Author: Clari5

Of the several significant innovations in the financial services universe, one key technology innovation has been the robotized financial advisor aka the robo-advisor.

A robo-advisor is a self-guided online wealth management service that provides automated investment advice at low costs and low account minimums, employing portfolio management algorithms.

A robo advisor can be ideal for those who don’t want to hire a financial advisor, don’t have enough assets to hire a financial advisor yet, or for those who have typically been DIY investors, but no longer want to select investments, rebalance and place trades on their accounts.

Some of the advantages and benefits of robo-advisors include:

• Bias-free, error-free, logical and transparent advisory
• Advise-on-demand with real-time, 24/7 access
• Speed and agility of analysis
• Better ROI for banks and wealth management firms over the long-term
• Risk profiling and advisory will get better with enhancements in cognitive computing, AI and behavioral analytics

Robo-advisors have been increasingly making their mark since a decade. Stats reveal the use of robo-advisors is steadily increasing. Robo-advisors managed $100 billion under assets in 2016 and this will increase to $2.2 trillion by 2021 (Fitch).

Some key factors contributing to the rise of intelligent robotized advisory services in financial services firms are:

• Explosion of data – data is doubling every 14 months and is expected to reach 10.5 zettabytes by 2020. This data is both financial (revenues, profits, growth) and non-financial (customer sentiment, employee engagement, marketing effectiveness, product feedback, and partner ecosystems). The availability of this data creates fertile ground for robo-advisors to provide algorithmic insights and recommendations that deliver highly predictive, error-proof and low-cost advisory services.
• AI is growing exponentially – many established firms worldwide (with about 20% in the U.S.), are making sizeable investments in AI. Venture capitalists are more interested in firms that are innovating robotized process automation. They invested between $4 to $5 billion in AI in 2016 alone with PE firms investing another $1 to $3 billion.
• Cost and availability – the costs of AI-enabled tools are falling, while availability is increasing. Proprietary as well as open-source tools are widely available and fueling the trend is the availability of low-cost cloud-based hardware.

Financial services firms are aware of the benefits of robotizing advisory services, including that it fundamentally lowers costs and helps broaden the range of service offerings.

While AI has brought about more innovation and greater competition, for an area such as financial advisory services that traditionally has a combination of trust, experiential expertise and human interface as its cornerstone, there will be some challenges to customers readily adopting robo-advisory services.

Leading financial services firms with in-person advisory operations servicing complex financial planning needs are aware of customer expectations around trust, financial growth goals and customized experiences. Also, certain investors are overwhelmed when trying to choose a reliable robo-advisor among a multitude of options available.

Tradition and mindset are also factors that make investors chose between engaging with a faceless software or with a human being. A lot of investors prefer human financial advisors, even though their advice may not be entirely accurate in certain cases. For instance, even when markets were indicating bottoming out, investors continued to apply the recommendations of their advisors.

A hybrid robot/human advisory model that blends the best of both worlds, could be a way forward.
Investment managers can optimize the quality of advisory services that require quick turnaround for portfolio-rebalancing or asset re-allocation and use human interface for consultative/iterative actions like goals achievement analysis.

Financial advisory firms can combine the best of client-centered technology and the benefits of the human touch in providing advice. For example, many traditional advisory firms already provide secure client portals on their sites where clients can login and view their account information and other valuable information. Some traditional advisors also offer mobile apps to facilitate client communication. Similarly, certain robo-advisors have an option to chat with a human financial advisor.

Blending the human touch of traditional financial advisors with the logic, fee transparency, methodology and accessibility of robo-advisors can be a useful combination for investors. They can access their portfolios and most of the advice online but can still receive guidance and personal advice from a human. This will make a difference as investors’ financial situations will evolve and market dynamics will continue.

