The Top 10 Risks of Legacy Systems with today’s markets
Accio Analytics Inc. ● 27 min read
Legacy systems are holding businesses back. From skyrocketing maintenance costs to heightened security risks, outdated technology creates challenges that modern organizations can’t afford to ignore. Here’s a quick snapshot of the biggest risks:
- High Costs: Legacy systems consume up to 80% of IT budgets, leaving little room for innovation.
- Security Vulnerabilities: Older platforms lack modern safeguards, increasing the risk of data breaches.
- Inefficiency: Manual processes and disconnected data slow operations and inflate costs.
- Incompatibility with AI: Legacy systems struggle to integrate with modern tools like AI and automation.
- Staffing Challenges: Fewer experts are available to maintain outdated systems, driving up labor costs.
- Growth Barriers: These systems limit scalability and hinder market expansion.
- Poor Client Experience: Outdated technology leads to slow service and lost revenue opportunities.
- Missed Market Opportunities: Competitors leveraging modern platforms gain a significant edge.
- System Failures: Aging infrastructure increases downtime and operational disruptions.
- Regulatory Risks: Legacy systems struggle to meet evolving compliance standards.
Takeaway: Modernizing is no longer optional. Firms clinging to legacy systems risk falling behind competitors, facing increased costs, and exposing themselves to security and compliance risks. Transitioning to modern platforms can reduce costs, improve efficiency, and better position businesses for future challenges.
Leaving Legacy Systems Behind
1. High Operating Costs and Maintenance Issues
Legacy systems are notorious for driving up operational expenses. On average, organizations spend a staggering $30 million annually just to maintain each legacy system [5]. These outdated platforms consume as much as 80% of global IT budgets every year [5], leaving little financial flexibility for innovation or growth. What’s worse, the hidden costs tied to these systems tend to build up over time.
Impact on Operational Efficiency and Costs
The financial strain on IT budgets is immediate and significant. Between 60–80% of IT budgets are allocated to keeping legacy systems running [10], which severely limits funds available for strategic projects or competitive upgrades.
On top of that, outdated systems often rely on manual processes – like trade reconciliations – that result in higher labor costs and increased error rates [6]. For example, a study in the UK revealed that 48% of businesses lose three or more hours daily due to inefficient systems, costing them at least £28,000 annually [5].
Another growing challenge is the shrinking pool of experts familiar with outdated programming languages, making it increasingly expensive to hire skilled professionals [8]. One CEO from the asset management industry summed up the issue:
"We were running one of the established hosted solutions, and certainly had some challenges. The software was very complex since it had grown over a long time, which made it difficult to onboard new team members and some portfolio managers even retreated back to spreadsheets… This increased total cost of ownership and slowed enhancements, hampering our ability to provide the best return for our investors." [7]
The inefficiencies don’t stop there. Legacy systems are also energy hogs, requiring significantly more power and cooling than modern solutions [3][4]. In contrast, cloud-based systems have been shown to use 77% fewer servers, consume 84% less power, and rely on a 28% cleaner power mix [3][4].
Special licensing fees add another layer of expense. Many legacy platforms depend on discontinued software that comes with hefty licensing costs. For instance, in 2015, the US Navy spent at least $9 million just to safely operate Windows XP, a system long past its mainstream support period [3][4].
System downtime and failures pile on additional financial burdens. Three-quarters of IT teams managing legacy systems dedicate up to 25 hours a week to patch management alone [5], pulling resources away from more strategic, value-driven tasks.
As these systems age, maintenance costs continue to climb [8]. By 2025, it’s estimated that 40% of IT budgets will go toward managing technical debt [5]. Meanwhile, companies that transition to modern digital infrastructure are seeing productivity boosts of up to 40% compared to those sticking with legacy technologies [9].
The financial and operational toll of maintaining legacy systems underscores their growing vulnerabilities and the urgent need for modernization.
2. Security Weaknesses and Compliance Risks
Outdated systems in asset management firms open the door to cyberattacks and regulatory trouble. These older platforms often lack modern safeguards like multi-factor authentication, advanced encryption, and up-to-date threat detection. Without these defenses, financial data is left vulnerable, making it an attractive target for unauthorized access and exploitation [13].
