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Wealth Management Focus on AI

Wealth Management Focus on AI

One of the more sober subsets of the financial services sector – the wealth management industry – has been majorly impacted by the AI edge.

From automating routine tasks for increased efficiency and cost savings, wealth investment firms are creating new use cases for AI, ML, and Deep Learning Technologies. Especially post-pandemic, when digital became our primary transaction medium, wealth management companies are hastily speeding up their cloud migration processes and investing in advanced analytics solutions to tailor client services dramatically.

The article elaborates on a few best practices in the AI-powered wealth management industry.

Present-day AI-influenced use cases for wealth managers. 

  1. Holistic AI-enabled investment advice. AI churns out personalized recommendations by synthesizing an investor’s current financial situation with past economic behavior and then aligning that to investment goals.

The subsequent investment recommendations yield the best approaches advisors can discuss with their clients. Much pre-work is saved in investment planning as activities like tax planning, and other input preparation exercises are automated.

With AI-driven algorithms (and platforms), the various tax scenarios, their underlying assumptions, and historical data are processed without human intervention.

  1. AI-driven Asset management. From predicting asset vulnerability to potential market risks to foreseeing market crashes, AI-use cases are on the rise.

An oft-cited example is how AI and ML’s pattern recognition skills are exploited to decide on equities buying and selling. How does that happen? By analyzing thousands of variables – like the company’s financial health, investor’s risk tolerance, and stocks’ historical or seasonal stock performance, specific risks to returns ratios are calculated.

Constant analysis of stock market movements enables recommendations to get sharper over time. With its quantitative and qualitative factors, this is only a start as AI-driven asset management is gaining quick ascendancy in wealth management practices.

  1. AI-led Compliance Management. Today trained AI systems can parse public notices for relevant regulatory information and compile reports. Investment policy statements, investment management agreements (IMAs), and exemptive orders are all examples of official sources that AI applications use to detect changes in the investment climate.

AI and ML systems collect, cleanse, and evaluate various data points to simplify compliance alert mechanisms. This proactively prevents a company’s resource wastage by optimizing its controlling algorithm, translating into direct cost savings.

  1. Robo-advisory. Robo-advisors evaluate a client’s risk tolerance and cash flow, among other criteria, before making investment decisions across stocks, bonds, or other financial assets.

As current projections go, approximately US$16 T in assets are expected to be managed by Robo-advisors by 2025. How does all of this play out? Investors begin by filling out online questionnaires that reveal insights into their investing preferences, after which product suggestions are offered. Next, without any human interaction, fund allocations and account reconciliations are carried out. Finally, the Robo-advisors automate asset swaps and financial investments through an ML system.

The listed technology practices are working because they align with what the new-age customers (Digital Natives and Millennials) want. Below we elaborate on the behavioral and ecosystem shift in the wealth management industry.

AI-infused future is reshaping tomorrow’s wealth management landscape.

  1. Hyper-personalization. Now wealth managers can balance personalization needs with automation. Through ML and CRM data, advisors gain insight into their clients’ wants, requirements, and perspectives at a never-before depth, even more than face-to-face interactions.

Generating a plethora of distinct client personas that extend well beyond the conventional wealth segments allows for the development of fully individualized user experiences. Particularly appealing are the swathes of information tailored to the client’s ESG interests, industry preferences, and financial objectives through a mix of portfolio design and rebalancing strategies.

  1. Next Goal Alignment. Post-pandemic, leading wealth management firms are applying ML strategies to provide Next Best Action suggestions for individual client portfolios. This enables advisers to scale up their ability to offer individualized advice.

Through an elaborate system of notifications and alerts, advisors build layers of iteration until the asset allocation needs are met. After that, using market data and CIO insights, sophisticated narrative reasoning is used to analyze customer behavior and determine the best course of action (or correction) to help each customer achieve their financial objectives.

  1. Simplifying Complex Financial planning. Modern digital planning engines can now perform intricate computations to offer a comprehensive, one-stop solution covering everything from strategy to particular goal support and product recommendations.

Additionally, they provide granular guidance for various circumstances beyond the scope of standard retirement planning. From planning for a child’s college fund donations to charity or a vacation house – all form part of a package that comprehensively meets a client’s future financial vision.

  1. 24/7 monitoring. Significant uptake of AI-driven wealth management solutions is constant, real-time observation. From real-time market movements to news affecting industries – the immediate availability of research, market data, and digital news is a game-changing advantage for investors.

