Andy Robertson is Chelmer’s Director and Chief Innovation Officer. His focus is on shaping the future of investing and wealth management, playing a vital role in setting production direction for Chelmer’s wealth technology solution, Myriad. His career has been in financial markets and financial services with a technology solution and is committed to providing elegant solutions.
Australian managed account market overview
Managed accounts have emerged as a focal point within Australia’s financial advice landscape, gaining increased attention as their role in the retail financial services sector, and financial advice in general, continues to significantly grow and mature.
The six-monthly managed account census data released by the Institute of Managed Account Professionals (IMAP) and Milliman in September 2025 shows managed account funds under management (FUM) totaled $256.24 billion as at 30 June 2025. That’s an increase of 24.6% from $205.58 billion the year before. Of that, SMA’s market share has increased slightly with 66% ($169.36 billion), while managed discretionary accounts (MDAs) are steady at 23.5% ($60.38 billion) of managed account FUM.
IMAP Chair, Toby Potter, says the results “[are] a strong signal that advisers are finding more clients whose investment goals and service needs suit the appropriate use of managed accounts.”
There is no doubt that the managed accounts sector is delivering to those investors and advisers.
Managed accounts give advisers greater flexibility to provide more efficient services and professional portfolio management. The integration of managed accounts technology into advice workflows allow them to rebalance portfolios in real time, automate reporting, and have more effective oversight of diversified investments to ensure consistent alignment with client goals. The discretionary account service model can also achieve a higher adviser-to-client ratio and the ability to increase that ratio and investor personalisation well in excess of a traditional advisory model. Because of streamlined operations and improved efficiency, advisers are able to focus on managing their clients’ needs and the relationship while automating portfolio administration and reporting.
For investors, the key benefits of managed accounts typically lie in better returns, exposure to various asset classes through their primary investment platform, greater transparency and the ability to have personalised preferences taken into account.
Specialist technology for wealth management
There is a diverse range of wealth management software available in the market, from global SaaS providers to custom-built in-house solutions, each with varying functionality, performance and user satisfaction. The ability to scale operations while accommodating personalised preferences has become essential as managed accounts continue to grow in prominence.
In 2023, Chelmer in conjunction with Suite2Go, reported identified two critical success factors among leading management account providers: customer centricity through enhanced visibility, strong client portals and comprehensive reporting; and modular, scalable platforms that deliver complete front-to-back office solutions. (Souce: The current state and future needs of wealth technology 2023 report)
Chelmer has been pioneering financial technology for over 30 years, providing specialist wealth management software to leading firms across Asia-Pacific. Today, our wealth management software Myriad manages over USD $70 billion in investor assets, processing hundreds of millions of dollars in daily transactions for our clients.
Myriad is purpose-built to support the flexibility and complexity that managed and discretionary accounts demand. As a tailorable software solution, Myriad enables wealth managers to operate with greater efficiency across the complete business lifecycle, from customer management and target asset allocation through to order execution, transaction settlement, portfolio aggression and reporting.
Our modular approach means you can expand existing functionality or work towards a full replacement of legacy systems, creating operational efficiencies that free your team to focus on what matters most: client wealth creation.
Managed accounts technology requirements
The burgeoning growth of managed accounts in the Australian market is being fuelled not only by shifts in adviser business models, but also by rapid advances in wealth management technology. Managed accounts technology is playing a pivotal role in enabling advisers to expand their managed account offering by making advice delivery more scalable, compliant and cost effective. Personalisation is a key benefit of good efficient managed accounts technology used in a discretionary service, but it also offers standardisation where it is important.
Core technology components financial institutions need
Wealth management technology supports various financial service models, including investor led, adviser-led and discretionary businesses. Technology should allow businesses to facilitate self-service for clients and adapt to changes in client preferences, such as moving to adviser-managed services or discretionary options.
Whether you are running a discretionary accounts type service or a managed portfolio service, the underlying technology requirements are extremely similar.
If you look at the modules of functionality or data in advice-led business, the technology will define what an asset is and information about that asset. That includes client representation, things like origin and destination of funds and asset ownership, and asset representation, including characteristics and trading methods. You will be running some form of portfolio and the ability to report on that. You will be placing orders and passing that through to execution management systems, and you are going to have reporting at various levels as well as some level of compliance overlay.