The financial toll of these security lapses is staggering. In the United States, the average cost of a data breach has soared to $9.36 million [13]. Between 2014 and 2022, data breaches across local, state, and federal agencies collectively cost $26 billion [13]. For firms managing sensitive client investments and personal information, these figures highlight the scale of the threat they face.
The infamous WannaCry ransomware attack in 2017 serves as a stark example of what can go wrong. This attack hit over 200,000 computers across 150 countries, taking advantage of vulnerabilities in older Windows systems [12]. Financial firms running similarly outdated platforms are at risk of facing comparable disasters daily.
Take the ransomware attack in Columbus, Ohio, in July 2024, for instance. It compromised the data of 500,000 individuals, disrupted operations, and resulted in $7 million in associated costs [13]. Another example is a 2022 incident in New South Wales, where critical council data was encrypted, leading to significant financial and operational setbacks [11]. These breaches not only drain resources but also disrupt essential services.
Impact on Operational Efficiency and Costs
Legacy systems don’t just create security risks; they also slow down operations and drain resources. Globally, 36% of businesses report increased vulnerabilities and an inability to handle advanced cyber threats due to outdated technology [15].
Compliance becomes a nightmare when these systems fail to adapt to new regulations. Maintaining data accuracy and integrity becomes a challenge, complicating audits and client services. This often forces firms to rely on manual workarounds, which increase error rates and place additional strain on employees [14]. One expert summed it up well:
"Ageing systems can’t keep up with evolving regulations and cyber threats, exposing companies to security breaches, fines, and inefficiencies." [14]
Adding to the problem is a shrinking workforce. Over the past five years, the mainframe workforce has declined by 23%, with 63% of those roles remaining unfilled [15]. This shortage leaves fewer skilled professionals available to update security measures or ensure compliance with regulations.
Another major issue is the lack of automation in legacy platforms. Modern regulations often require automated reporting and machine learning–driven tools for surveillance and data validation. Without these, firms are stuck with manual processes that are both time-consuming and prone to mistakes. This creates a vicious cycle: as security gaps grow, compliance costs skyrocket.
In today’s interconnected financial systems, a weakness in one area can ripple through the entire network, exposing firms to regulatory penalties that could total millions. These cascading risks highlight the urgent need for modern systems to protect data and maintain operational efficiency.
3. Disconnected Data and Poor Reporting
Legacy systems often create silos, isolating data across different platforms and leaving businesses with fragmented information. These systems, designed for basic transactions, trap important data in separate databases, making it difficult for decision-makers to get a complete view of operations. The result? Outdated reports that fail to provide actionable insights[19].
This fragmentation directly affects data accuracy and governance. Asset managers frequently find themselves manually compiling spreadsheets, which not only wastes time but also increases the chances of errors. These inefficiencies disrupt workflows and significantly impact operational performance.
Impact on Operational Efficiency and Costs
When data is siloed, employees spend excessive time gathering, reconciling, and formatting reports instead of focusing on strategic analysis. This inefficiency extends to compliance reporting, where outdated systems require multiple manual steps to extract necessary data. These bottlenecks slow down processes and drain resources.
Modern asset managers could reduce their operational costs by 25 to 40 percent through AI-enabled solutions – if they have the right data infrastructure in place[20]. Firms sticking with disconnected legacy systems, however, face higher costs and lag behind competitors who are adopting more efficient, integrated platforms. The inefficiencies not only inflate expenses but also increase the risk of non-compliance, adding another layer of financial and operational risk.
Risk of Regulatory Non-Compliance and Security Breaches
Fragmented data doesn’t just slow operations – it also increases compliance risks. Poor reporting accuracy can lead to violations with hefty financial penalties. For example, the cost of non-compliance is, on average, 2.71 times higher than the cost of compliance[18]. When data is scattered across multiple systems, ensuring the accuracy and completeness of regulatory submissions becomes a daunting task.
