Having spent the entirety of last week delving into all aspects of fintech partnerships, and how they tie into our month-long coverage of fintech ecosystems, this week we’ll be shifting our attention to the understated sector of wealth management.
In light of higher inflation and tighter margins of profit, firms and folks alike are increasingly turning towards varied fintech services to protect, progress and restore their wealth. And for those that make this pursuit, wealth management arrives at the first-choice destination.
Here we’ve welcomed a diverse range of experts from the sector to discuss how incorporating contemporary technologies, including artificial intelligence (AI) and machine learning (ML), into wealth management is garnering a whole host of benefits for those that choose to adopt them:
Introducing our conversation, here Reena Raichura, director and head of product solutions at the desktop integration platform Glue42, explains how the wealth management industry is currently undergoing a ‘digital overhaul’ which is being accelerated by both the effects of the pandemic and the rise in the number of robo-platforms that larger and more traditional firms now have to compete with.
“Digitally savvy clients expect an ultra-personalised and bespoke service front-to-back and won’t hang around if a solution or service is digitally bland at best,” she says.
Desktop integration technologies like that of Glue42 are being leveraged to create ‘best of breed’ advisor and client-facing platforms, where data is centralised and cloud-based.
“Just moving to this type of micro-apps/services, data and interoperable infrastructure have been a huge boost for wealth management firms both from an employee and client retention perspective. The next logical step then is using AI and ML technologies to boost employee and client experiences even further,” Raichura continues.
Discussing the core benefits of AI and ML in wealth management, she points to hyper-personalisation, next best actions and proactive customer engagement as examples.
“Using a combination of desktop integration and AI/ML, advisors can curate client-centric cross-application ‘workspaces’ that enable them to get the relevant data they need at the point that they need it,” she says. “For example when a client calls, a workspace can pop up with the relevant windows and data required to have a contextual and meaningful conversation. This creates a ‘hyper-personalised’ client experience.”
“Take it one step further,” Raichura continues, “and desktop integration mixed with AI/ML can give advisors ‘next best action’ alerts by analysing client, market and other data sources to prompt the advisor with potential products and services offerings, or news and insights relevant to a specific client.
“The same technologies can be also used to push contextual notifications to clients through their digital communication channel of choice and create a more proactive customer engagement.
“Whilst AI/ML in wealth management is important for creating an emotional connection with clients, it’s the overall digital infrastructure combined that is bringing the benefits to wealth management.”
Access to data
Following on from this, Giuseppe Sette, president and co-founder of the AI-driven investment research platform Toggle, emphasises how the wider use of contemporary technologies like AI is generating a more comprehensive oversight of data.
“Wealth managers often field questions from clients who are closely watching markets and monitoring financial news stories,” starts Sette.
“They’ll be asked questions like, “What will energy stocks do if oil drops 10 per cent from here?” or “What will happen to my Tesla holdings if Ford exceeds their earnings expectations?” and giving a data-backed answer was incredibly time-consuming.”
Sette confirms that by harnessing the power of ML and AL, wealth managers can stay on top of the data and answer questions like this in a matter of microseconds.
“They no longer need to dig through endless PDFs to find their answers and have the ability to tailor the search to meet the exact conditions the client is inquiring about,” he says.
“And with ML, investors don’t need to run individual queries themselves. With the right software, they can answer questions like this without having to learn to code.”
Less friction and deeper relationships
Addressing the topic in a broader context, Niharika Shah, executive vice president and chief growth officer at TIFIN Wealth, describes the application of AI within wealth management as a transformational concept; a new way of doing business that must start with the firm’s strategic priorities and operating ethos/culture.
TIFIN Wealth itself is an AI-driven platform designed to drive personalisation at scale across investments, financial planning, personality assessments, risk assessments, client communication, private markets and charitable giving.
“Put in another way, the application of AI is not a one-size-fits-all idea,” she comments.