To start providing discretionary account services, there are a couple of key additional managed account technology or data elements that are needed that may not have existed in an advisory or traditional broking service model. Generally speaking, if the technology has been done well and is a good managed discretionary accounts platform, it will have all the data and elements of a traditional broking or advice technology platform, but with the additional functionality that allows you to concurrently provide a SMA or MDA type service model.
Here’s one way that Myriad does this.
Target asset allocation
A target asset allocation defines the desired or ‘target state’ of a portfolio. It sets the exact mix of assets that a portfolio should hold to achieve its investment objectives. In discretionary managed accounts, each client portfolio is attached to one of these target asset allocation models, providing consistency and a clear investment framework.
Essentially, you are looking for managed accounts technology to capture data for the portfolio target or model portfolio, not just at the top level asset allocation to asset classes, but all the way down to the individual asset weightings themselves. This, when combined with the actual portfolio holdings, provides the mechanism to rebalance (mass order generation). The business process shifts from changing portfolio holdings (orders) to changing models (targets).
To gain efficiency benefits from managed accounts, the target asset allocation must be defined at the individual asset level. This granular detail enables systems to automatically generate and process orders for rebalancing and adjustments. Without this, the system cannot efficiently execute or scale the management process.
Portfolio rules
In addition to portfolio targets, the managed accounts technology will need to hold compliance related investment data.
Looking at target asset allocation or looking at the portfolio tells you what you should have or do have, but is silent on things like what the investor cannot do or what assets the investor cannot hold. You might see that your Australian equities are at a given target weight, but you cannot necessarily tell if there is a target range and whether the target is within the range, or that they cannot hold Malaysian Equities.
So, you are looking for technology to capture data around concentration/exposure rules and any exclusions or suitability criteria.
Some of this may be organisation policy, some may be organisation profile setting, and some will be individual client personalisation. These are typically a combination of ‘must haves’, including asset type, sector etc, but also the ‘must not’s’, for example you cannot hold certain asset classes or assets. Good managed accounts technology will validate that changes in the model portfolios/targets conform with the compliance data before they come into effect, and that orders generated at the rebalance stage also conform with the compliance data rules.
Using standardised target asset allocation models allows advisers to serve more clients efficiently. For example, managing 30 model portfolios for many clients is far more scalable than managing 100 unique allocations for 100 clients. The goal is to maintain a manageable number of target models while still offering personalisation. Managed accounts technology allows for individual investor constraints, for example excluding certain sectors or assets, on including certain assets or holdings to be applied on top of a shared target model. This provides personalised portfolios without creating entirely new models for each client. What that means is that a client is attached to one of the common mandates/models, but their constraints or overrides are being applied individually against that target. This means Investment Management/Asset Management is managing fewer models/mandates without dealing with individual investor requirements, but the Adviser is still able to provide many highly personalised outcomes to their clients.
Rebalancing
Having the target asset allocation at the individual asset level not only provides transparency because you can see exactly what you are going to invest in, but it also now means that technology can do rebalancing.
Rebalancing is simply mass order generation, creating buy and sell orders to align holdings with their target weights. However, adjusting a portfolio to bring it back in line with its target asset allocation can only be achieved if you have both the current portfolio holdings including existing orders and the target asset allocation at individual asset weights.
At its simplest implementation, rebalancing automates the adviser manually entering a lot of orders which can be done over a period of time. Rebalancing in some service models may still be performed by an adviser or portfolio manager, and may allow for variance from the targets, but other business models may have the rebalancing being done by technology as an automated background process.
Gone are the problems of manually placing orders in all portfolios to sell an asset that needs urgently removing from a portfolio and the inequality in execution that causes because of timing or not being able to reach clients to make a decision on an elective corporate action.
More complex scenarios can also be handled by technology like Myriad which holds detailed asset and client information, for example the switch from an unlisted fund in custody where the cash redemption may be weeks after the order execution into buying an equity registered to the Client HIN which expects payment 2 days after execution.
Individual asset weight management vs basic asset allocation
Basic asset allocation, seen in advisory models, categorises investments into broad risk profiles (eg conservative, balanced growth) by defining percentages across asset classes like cash, fixed income and equities. Based primarily on the client’s risk profile which determines how much risk and return are targeted. For example, a high risk portfolio might hold 70% equities, 28% fixed income and 2% cash. A conservative portfolio might reverse those allocations. This level establishes the general investment strategy, but doesn’t specify which individual securities or investments are held.