Legacy systems also struggle to meet modern privacy regulations like HIPAA and GDPR[16]. Without integrated reporting capabilities, tasks like tracking data usage, monitoring access, and generating audit trails become cumbersome. This leaves organizations vulnerable to violations and significant fines.
| Compliance Framework | Potential Penalties |
|---|---|
| GDPR | Up to €20 million or 4% of annual worldwide revenue |
| HIPAA | Up to $1.5 million per violation per year |
| PCI DSS | $5,000–$10,000 per month |
Security risks are another major concern. Without real-time monitoring and automated reporting, legacy systems make it harder to detect breaches quickly. When incidents occur, fragmented data complicates efforts to assess the damage or generate accurate reports for authorities and clients, further amplifying the risks[16].
Ability to Integrate Modern Technologies (e.g., AI, Automation)
Legacy systems pose a significant barrier to adopting modern technologies like AI and automation. Their isolated nature prevents AI models from accessing the comprehensive datasets they need. Without high-quality, accessible data, even the most advanced AI models fall short[19]. Moreover, these systems weren’t designed to handle real-time data feeds or process unstructured information, both of which are critical for AI platforms[19].
Another challenge is the lack of infrastructure to support AI asset management. Legacy systems often lead to issues like version sprawl, retraining gaps, and inconsistent outputs, making it nearly impossible to implement effective MLOps frameworks for monitoring and governing AI models. This limitation not only disrupts current reporting but also stifles the deployment and management of AI tools.
Microsoft CEO Satya Nadella summed it up well:
"Businesses should embrace digital transformation, not only to survive – but also to thrive." [17]
Asset management firms that continue relying on outdated systems risk being left behind as competitors leverage integrated, AI-driven platforms to gain a competitive edge.
4. Cannot Use AI Analytics and Automation
Legacy systems don’t just slow things down – they actively block progress by making it nearly impossible to adopt AI and automation. These outdated platforms force companies to stick with manual processes while competitors race ahead with smarter, automated solutions. The problem? Legacy systems simply weren’t built to handle the immense data needs and processing power that modern AI tools require. This creates a bottleneck that holds companies back from advancing technologically.
Here’s a staggering fact: about 70% of Fortune 500 software is over two decades old. Meanwhile, generative AI is projected to unlock over $10.3 trillion in value by 2038 [21]. For companies stuck on legacy systems, the gap between potential and reality grows wider every year.
Impact on Operational Efficiency and Costs
Without access to AI-powered tools, companies face a ripple effect of inefficiencies that hit their bottom line hard. Tasks that could be automated remain manual, leading to higher costs and more errors. Research shows AI can boost operational efficiency by 10% to 15%, and in some cases, up to 40% to 50% [23]. But firms tied to outdated systems can’t tap into these benefits. Instead, they’re left grappling with high maintenance costs, the need for specialized skills, and the frequent downtime that legacy systems are infamous for [21].
The financial toll doesn’t stop there. Legacy technical debt – a term for the cost of maintaining outdated systems – costs the U.S. economy a jaw-dropping $1.52 trillion [22]. Add to that the inefficiencies of clunky interfaces, outdated processes, and limited automation, and the operational risks skyrocket.
Consider this: when legacy systems crash, they waste 22 minutes per event and cost businesses about $9,000 per minute [28]. These disruptions don’t just drain resources – they also prevent the uninterrupted operations that AI-driven automation could deliver. Beyond inefficiencies, these systems amplify security risks and exacerbate the data silos already discussed.
Ability to Integrate Modern Technologies (e.g., AI, Automation)
Legacy systems weren’t built for today’s technology. They lack the architecture to support AI and automation tools, struggle with real-time data processing, and often miss the APIs needed for seamless integration. On top of that, they can’t meet the computational demands required by machine learning models.
As Paz Gonzalez-Cutre, a Financial Crime Expert at ThetaRay, puts it:
"AI isn’t here to replace legacy systems; it’s here to work with them – and it’s doing so more effectively than ever." [24]
But without modern infrastructure, companies miss out on AI’s ability to analyze data in real time, predict problems, identify patterns, and automate decision-making. Some organizations have found success by modernizing strategically. For example, DCI (Data Center Inc.) partnered with Luby to revamp a core solution using modern design and UX technologies, cutting system response time by 25% and expanding services to new clients [27]. Similarly, Caliber, a credit company, shifted to a microservices architecture, boosting loan processing capacity by 35% and reducing operating costs by 20% [27].
Scalability and Adaptability to Market Changes
Legacy systems create roadblocks when it comes to scaling and adapting to fast-changing market demands. These platforms simply can’t keep up with increasing data volumes or the analytical needs of modern businesses.