Shah designates the use cases for AI into two broad categories: intelligent automation that eliminates workflow frictions, and secondly, intelligence that enhances the advisor-client relationship using personalisation at scale.
“In both cases, the benefits are enhanced productivity and better outcomes for the client, advisor and the firm,” Shah elaborates.
“Clearly, the applications that have the most impact are the ones that achieve both: eliminate frictions and deepen relationships.”
To further illustrate her point, she points to charitable giving as an example.
Citing the data of Fidelity Charitable, Shah explains how advisors that incorporated charitable giving as part of their services experienced three-fold organic growth and 1.3-times growth in AUM per investor.
“This when combined with the fact that eight out 10 investors want to include charitable giving in their financial portfolio, the business case speaks for itself,” she comments.
“However, DAFs thus far have been complex to implement (workflow friction) with minimum thresholds and a lack of personalisation (impacts on advisor-client relationship).”
The platform’s ‘TIFIN Give’ feature has adopted the technology to simplify workflows, eliminating minimum barriers while using AI personalisation in underlying DAF investments to align its clients to specific causes.
“By placing the advisor in the centre of the relationship, TIFIN Give has created an opportunity for the advisor to engage cross-generational family members, a critical win given the wealth transfer imminent over the next few years,” concludes Shah.
“The rise of AI represents one of the biggest technological upheavals in wealth management,” comments Alfredo Rubina, vice president of financial services industry EMEA at SoftServe, a software engineering and digital transformation company that works with many of the largest global financial institutions.
Rubina explains how the use of AI in this instance is helping to unscramble both structured and unstructured data in real-time, while simultaneously presenting opportunities to increase efficiency, save costs and exploit growth potential in times of enormous pressure on margins.
He indicates that portfolio management is the first sector of wealth management to which AI is being applied.
“In portfolio management, AI-supported or fully automated investment decision processes are widespread, with robo-advisors being the most prominent example of the use of artificial intelligence in this area,” says Rubina.
“These digital asset managers are intelligent systems that use algorithms to generate, manage and implement investment recommendations and are able, for example, to proactively send alerts regarding investment-specific and market risks,” he continues.
Developing his point, Rubina describes how the use of ML is allowing trading algorithms to better identify the individual need of users in the optimisation of the decision-making process.
“This helps to relieve advisors of routine manual tasks and gives them more time for value-adding activities, while improved controls help to manage and minimise the risk of human error,” he explains.
Looking at related technologies, Rubina sees the most promising to be natural language processing (NLP), which helps analysts, investment teams and clients identify changes in public opinion towards companies based on information from social media and corporate financial reporting, among others.
The right investments at the right time
“Finance and investing are two of the most competitive markets today. Sophisticated players are experimenting with using the best in technology, including AI, to help customers manage their money,” adds Max Osbon, chief investment officer at Unifimoney.
The company offers a comprehensive digital wealth management platform with trading over 70 cryptocurrencies, and passive and active investing in thousands of stocks and ETFs and precious metals.
“AI presents opportunities for advisors, wealth professionals, and financial institutions to help their customers invest strategically,” he says.
Expressing these opportunities, Osbon discusses how the application of AI can help augment and simplify the analysis process, helping customers choose the right investments at the right time to build their portfolios.
“Leveraging AI to enhance wealth management offerings enables them to provide relevant advisory services to customers based on their portfolio and how much/often they invest,” comments Osbon. “Because of how much AI helps automate this analysis, advisors can expect huge time savings and a boost in efficiencies.”
Despite the benefits that AI is able to provide, as heavily outlined here, Osbon suitably closes our discussion with a warning to remember who’s really in control.
“While AI allows for better models to be built, designers will still need to train the model and not give it full control for decisions,” he says.
“At the end of the day, there should still be a person to direct the AI to express the desired outcome. Using AI requires work and guidance but should be top of mind for all finance and wealth management companies to compete now and in the future.”