Individual asset weight management moves beyond top-level categories to define specific holdings and their target weights within the model. For example, instead of just “30% equities” it specifies exactly which equities (companies, sectors or regions) and in what proportions they are held. This provides transparency since investors can see the precise make-up of the target asset allocation. It enables technology-driven rebalancing, ensuring the portfolio remains aligned with its target weights over time.
One of the key things to look for in your managed accounts technology is how to get commonality in your model structure. If a model is a target asset allocation with many assets in it, for example, 50 assets with weightings that total 100%, then making a top-down allocation change affects all of them. If you change the overall allocation from 40/60 to 39/61, all 50 asset weights must adjust to reflect that 1% top-down shift. That is not going to be that efficient when you look to scale that out, so often you want to think about what is the lowest building block that you want to hold your models. That may be geared around external model managers or in traditional stockbroking type businesses where you have your own research departments, they are the quants group that makes the decisions about what should be invested in and what weights. You look to put these things together so that when you make a change you make it at the one low level and it has a big ripple up effect. Those are some of the things you would expect to see technology helping with in a MDA business model. The key thing here is that we are looking to either pass the responsibility to the people with the expertise, for example, the research department or the external manager makes the choice of the model, or it allows us personalisation at scale.
Automated rebalancing and compliance integration
Automated rebalancing supports compliance by ensuring portfolios consistently reflect the agreed target allocation and investment mandate. It also eliminates manual error, streamlines order generation and allows advisory businesses to scale efficiency by reducing manual workload.
While manual order placement is possible in non-discretionary models, automated rebalancing provides efficiency and coupled with detailed asset data means that minimum order sizes, holding sizes etc can be used to ensure that execution costs are introduced into the portfolio through excessive order churn
In manual or advisory models, advisers place individual orders to realign portfolios as systems typically only know the top-level allocation (e.g. 30% equities, 70% bonds). Without individual asset-level models, the system cannot determine what specific assets to trade. Automated rebalancing becomes possible only when the target model defines allocations down to the individual assets, enabling systems to calculate and execute precise orders automatically.
In managed discretionary accounts, the systems can automatically detect when a portfolio deviates from the model and generate all necessary orders for realignment, without human intervention or client approval. In non-discretionary (advisory) accounts, automation can still propose those orders, but they require the client’s approval before execution. In either model with integrated OMS/EMS technology these orders can then be managed through to execution.
Technology differences between SMA and MDA models
While the expansive use of SMAs as a vehicle to service the adviser market has driven FUM growth, a key part of the attraction of MDAs is the flexibility they offer to advisers to provide more service-like offerings to their advice clients than are generally available from platform-based products/SMAs. which also do not provide the level of personalisation of managed accounts technology.
SMA providers focus on managing the target asset allocation and issuing the product, often relying on third-party platforms for client onboarding and order placement which limits their automation capabilities.
MDA providers offering a service rather than a product, tend to manage more of the client-level operations themselves, necessitating more robust internal technology for personalisation. Sophisticated MDA technology can encompass SMA functionalities, but SMA-only technology is operationally inefficient for highly personalised services.
Each MDA arrangement between a client and adviser is unique. It’s not like a registered scheme or SMA where everyone’s in a single product. Each client, even if they are managed in accordance with the same model, has a unique relationship. That gives rise to some really significant differences in the opportunities that MDAs provide, driven largely by a technology approach.
Specialist managed accounts technology presents a significant opportunity to utilise the flexibility that MDAs offer, allowing advisers to differentiate the service and customisation capabilities of MDAs from the one-size-fits-all product characteristics of so many SMAs. Often private wealth clients expect their adviser to be able to support all investment types, multiple tax structures, and custody, HIN or offshore assets, and MDA services make managing this practical and scalable. To bring such a service to the market requires complexities to be enhanced with as much technology-enabled integration as possible to make it effective and efficient.
Business impact and ROI
Revenue enhancement
In a transactional revenue model, income comes solely from transaction costs. This model leads to “lumpy” revenue as clients only transact when markets are rising. In a service-based model, a percentage of the portfolio’s value is charged on an agreed period basis, ensuring recurring revenue regardless of market fluctuations or transaction volume.
