementation process, the initial work will likely not succeed. Second, successful advisors have developed and honed processes and workflows that personally work for them over the years—getting them to be willing to experiment and actually change those patterns requires more than a leap of faith. While the road to get there may be long, the opportunity is clear as 77% of wealth executives believe AI will transform the advisor-client experience via tools like augmented CRM that enhance the industry’s very personal and real nature.

Interestingly, the very AI technology that wealth advisors need to buy into can also be used on the sidelines to monitor and help improve their success with clients. Some firms are using behavioral analytics to understand and monitor the success drivers essential for their advisors, help pair them up with potential clients, and even help them identify which clients are at a higher risk of attrition.

Look for more in this space

The future of AI in wealth is promising but not yet fully charted. To help your firm as it starts or continues its AI journey, my colleagues and I will be publishing a series of blogs on key hot topics—including funding, data and culture considerations.

Look for more in this space soon. In the meantime, don’t hesitate to reach out if you’d like to further discuss what we’re currently seeing in the market.

*All statistics mentioned in this blog are from Accenture’s AI in wealth management: Built to scale publication, 2020