Beyond weekly or monthly updates, clients today monitor their holdings as frequently as they check their inbox or social media for updates. More importantly, advisers today interact with clients and keep tabs on the markets, services, portfolios, and investment strategies – all thanks to the AI proliferation in the asset management sector.

Conclusion

Many financial institutions are exploring using artificial intelligence (AI) to enhance asset management, either as a replacement for human wealth advisers or, more typically, to supplement existing efforts.

Each firm’s AI initiatives are tailored to its particular clientele, investing strategies, and guiding investment principles.

In all of this, the growing role that AI and ML technologies will play in growing the wealth management sector cannot be underestimated.

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The State of Digital Transformation in Wealth Management

The State of Digital Transformation in Wealth Management

In the times ahead, 2022 would be seen as the pivotal year for how wealth management adoption grew and changed irreversibly. Coming out of volatile and ambiguous times, where consumers lacked physical offices, what investment advice would stand the test, there is also increasing evidence of how wealth-tech firms were betting big on digital technologies to drive more efficient wealth advice. Digital onboarding and servicing as processes allowed customers to balance short-term financial stability with longer-term yields. In short, the most significant gain for the wealth management industry is that most players, if not all, have begun taking firm steps towards a digital mindset.

Tectonic shifts, total transformation 

The shifts are apparent. Pivoting to a relationship-based model where advisors offer personalized advice tailored to clients’ goals and life events is possible because of several advances – unified experiences and functionalities like account aggregation, CRM tools, and client portals.

Another critical advantage for wealth managers emerges from scale and omnichannel servicing. In this regard, digitization of account opening, account transitions, and e-signatures, among other workflow tools, has made scale jumps possible, reduced errors, and cut the processing time. In the times of remote working, add to this pot the collaboration tools like Zoom, whose instant appeal among the millennials isn’t going unnoticed.

Seizing the Environmental Social Governmental (ESG) edge

Before every discovery becomes an industry default, there is a window where wealth management firms capitalizing on a trend can achieve quicker customer acquisition. Most analyst firms predict how the current global unrest around sustainability is a cause close to the hearts of millennials and GenY. Support for climate change and other social causes are more than just conversations. The younger investors want their wealth and portfolio managers to be aware of these nuances and offer solutions that have deep links to sustainability.      

Intelligent Automation

A critical fallout of the increased M&A activity in the asset and wealth management (AWM) industry is the increased adoption of RPA (Robotic Process Automation). Merging company and industry data, onboarding new clients, transferring data faster to the new systems, and high sensitivity errors detection and alerts are all coveted features of RPA tools and technologies.

Additionally, along with the various digitization technologies now commonplace (OCR and ICR), there are matters of compliance that automation practices are transforming within AWM.

Cloud Computing

Top wealth-tech players are moving to account management systems for enhanced tracking (and auditing) of documents. With security against data breaches, Cloud applications allow more flexibility and quick scalability through far cheaper subscription options (Software-as-a-service), freeing firms from heavy capital investments in data storage. This cloud-based software market size is expected to grow to $20B before 2026.  

Advanced Analytics and others

There is evidence that 71% of customers willingly share personal information with an increased demand for personalization. Then the onus of creating and maintaining empathetic connections is probably an advisor’s top priority. Wealth managers today use advanced analytics to transform data into insight for customers and channel these insights via interactive dashboards to do this capably. More than Robo-advisory as a notable AI /ML example, AWM firms are feverishly exploring more use cases across lead conversion, unstructured data ingestion, and high-frequency algorithmic trading. Finally, these tools offer unique ways to make optimal investment decisions. Admittedly, integrating these trending technologies is at its inception, and for AI and ML, the years ahead promise to be far more exciting.

Tech Titans in AWM

Across sectors and industries, firms today aspire to be either a technology company, financial companies, or both. Expanding their customers’ wallet share and consolidating their lifetime value are primary motivations for the FAANG companies (FB, Amazon, Apple, Netflix, Google). These digital savvy companies with deep roots in customer analytics are well suited to harness their vast swathes of data and enter wealth management and asset portfolios. Like felt across other businesses, such forays are likely to upheave the industry landscape, something that incumbent players must acknowledge and prepare for.

Emerging tech and the role of Data. 

Real-time settlement models, data privacy protection, risk, financial history, and investments in cryptos are tangible Blockchain use cases in AWM. The leading wealth-tech firms understand the value of executing such high-touch services by embracing emerging technology. As autonomous financial instruments and investment vehicles become popular, the traditional wealth management functions like client advisory and portfolio management will become leaner and be threatened with revenue erosion.

