How wealth managers can navigate hyperautomation

Wealth management firms can realize the power of digital transformation through hyperautomation. 

As wealth management organizations transition to a digital-first mindset, the industry has collectively recognized automation as a foundational lever of a broader front-to-back digital transformation.

According to the EY-Parthenon 2022 Digital Investment Index, firms across all sectors are making record investments in digital transformation this year, up 65% from 2020.

In fact, forward-looking wealth firms are spending 20% of their operating budgets on digital innovation — including investments in automation technologies — with the most innovative firms spending significantly more. This underscores the importance of dedicating spend on building, strengthening and scaling automation solutions. [1] In this case, automation solutions refer to a wide range of techniques that enable the digitization, processing and evaluation of information to fundamentally change how work is performed front to back.

 However, with one third of wealth managers still at an early stage of digital maturity, there is a pressing need for wealth organizations to chart a more aggressive course for their automation journeys.

Confronting industry-wide challenges with automation

With the current level of disruption facing the wealth management industry, incumbents can use automation to offset four key challenges:

1. Shifting to a digital operating model: Wealth management organizations have often found it more difficult to successfully embrace automation than other sectors, hindered by legacy technology architecture, manual or paper-based processes, and poor data quality. In instances where automation has been properly leveraged, it has established components of a digital operating model that enables scalability and efficiency.
2. Relieving fiscal pressures: Wealth managers continue to focus on flattening their cost curves as a means to grow profits. The rising cost of regulatory requirements — such as consumer protection and cybersecurity — makes it increasingly critical to leverage automation to reduce operating costs not related to compensation.
3. Adressing client needs: Firms are also tasked with redefining the client experience across the spectrum of wealth management services. Clients are demanding seamless, omnichannel interactions throughout the entire customer lifecycle. Firms must leverage emerging automation technologies to design a personalized, client-centric experience. Examples of this include: i) enabling a digitized onboarding that is simplified, secure, and engaging; ii) guiding client interactions through chatbots, or iii) using intelligent automation techniques to produce continuous data-driven insights, such as market sentiment analysis, client profiling and transaction analysis. Advancing their automation agendas can also help wealth businesses futureproof themselves by enabling them to connect with their next generation of clients.
4. Redefining the advisor value proposition: Amid the Great Resignation, wealth managers must equip their advisors with the appropriate capabilities — technology stack, vendor ecosystem and data architecture — to deliver an exceptional client experience and foster hybrid-advice relationships. To improve advisor attraction and retention, firms must empower their advisors to focus on productivity, value-added tasks and high-touch interactions by automating their traditional activities wherever possible.

To stay ahead of the curve, wealth managers need to take advantage of automation to harness the collective power of processes, people, technology and data.

Bringing a connected ecosystem of automation capabilities (also termed as "hyperautomation" by Gartner) to life 

The speed at which the automation landscape is advancing can pose a significant challenge to wealth managers, given the industry has yet to master the successful adoption of traditional, rules-based technology. These tools are focused on improving high-volume, manual, repetitive and/or data-intensive processes. 

A greater risk, however, emerges when automation transcends these basic tools, which are often limited in their scope and narrow in their application. If firms use these tools in isolation, they could miss out on the opportunity to drive greater value by automating and streamlining end-to-end processes, potentially stunting their digital growth.

This evolution has accelerated the need for leading wealth management organizations to invest in an ecosystem of more sophisticated, intelligent technologies to complement their existing robotics capabilities. These new tools have the power to emulate human behaviour, judgment, and reasoning.

When it comes to their automation strategies, wealth managers should adopt a hyperautomation mindset in exchange for a one-size-fits-all solution.

Hyperautomation refers to a strategic blend of task/process automation and knowledge augmentation tools across the continuum of automation capabilities that are fit for purpose (see Figure 1 for an overview of the intelligent automation spectrum).

Figure 1: Intelligent automation spectrum 

Hyperautomation yields higher benefits than the traditional automation approach, as it allows for end-to-end automation through a unified application of technologies. Hyperautomation flexibly extends beyond the use of basic technologies to automate standalone tasks by orchestrating and streamlining processes with both structured and unstructured data.

Specifically, wealth managers can now automate highly complex processes that historically required human input using machine learning (ML) and artificial intelligence (AI) capabilities, intelligent workflow orchestration, decision management suites, intelligent business process management (iBPM) and other cognitive applications.

For example, wealth managers can employ hyperautomation to enable seamless, front-to-back integration for common transaction processes. The organization could apply intelligent optical character recognition (iOCR) to extract unstructured and handwritten data from client documentation, followed by robotic process automation (RPA) to categorize documents and validate information, and iBPM to update the case with additional documentation and manage approvals. Simultaneously, natural language processing (NLP) chatbots could be adopted to support advisors with any questions they may have throughout the process while providing insights on customer trends.

Employing process-first hyperautomation 

The key to enabling a process-first hyperautomation approach is to apply automation holistically using three key steps:

1.  Identify organizational pain points within end-to-end processes — including a review of operating model architecture, data management and accountability practices — across front-, middle- and back-office functions
2. Assess the full automation spectrum to understand the optimal scope, applicability and use cases for each tool, review the business’s existing portfolio of capabilities and explore investment opportunities for new automation techniques
3. Perform a mapping exercise to prudently select a combination of automation capabilities to maintain, enhance and/or invest in that are suitable for the identified process pain points

The above approach can also be conducted with the use of process mining and task mining to shorten discovery time and provide data-driven insights to the organization.

Process mining refers to the extraction of knowledge from event logs in application systems to discover, monitor and improve current processes.

Task mining allows firms to capture user interactions and desktop data to optimize their advisors’ workflows.

Together, these powerful tools can be deployed to identify suitable candidate activities/processes for automation.

The result will be an automation ecosystem unique to the firm that has the power to transform and digitize the enterprise in line with the organization’s identified strategic drivers and needs.

Industry players that can build a custom automation toolkit using this approach will come out ahead with their ability to skillfully combine techniques that digitize and structure data, process information, and enable cognitive decision-making to drive business outcomes.

Applying automation front to back

How can wealth managers successfully bring automation to life for distinct front-to-back processes?

Front office digitization can be achieved through next-generation virtual assistants or chatbots that use ML and subsets of NLP. These capabilities can promote self-service, ultimately increasing the speed of responses to complex problems, reducing volumes for mid-to-back operations functions, generating data insights and enhancing client experience. Based on a recent internal EY case study, a service centre automation effort that operationalizes chatbots and portals could replace 10% to 20% of human effort spent on basic servicing tasks.

Intelligent automation can also offer digital flexibility and enhanced efficiency for a wealth manager’s KYC and onboarding process. Capabilities such as OCR and digital forms can process unstructured and semi-structured data to enable seamless client onboarding. Automating the KYC process could yield upwards of a 30% reduction in process costs.

iBPM is another example of an evolved technology that combines standard business process management software with an integrated AI component to help wealth managers automate specific start-to-finish processes, such as cases requiring collaboration across front- and back-office stakeholders. 

Looking ahead

EY teams have supported clients from strategy to execution across the full spectrum of traditional and emerging automation technologies.

EY was named a leader in a 2022 assessment of the RPA Services market landscape and was also recognized as a 2022 MarketScape leader in an assessment of the Worldwide Intelligent Automation Services vendor landscape.

Is your organization ready to embark on a transformative program to accelerate your automation journey?

For more information on how EY Wealth and Asset Management Consulting teams can help, visit ey.com/ca/wam and reach out to start a conversation.