References:

• AI and robo-advisors, TechRules
• Robo-advisors can’t create trust, CNBC
• How AI will change the role of financial advisors, Accenture
• How AI with robo-advisory works, MoneyControl
• Preferred payment methods of online shoppers worldwide – Statista
• Machine learning, AI and robo-advisers: The future of finance?, CFA Institute

It is perhaps an overwrought cliché these days to begin all serious contemplation through the digital lens. Nowhere is this truer than in the case of the BFSI sector, which has seen it’s fair share of upheavals in the last several months. Most notably (and perhaps tellingly), ‘Digital’ Fraud and Risk Management features high on the agenda of bank boards, as they grapple with new threats and new realities everyday. As monolithic structures threaten to crumble and further test the patience of the savvy investor and the regular consumer alike, it is prudent to try and understand the elements of the digital wave that can perhaps avenge the metaphorical Thanos in this new ecosystem.

Financial Risk Management (FRM) has historically been a core focus area of most progressive financial institutions that view fiduciary responsibilities as more than mere lip service. Deep in the bowels of the banking system, the Risk Management Committee often votes ‘aye’ or ‘nay’ on a potential loan/mortgage/advance by relying largely on years of honed intuition and a helpful dose of supporting data. What’s changed in this idyllic setting is the rapidity with which banking and digital boundaries have blurred, thereby throwing into the mix, difficult problems posed by Big Data and innovative methods of technological skullduggery that have evolved virtually overnight. To stay in business therefore, donning armor tailored in the digital factories of hyperaware tech giants and fintech firms may be the most meaningful solution.

At the frontline of this newly minted armory is Robotic Process Automation (RPA). While RPA’s home turf is in the area of repeatable and rule-based structures that require little human imagination, it has largely been implemented in operational efficiency improvements (purportedly, with some critics still insisting that the jury is out on this) and in back-end roles that have always had step-motherly treatment meted out to them. That said, RPA seems to have become more than just a digital buzzword, with several bankers viewing it as a potential panacea to the ills of human-controlled FRM. But is it?

Can it avenge FRM and save it from becoming a gangrenous canker that threatens to sabotage the system as a whole? That is a question that requires use cases to justify its utility, and forward-looking banks that can allay fears and doubts by boldly going where their predecessors feared to tread.

However, as is the case with every decision, one must remember that enthusiastic pros are often weighed against somber cons. RPA, by its very definition works its magic in structured, rule-based, repeatable scenarios that require little or no imagination. Brute force therefore, trumps creativity and ingenuity. But in the arena of FRM, increasingly weighty odds are being placed on swiftly changing scenarios, bringing with them new mountains of unexplored data and hitherto uncharted analytical territories that require intrepid and decisive action on the part of the mightiest heroes that the institutions can bring to bear on these problems. Thanos therefore begins to shrug his mythical cloak and becomes a clear and present danger that RPA may be ill equipped to handle alone. Where then does one turn to for additional ammo?

Just as the digital cliché is a convenient bandwagon to hitch prima facie arguments on, Artificial Intelligence (AI) and Machine Learning (ML) provide ample fodder for the ruminating analyst to chew on while contemplating solutions to problems mired in complexities that ‘mere automation’ is ill-equipped to handle.

AI/ML not only addresses the blind spot that an RPA solution to FRM causes, but also builds long-term resilience into the overall setup to ensure ‘future-proofing’ as far as such a concept is realizable with today’s technology. Complex scenarios can be mapped and the ML algorithms can learn from the data, develop parallel scenarios, understand underlying nuances between hitherto unconnected variables and develop a meaningful FRM business solution that banks can slowly pilot and then as technology, support and the ecosystem develop, deploy as a backbone to their overall digital offering.

Once again, it is prudent to look at all this in the context of the current scenario and try to delineate a pragmatic way forward. Presently the sector is turbulent, with flagrant customer and employee frauds, corporate governance lapses and an increasingly wary set of investors whose ROI, combined with the government’s political will could just be the decisive factors in the short to medium term fate of the Banking vertical in India.

Macroeconomic and political considerations aside, the microeconomics of prudence, choice and utility can best be encapsulated by Peter Drucker’s timeless pronouncement: “ The best way to predict the future is to create it.”

To predict the future therefore, we must look increasingly at deploying an RPA-first, AI/ML-next strategy that can bring back much needed credibility to a flagging FRM situation.