All the mentioned growth levers – Automation, AI, ML, Cloud Computing, and Blockchain – ultimately rely on the robustness of a company’s data infrastructure, including managing data quality, integrity, and governance.

Conclusion

The actual unlocking of the full potential of these as-yet inchoate technologies is happening with each passing day. With the increase in global demands for holistic wealth management, offering niche investments, bespoke advice, or customized protection will also rise. The competitive edge for AWM companies will come from ecosystem collaborations and embracing new technologies that drive the customers’ pricing and value balance.

 

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Five use cases for wealth management as a service

Five use cases for wealth management as a service

The promise to provide consumers with the financial services they need when they need them, over the right channel, and tailored to their context – has led technology to be the favored innovation lever for the financial sector. From wealth management, commercial, investment, and consumer banking, stocks, loans & finance, and foreign exchange, the most significant use cases have been seen in high-frequency trading, risk management, creditworthiness, commodity trading, and increased personalization.

Post-Co-vid, wealth managers are tackling some new and some very complex challenges. Staying relevant to the younger investors

  • ­Leveraging the latest Tech to stay relevant 24.7
  • ­Combating disintermediating posed by Robo-advisory services
  • ­Pressures to decrease fees and increase revenues.

The mentioned market landscape features increase the dependence on business processes and cost optimization, find ways to enhance investor experiences, reduce cycle times and errors, and finally, better utilization of advisor times.

BaaS and its merits

BaaS being API-based is not the same as white-labeling. Also called embedded banking, BaaS is when consumers use banking services through distribution channels that are not a bank or a financial services company. For instance, when you use the wallet feature of the rideshare companies or convert your purchase into EMI’s at the supermarket aisle – those are examples of BaaS. The distinct advantages are that the financial component becomes flexible, quicker, and technology-friendly at an inexpensive differential.

When applying BaaS to wealth management, the possibilities of conducting banking in more non-banking channels make for exciting propositions.

  1. Self-Service in Wealth Management

 Banks are experimenting with a “go-to-wealth” manager by revamping the direct-to-consumer strategy. Implementing a single offering for direct investments and financial planning, the services providers are developing both the digital channels as they take off the legacy platforms. To fully service affluent clients, re-engineer the execution of processes, and improve product capabilities – are all effective ways to significantly reduce the cost-to-income ratio.

  1. Developing Multiple Value-adding Tools. 

From enabling clients to see wealth managers’ virtual availabilities to tools that resolve queries and next-gen communication platforms, including screen sharing, are upping the boundaries of wealth-management practices that have long relied on face-to-face advisory services.

Several ‘what-if’ analyses tools are expanding the client’s knowledge across multiple investment options, resulting in higher conversion.

  1. Next-best-action in Wealth Management 

The growth in the number of sales prospects, touchpoints, and communication channels makes it impossible to manually calculate the probabilities that will bring in the best engagement on an individual basis. For precise targeting of the hard-to-let go offers, modern ML algorithms continually discover customer buyer journey patterns to effectively motivate clients to buy, thereby enhancing marketing and sales ROI.

  1. Financial Markets and Investment Analysis. 

Choosing to invest in a stock, company or commodity relies on Data sciences today. The increased pressures to automate and make the process more and more foolproof is a technology end game hotly pursued by the best in the business. Consider the practices of algorithmic trading that are used to choose which are the favored stocks. Advanced mathematical formulas guide bankers to select the best stocks and visualize a long-term risk-optimized management strategy for these stocks. Reliable scientific results come when data fed to the ML algorithms grow both volume and richness.

  1. Advanced Analytics in wealth management 

 Advanced analytics is used extensively in wealth management, from lead generation and pitching to onboarding and transaction execution, reporting and reviews, servicing query resolution, and communication. Wealth managers use the digitized operating model to support advisory and non-advisory activities and service the changing investment preferences. Building modular data and IT architectures enables intelligent decision-making and personalization at scale. This is not only about meeting regulatory obligations but also boosting the productivity of investment advisors.

Conclusion.

A wealth management firm comes together when people, processes, and technology work in a mutually enhancing manner that offers the best client experience and makes for a strong case of efficiencies by automating routine tasks, thereby freeing up the advisors to respond with higher agility to the client needs. After all, the best possible resource they bring to their relationship is trust, and growing it, requires ample quality time.

