Why growing model portfolio customisation poses a challenge to scalability

Why growing model portfolio customisation poses a challenge to scalability

Jacobi co-founder, Tanya Bartolini discusses how model portfolios have risen to prominence, offering efficiency and cost effectiveness. However, the proliferation of these portfolios poses challenges to scalability and control.
Author: Jacobi – www.jacobistrategies.com


In this article, co-founder at Jacobi, Tanya Bartolini discusses how technological advancements enable firms to customise and manage model portfolios effectively, catering to diverse client needs. As the number of model portfolios and accompanying systems grows, it becomes crucial to adopt streamlined approaches that provide clear optics and improved client engagement. By centralising data and utilising analytical tools, investment teams can achieve both customisation and consistency.


Author: Tanya Bartolini, Jacobi co-founder


In little more than two decades model portfolios have come to dominate the way investment decision  making is packaged and sold to clients. Their success has enabled investment groups to deploy their  best ideas, from asset allocation to portfolio construction whilst at the same time delivering greater  efficiencies and cost effectiveness to investment firms. 


However, with all of that success, investment firms now face a proliferation challenge which impacts  some of the core efficiency benefits once gained. With some investment firms now managing 100’s  and 100’s of models they now face significant challenges to the scalability and control that they once  generated. The good news is that with technology, firms can both customise model portfolios and manage them efficiently enabling a higher volume of output. 


Something for everyone  


All clients are unique. Each has their own specific requirements. These may be risk tolerances, liquidity  preferences, volatility limits, tax sensitivities and so on. 


Add in preferences around active and passive approaches, fee levels, and in house or open architecture  – as well as investment groups targeting the outsourced CIO market with bespoke products – and you  end up with many potential product permutations. 


No wonder that investment groups and wealth managers have expanded the number of model  portfolios they offer to clients. Having 30, 40 or 50 in a single organisation is no longer unusual, and  some have as many as several hundred. 


This growth in model portfolio customisation comes at a price. It can mean investment groups lose  control of their own products. In such a world, how do portfolio managers ensure consistency across  the daily decisions necessary for asset allocation, portfolio construction and security selection? If, say,  a model portfolio drifts outside of its range of risk tolerances, to what extent is that portfolio, and the  clients it serves, diverging from agreed targets? 


And if consistency ebbs away, how can an organisation hope to report to clients with the granularity  and accuracy now seen as the norm? What level of confidence can a leadership team have that they  are adhering to increasingly onerous regulatory and governance requirements? 


Whilst customisation brings many benefits to the client – it poses challenges to providers.


Proliferation of model portfolios and systems


It’s not just model portfolios that have mushroomed. Systems have too. 


An investment group might not have as many as 30, 40 or 50 model portfolio systems. But the chances  are they’ll have too many for the task in hand. They’ll have varying degrees of compatibility. Data will be  common to some, but not to others. 


Parts of their data will almost always live in spreadsheets – often disconnected from other systems. If  we think about why model portfolios exist, this is a profoundly sub-optimal way to operate them. 


The value in managing model portfolios, and communicating that management to clients, surely lies in  making it as easy as possible for those clients to see why their assets are positioned as they are. This  direct throughput from investment team to client is essential to the quality and duration of the  relationship between them. But increased customisation has bred complexity. 


There’s a second aspect to multiple and inflexible systems. 


When investment groups rebalance model portfolios, they require their portfolio management and  trading systems to engage seamlessly and efficiently. Data needs to move whole and unimpeded  between the two. 


It is possible to do this through spreadsheets and ad hoc data input. But, in an era of increased  customisation, this is inefficient and risky. Portfolio managers increasingly need to set spreadsheets  aside and embrace a new way of working, where aggregated data can be stored, managed and  assessed in one place – and shared with internal and external stakeholders in a controlled manner. 


Command and control  


Imagine a world where model portfolio data – across 500 or even more products – all sits in one place.  Such a singularity of perspective enables anyone to track every aspect of a set of model portfolios and  to make accurate assessments and decisions with the utmost confidence. 


Customisation and consistency need not be a binary choice. 


For example, the strategic asset allocation (SAA) used to design a model portfolio using a consistent  asset schema and capital market assumptions to validate and analyse existing portfolios. Firms  can use them to set the SAA with an optimisation framework that reflects the unique process of the  investment firm. This can then be customised to different client preferences and objectives.


Take the task of making tactical shifts to existing models. Portfolio management teams must make  proposed changes rapidly and then analyse how these changes affect their many portfolios. Both the  analytics and metrics used to assess the impact on expected risk and return should be consistent with  those used in the initial portfolio design process. 


Clear optics – not spreadsheet spaghetti  


One of the advantages of a system that not only houses all model portfolio data but allows for the  management of those models is significantly improved client engagement. 


Let’s say a portfolio manager models a series of forward-looking risk and return scenarios across their  whole range of customised portfolios. The data that feeds the modelling all comes from one system;  this same system facilitates the modelling; and it also generates live, real- time charts that demonstrate  to clients or other key stakeholders the full impact of those potential future scenarios. 


This is the strongest possible link between the intellectual property of investment models and client  objectives. 


And, compared to the spaghetti-like approach of spreadsheets – with all the work they require to  compile, maintain and interpret – having just one system offers clients optical clarity over their  investments and the processes around them. 


This optical clarity works not just from portfolio manager to client – it also flows inwards, within an  organisation. 


Say a portfolio management team needs internal approvals for certain asset allocation calls. Or  perhaps they are nudging against the limits of designated liquidity ranges, given security selection  decisions, and need sign off from compliance. Perhaps there’s a need to de-risk a series of portfolios. Whatever the scenario, the workflow associated with such governance can be complex and time  consuming. 


But a multi-model portfolio management system that enables scalability and control can also offer a  much smoother workflow – again because all relevant data is held within the same system, making  interrogation and decision making by internal colleagues much more efficient and effective. 


And this is across an organisation’s 30, 40, 50 – or 500 – model portfolios. Not just one.


Model portfolios – remembering tomorrow  


If we accept that model portfolios are here to stay, and that they will continue to grow in number, in  terms of the assets they manage, and in customisation, then every single provider must be prepared for  what’s to come. 


Current best practice sees investment groups centralising their data and deciding which components  of model portfolios must remain consistent and which must be customised. Done well, this enables  providers to operate as many model portfolios as they wish with the utmost levels of control. 


Future best practice sees more of this – as smarter technology becomes increasingly the norm over  the next decade – offering greater transparency around objectives, product governance and portfolio  management. 


This means that any group operating model portfolios can embrace hyper customisation  wholeheartedly – rather than fear it and its consequences – as they serve clients more effectively, and  help them reach their objectives. 


About Jacobi 


Jacobi was founded in 2014 with a vision to transform technology used for multi-asset portfolio  design, analytics and client engagement. Jacobi provides its services to top-tier investors across the  globe with a client base representing assets under management of over US$7 trillion. Its award-winning  technology has its roots in institutional investment management and uniquely incorporates a market  leading software development kit. This allows firms to build their own models, tools and  applications on the platform.


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