This issue becomes even more pressing as consumer expectations shift. By 2030, AI-friendly consumers could drive 55% of consumer spending [22]. Companies stuck with legacy systems will struggle to deliver the AI-powered services that today’s customers expect.
The financial sector feels this pressure acutely. The International Data Corporation (IDC) predicts financial services will lead AI spending between 2024 and 2028, accounting for over 20% of global AI investments [25]. Yet, 75% of banks face challenges implementing new payment solutions due to outdated infrastructure [25], and 59% of bankers cite legacy systems as a major hurdle [25].
As Jacquelyn Thome, a Consulting Solution Architect at Presidio, explains:
"Artificial intelligence and machine learning allow IT engineers and admins to analyze more data in real-time… and also to allow some of that technology to do some unmanned decision-making for us." [26]
Organizations that modernize their systems can harness AI to make faster, more accurate decisions and automate processes. McKinsey & Company highlights the urgency of this shift:
"Using AI technologies can result in increased automation and, if the associated risks are accounted for, can often surpass human decision-making in terms of both speed and precision… AI can unlock up to $1 trillion of additional value for banks annually." [29]
For firms stuck on legacy systems, the risks are clear: falling behind competitors who use AI to offer faster, smarter, and more personalized services. Without modernization, these companies risk becoming irrelevant in a market that increasingly demands agility and innovation.
5. Staff Shortages and Skills Gaps
Legacy systems create a unique staffing challenge by narrowing the pool of candidates who are familiar with outdated technologies. As seasoned professionals retire, they take with them decades of institutional knowledge, leaving companies struggling to find replacements. On top of that, younger, highly skilled professionals often shy away from organizations still reliant on legacy systems, making it even harder to attract the talent needed to remain competitive in fast-moving financial markets. This talent shortage not only slows down system updates but also significantly increases costs.
Here’s a startling statistic: developers spend 42% of their time fixing legacy systems, which adds up to 104 days per year. In Japan, 40% of companies allocate a staggering 90% of their IT budgets to simply maintaining these systems [32][33]. This leaves IT professionals stuck in a cycle of maintenance rather than focusing on forward-looking projects that could drive innovation.
The real challenge isn’t just finding people – it’s finding the right people. Education and training programs today are heavily geared toward modern technologies, steering developers toward newer coding languages and frameworks that align with their career aspirations.
Impact on Operational Efficiency and Costs
Staffing shortages around legacy systems hit companies hard, affecting both their day-to-day operations and overall profitability. When qualified personnel are scarce, projects get delayed, and resolving issues takes longer than it should. Often, only one or two aging experts are left who truly understand these outdated systems, creating a critical dependency.
Relying on legacy systems also heightens risks around data protection and system maintenance. A lack of skilled staff makes it harder to secure and update these systems effectively [30]. And the financial burden doesn’t stop at salaries. A recent survey revealed that 70% of technical workers had multiple job offers when accepting their current roles [34]. To compete, companies are forced to offer premium wages to attract and retain the few specialists available, further driving up operational costs.
Diane Chaleff, product manager for Google Cloud’s office of the CTO, sums it up perfectly:
"Outdated technology forces us to work within its constraints, instead of doing what’s best for the business." [31]
Ability to Integrate Modern Technologies (e.g., AI, Automation)
The skills gap becomes even more glaring when companies attempt to modernize. Legacy systems not only require specialized expertise that’s increasingly hard to find but also demand entirely different skill sets to integrate modern technologies like AI and automation. This dual challenge leaves companies in need of both legacy system experts to keep operations running and specialists in new technologies to drive innovation.
The reluctance of top technical talent to work with outdated systems further complicates modernization efforts. For banks and other businesses, this makes it harder to attract the experts needed to thrive in today’s digital-first world [1]. The growing shortage of legacy system experts accelerates the urgency for app modernization, as maintaining these outdated platforms becomes unsustainable both financially and operationally [1].
Scalability and Adaptability to Market Changes
These staffing challenges don’t just impact daily operations – they also limit growth. Legacy systems create bottlenecks, making it nearly impossible for companies to scale efficiently. When only a handful of employees have the expertise to manage core systems, growth becomes constrained by human resources rather than market demand. This becomes especially problematic during periods of rapid change or expansion.