Operational efficiency gains
Managed account technology enables advisers to service more clients by optimising the client-to-target model ratio. If all clients use the same target asset allocation, an adviser can manage more clients. However, sophisticated technology allows for personalisation by applying individual client-specific constraints or overrides against a standard model, meaning an adviser can manage a personalised client experience without creating a new model for each client, thereby improving scalability.
If we look at more traditional advice giving businesses, metrics were based on how high you could get the adviser to client ratio. Of course, you could drive that number higher, but it came at the expense of effectively standardising the client portfolio. If an adviser just put everyone into a SMA they would be able to have a much higher ratio than if they had a lot of personalised portfolios. An efficient business was one where both the adviser to client ratio count and the amount of personalisation were both increasing. Ultimately, sooner or later, the ratio and personalisation plateau, as the limiting factors are the nature of the advice business model and the adviser themselves.
The discretionary type service model can achieve a higher starting ratio and the ability to increase that and the personalisation well in excess of the traditional advisory model. For the business metrics, the ratio patterns still apply, but you should be able to extend your adviser to client ratio and actually be able to support a far greater amount of personalisation in the portfolio services you are offering. The ratio of model portfolios (targets) to client portfolios is an additional business metric that should be used in discretionary accounts. For example, a 1-to-1 ratio is a poor efficiency metric, typically because of poor technology.
Highly efficient MDA models improve implementation timing by streamlining the process from model change to portfolio execution, reducing the time from days to minutes or hours. This efficiency allows for faster asset adjustments after market announcements, potentially leading to greater gains compared to advisory models where client approvals cause delays. While the core benefit is operational efficiency, these models also yield multiple positive outcomes, including better client results.
Because Myriad has so many modules and so many different user interfaces, organisations have the ability to move processes directly to the origination point user. This not only saves operational time, if done well, it can remove risk because typically re-keying information is removed.
Premium pricing capabilities through personalisation
While personalised portfolios may warrant slightly higher fees, the main advantage of models such as MDAs and SMAs lies in their operational efficiency. This efficiency, supported by technology, allows advisers to serve more clients and grow revenue without a corresponding rise in costs, as many operational expenses remain fixed.
Implementation planning
Technology integration considerations
There are significant challenges in technology integration within financial services. Software systems have piled up in the financial industry in an ad hoc way, with little thought for how they integrate.
The broad and complex nature of the technology domain is a major hurdle, making it unrealistic for any single vendor to cover all needs, so businesses often purchase multiple overlapping technologies. The situation we have now is that wealth managers and financial advisers might have up to a dozen applications on their desktop, or some consolidation in a web browser application but running multiple tabs for each system, that lack standardisation and don’t talk to each other. Different value propositions mean advisers may use different applications for adviser business needs and platform software for client needs. This involves a mix of solutions for advice preparation and delivery, alongside investment platforms where they’re executing the service and holding assets.
On the whole, platforms are still dominating the availability of information. The complexity of opening those systems up via integration capabilities means advisory firms are limited by what platforms want to enable. Even for the very small number of platforms that provide a modern technology interface, it is still a longer and more complicated integration process than it should be. While there are standards that exist as a technology layer, this doesn’t provide a business standard and the lack of industry standardisation and sufficient scale within the financial services sector, unlike in industries such as accounting, makes bespoke interfaces a common but costly necessity.
Duplicating data due to poor integration is a common problem in the industry, leading to significant operational challenges. FDC3 (Financial Desktop Consortium) is a messaging standard that provides interoperability between financial desktop applications/browsers. FDC3 helps prevent data re-keying across various systems like CRM, marketing and advice generation or note taking, ensuring data is created once and automatically propagated. This integration saves time by automating tasks, such as generating meeting summaries and client communications, directly from the tools used.
Change management factors
There’s no way to sugar coat it: technology implementation projects are often problematic and rarely just technical undertakings. They are complex, time-intensive projects that test an organisation’s decision-making, structure and its ability to manage changes. Businesses typically initiate technology change when the perceived problem of inaction outweighs the challenges of implementation. Many firms underestimate this complexity, overestimate anticipated outcomes and fail to account for the broader organisational shifts required to make new systems successful.