 

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2022 Trends in Wealth Management Driving the Industry’s Future

2022 Trends in Wealth Management Driving the Industry’s Future

In 2022, wealth management firms consisting of commercial, and retail banks, universal banks, fund management companies, online trading platforms, private banks, brokerage firms, and family offices, are in a reinventing mode. Demographic shifts (before 2030, millennials will be five times wealthier than today) and increased digitalization (automated workflows, improving hyper-personalized products, the impact of data analytics in client acquisition, servicing, and retention) drives profound changes in an industry that is in a hurry to shed its ‘conservative cloak.’

Here are 2022’s top seven trends for the wealth management industry 

Soul Searching and Money on their Minds

Pandemic brought in waves of reflection. As people began rethinking their relationships with work, purpose, and money, COVID variants brought stock market uncertainty. Low-interest-rate environment prevailed, cash usage fell, inflation rose, remote working changed the nature of wealth advisory services, fund managers favored diversification approaches, and cloud computing (amongst other technologies) gathered steam in its industry journey.

Every dark cloud brings its silver lining.

In the last 24-months, the spurt in financial planning needs – short and long term – shows enhanced customer motivations to envision, plan and start on their life goals. So, what’s needed? Hordes of informed customers today look for competent (and digitally equipped) wealth managers to help them across the spectrum – from tax advisory to estate planning and will creation and everything in between. 

Blockchain and crypto complexity is no longer ignorable. 

While blockchain impacts across retail banking and asset management get discussed, it is a matter of time when wealth management use cases see the applications of real-time settlement models, single point of truth, automated investment vehicles, and smart contracts. The distributed ledger technology promises to severely disrupt the industry – from how financial transactions are executed (threatening transaction fees), crashing costs of KYC and investment profile transactions, and more importantly, when cryptos are offered as a mainstream investment asset choice. A few banks (UBS) are experimenting with distributed ledger technology-based trade finance systems.

Baby Boomers pass the baton to Millennials. 

In the generational relay race, as millennials prepare to run the next leg, the technology functions as the baton. The wealth management industry, to be fair, has been in a preparation mode for some time – advisors’ compensation structure has moved from a compensation-based model to goal-based frameworks. The new generation advisors lean towards data and analytics to juggle multiple investing strategies with often contradictory client asks. The sweet spot is to stack the highest returns via a hyper-personalized portfolio aligned to unique life goals and lifestyles.

And what are the technology systems driving the goal?

From cloud computing platforms for data and richer insights to embracing open API architecture for 360-degree customer views to Robot-based advisory services, predicting life events via AI/ML detection systems, and product propensity engines for affinity offers.

Old-world customer experience still wins. 

As more clients adapted to virtual meetings overnight, what surfaced as a winning practice was something the industry knew as its single biggest differentiator: trust in a one-to-one personal environment. The shift is evident. More than seeing a product as a single source of value, customers now seek value in the experience of how a product or service is delivered. Static, episodic, and manual planning processes have to go. Instead, the millennials and device-savvy customers ask for more dynamic, ongoing, and digital choices. Moreover, financial security has consistently ranked high on a successful wealth advisor’s list, but the pandemic emphasizes that one size will not fit all and focuses on combining risk planning with growth.

Developing an ecosystem focus for wealth management hypergrowth.

Hong Kong’s Total assets under management (AUM) rose 21% to $4.5 Trillion in 2020, while private banking and wealth management reported an increase of 25% to $11.3 trillion. In a stiff competition for global wallet share, the island region continually punches above its weight because of multiple factors. The transparent regulatory framework, technology-embracing climate (including robot-advisors and high VR usage in the industry), a professional talent pool, and the broad availability of new-age investment offerings (art and wine, for instance).

Go Green, beyond the currency. 

While financial returns will continue to occupy full attention, a growing segment of investors expects their wealth managers to know more about the current ESG issues and practices. ESG, or Environmental, Social, and Governance, is today’s direct result of rising consumer consciousness so that planet is seen as equal to profits, meaning equal to money and growth as equal to Green. In product design, fund allocation, and performance parameters, significant efforts in the wealth management industry show a considerable ESG influence. 

Final words. 

In a world that fights one variant after another, the power to do good and the ability to be good comes from the belief that customers are secure in their current material spheres and protected in their future goals. Wealth management has a direct and pivotal role in cementing that belief.

Never has there been a time in history when the industry has had a more significant power to change the future.

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Top 5 Digital Transformation Challenges In Wealth Management

Top 5 Digital Transformation Challenges In Wealth Management

When it comes to meeting challenges, there are two truths. First, effective problem solving involves digging at the roots instead of hacking at the leaves. Second, a problem can’t be solved until we ask the right questions. So along with digital transformation challenges, let’s look at the dynamics that creates them, and ask questions that help us solve them.

How large is the AWM industry?

One PwC release talks about how with $110 T in assets (2020), the asset and wealth management (AWM) industry can quite literally shape a better future for investors, shareholders, the economy and the society. As one considers the growth projection of 5.6% YoY, and the resultant size of $147.4 T (2025), the enormity of it all sinks in.

Moving from ‘What-if’ to ‘What-is’.

For years now, AWM industry could have used benefits that fell off the pandemic. It is an odd statement to make (after all, no one wants an event of such scale and destruction). In the context of AWM digital transformation, wealth management systems primarily functioned with back-office support and on legacy platforms. The digital presence was limited. The anachronistic practice worked on one-to-one, product-led advisement. Not anymore. Consumers today discover products digitally and decide differently.

Technology undoubtedly is at the heart of the modernization, but successful wealth management transformations need to be customer-centric powered by scalable next-gen platforms.

With that caution, let’s get down to the top 5 digital transformations in AWM

  1. Managing the wired investor. Slow adaptation to demographic shifts.

No longer is the lucrative AWM segment made up of 50-year-olds. The segment sees a growing number of HNW millennials and women. A recent world wealth report posits that HNW clients are likely to transfer $68 trillion within 25 years to their heirs. Firms and technologies, as the study highlights, are neither prepared to manage expectations of new-age beneficiaries nor have a plan to arrest 80% of heirs that are likely to change financial advisors. For meeting the unprecedented scenario, both advisor experience and machine-learning approaches are necessary.

Transformation Trigger

Do your solutions fuse optimal elements from science-based advice (asset allocations, mutual funds selections etc.) with human-based advice (more complex needs – tax & asset planning etc.)?

  1. Rise of emotional analytics. AI-based wealth management.

In a client-advisor relationship, human emotions guide and reveal the most important component: trust. Even so, the same validated human behaviour AI technologies deployed in making autonomous vehicles and remote medicine, are enabling financial advisors to bring up best interest by detecting (and managing) client behaviours.

Transformation Trigger

For your AWM organization, what is the appetite for AI-based targeting and personalization initiatives through emotional analytics solutions?

  1. Behind the curve on Big Data and Analytics. Creating Insightful Personas.

Gauging real-time market sentiments, hyper-personalizing services, and providing for omni-channel customers who have several bank accounts, call for advanced analytics. AWM firms using simple analytics (MIS reporting systems) for mining customer insights, and assessing product penetration, are woefully behind in the digital transformation race.

Transformation Trigger

When it comes to Data Analytics, how much of time are you making for tracking business performance, client acquisition, sales & retention, and ultimately, client advice?

  1. Underutilizing the power of API’s. Growing reach.

AWM companies that are in a fast catch-up mode are prioritising their business tactics – calibrating clients, clearing out legacy systems, and rationalizing portfolios.

Success of these repair initiatives will however depend on how deep they engage with the ecosystem and equip workforce with newer capabilities.

Eventually, their growth narrative will have to face up to two imperatives:

  1. Bring in agility through platform customizations and
  2. Enable remote access that covers wider geographies

These two essential value-plays are fulfilled through API’s (application programming interfaces).

Transformation Trigger

For introducing new functionalities, sharing analytics with client, or even, for reducing costs, how well-versed is your wealth management company with ‘everything-API’?

  1. Embracing Digital Transformation at the core. Holistic goals-based advice.

While AWM organizations make investment in Data, Analytics, AI and other technologies, most fail to embrace it as a culture. There are exceptions though. Like the Toronto-based TD bank group’s program, called WealthACT. Today investment advice is largely commoditized for mass market offerings. Also, post-pandemic, the investing environment has grown uncertain and complicated. To combat this, leading AWM firms invest substantially to train employees on goals-based advisory frameworks.

The digital transformation challenge, however, comes from a lack of access to right tools and a maturity-approach that asks for a complete embrace of ‘digital as a culture’.

Transformation Trigger

In your AWM company, does the digital transformation programs specifically include skills for understanding emerging tech, and building empathy for the ‘new-wired’ customer?

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