A common misstep is treating implementation as a “set and forget” exercise, rather than an ongoing process that evolves with the business. Projects frequently stumble due to limited management buy-in and insufficient attention to change management. Even with the rise of new technologies, such as AI, adoption can be patchy, reducing potential return on investment.
Much of the difficulty lies in human behaviour. Organisations often focus on what isn’t working in their current system while overlooking what is. In the rush to solve existing pain points, they sometimes adopt new technology that inadvertently creates bigger problems in areas that were previously stable.
Successful implementations depend on strong leadership, realistic planning and sustained management buy-in. Too often, management treats implementation as a one-time event, rather than an evolving process that demands ongoing attention. Change must be actively managed, measured and resourced. Without this, even well-designed solutions can fail to gain traction or deliver meaningful improvements.
Chelmer’s deep domain expertise and Myriad’s modular technology offer a proven framework for managing these challenges. Built on open architecture principles, Myriad supports incremental, phase implementation, minimising disruption and helping organisations evolve their systems over time. Our support for industry standards such as FDC3 ensures seamless compatibility and integration with existing platforms, enabling first to modernise while retaining the elements that already work.
Timeline and success metrics
Because Myriad is no code, personalised, modular software and built on open architecture principles, it can be implemented in stages and seamlessly integrated into business workflows. This approach enhances the longevity and functionality of existing technology while providing a clear pathway away from legacy systems.
For just over a decade, Chelmer has partnered with one of New Zealand’s leading wealth management firms to replace their legacy technologies, delivering greater automation, efficiency and improved functionality. The project established a strong foundation for further development using Myriad’s software components and open architecture to progressively replace additional systems and seamlessly connect internal and external platforms. The result was a highly integrated solution that simplified operations and reduced overhead.
Since implementing Myriad, the firm has achieved exponential growth in funds under management without a proportional increase in operational staff. This demonstrates a significant gain in efficiency and scalability. Advisors can now offer clients more sophisticated, tailored investment options with real-time visibility, strengthening the firm’s competitive edge.
Next steps framework
Assessment and planning approach
With deep domain expertise and a proven record of successful delivery, Chelmer understands what drives effective outcomes. We are committed to creating customised and personalised technology strategies in partnership with our clients. Our focus is on developing progressive, long-term partnerships that allow us to continually evolve and co-create solutions as needs change, ensuring sustained value and growth over time.
Buildind managed account capability through partnership
When a managed account services company set out to strengthen its managed discretionary account technology, the search for a partner who combined proven technology with a shared vision for innovation led to Chelmer. The combination of Chelmer’s modular Myriad solution and the organisations’ market and business analysis capability presented a compelling opportunity to demonstrate the true flexibility and potential of MDAs.
The company selected Chelmer because the team showed a genuine commitment to developing managed account capability. Chelmer’s existing technology provided an excellent foundation for enhancing and customising features to meet the specific requirements of MDA delivery, while also establishing a basis for future development. Few providers in the market offered such a robust and adaptable solution.
What made the partnership particularly effective was its progressive, collaborative nature. Both teams brought complementary strengths—Chelmer with deep technical expertise and the company with strong market insight and strategic understanding.
Together, this partnership created an environment of co-innovation, allowing both organisations to learn from each other, refine their approaches and successfully overcome the challenges that emerged along the way. The result is a managed account technology that not only delivers on current needs but is built for continuous evolution as the MDA landscape progresses.
Implementation roadmap overview
When it comes to implementation, Chelmer’s robust project management methodology has been refined and strengthened through successful implementations of Myriad for our clients.
- First, we develop a thorough understanding of your business so we can determine how we can add value.
- Then, we custom-configure a solution that meets your unique needs and processes.
- As the industry, your customers and your business grows, we evolve your solution; adjusting and re-configuring components, adding new features, and integrating new advances quickly and efficiently.
- We ensure Myriad integrates with your key suppliers and partners.
Our approach to partnering with clients means that we regularly share our technology and Myriad’s development roadmap. Client input is extremely valuable and is used to refine and focus our thinking and drive the R&D input to the software releases.
Our development roadmap continues to extend this advantage of distributed computing and applying the same concepts to the user interface, with the implementation of Micro UI’s. This provides ultimate flexibility in personalisation, and when coupled with technologies such as FDC3 and PWA’s, revolutionises the user desktop experience.
Resources for getting started
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