To break free from these constraints, companies need to rethink how they approach tech talent. Building an organizational culture that embraces continuous learning and change is essential [34]. Modernization doesn’t just solve the talent shortage; it also makes IT environments more appealing to top talent and allows companies to shift some of the heavy lifting to external IT vendors who are better equipped to manage these transitions [1].
6. Limited Growth and Expansion Problems
Legacy systems pose significant challenges for asset management firms looking to grow or enter new markets. A striking statistic highlights the issue: around 70% of the software used by Fortune 500 companies was developed more than two decades ago [21]. These outdated systems not only stall growth but also lead to higher operational costs, as explained below.
Impact on Operational Efficiency and Costs
When firms enter growth phases, legacy systems often turn into costly obstacles. The experience of a CEO from a $6 billion asset management firm illustrates this:
"We were running one of the established hosted solutions, and certainly had some challenges. The software was very complex since it had grown over a long time, which made it difficult to onboard new team members and some portfolio managers even retreated back to spreadsheets… This resulted high total cost of ownership and slow delivery of enhancements, which in the end impaired our ability to provide the best return for our investors." [7]
The complexity of maintaining and upgrading legacy systems drains IT budgets. Lengthy upgrade cycles consume time and resources that could otherwise be allocated to growth initiatives. A Head of Technology at a $9 billion asset management firm shared:
"With an on premise system, upgrades take a considerable amount of time and effort, and generally we upgrade annually – meaning we have to wait a long time for software improvements… It also means we have to spend valuable resources on non-core activities such as hosting and IT maintenance." [7]
Ability to Integrate Modern Technologies (e.g., AI, Automation)
Legacy systems also stifle the adoption of modern technologies like AI and automation, which are projected to generate over $10.3 trillion in economic benefits by 2038 [21]. These systems often struggle with compatibility issues, data quality challenges, and performance bottlenecks [19] [35]. While companies that embrace AI and automation can save over $2 million [36], legacy platforms make achieving these savings far more difficult. This technological lag further hampers firms’ ability to adapt to fast-changing market conditions.
Scalability and Adaptability to Market Changes
Outdated systems severely limit a firm’s ability to scale and adapt. Unlike modern cloud-based solutions that offer seamless scalability, legacy platforms require months of planning for changes that newer systems can handle in a matter of days or weeks [21]. This lack of agility can be a major setback when markets shift quickly.
Additionally, these systems often fail to meet new privacy regulations and require longer timelines to implement compliance measures [16]. Interoperability issues further constrain scalability, while the high cost of maintaining aging infrastructure diverts funds away from modernization efforts. For example, Microsoft Dynamics GP will no longer be supported after December 31, 2029, leaving firms reliant on this software with limited options [2].
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7. Bad Client Service and Lost Revenue
On top of the operational inefficiencies and growth challenges discussed earlier, poor client service can severely impact revenue. Outdated legacy systems not only disrupt workflows but also push asset management firms into relying on time-intensive manual processes, leaving advisors stretched thin.
Impact on Operational Efficiency and Costs
Advisors using outdated systems spend a staggering 60–70% of their time on tasks that don’t directly generate revenue. This inefficiency costs firms an average of $3.6 million annually and slashes productivity by 25% [37][38]. Instead of focusing on building client relationships or offering strategic financial advice, advisors are bogged down by manual workflows and inconsistent processes. The lack of standardization across these systems leads to uneven client experiences and slower problem resolution, further damaging the firm’s reputation.
Challenges in Adopting Modern Technologies (e.g., AI, Automation)
Today’s clients expect more than just basic financial advice – they want comprehensive, tech-enabled solutions. For example, high-net-worth individuals often hold less than 45% of their wealth in liquid assets, with the remaining 55% tied up in illiquid investments that traditional systems struggle to track [37]. Without modern tools like AI and automation, advisors can’t provide the detailed portfolio insights these clients demand. This gap forces many clients to turn to competitors who offer better digital experiences. In short, firms that fail to upgrade risk both operational inefficiencies and losing client trust.
Struggles with Scalability and Adapting to Market Changes
Modern clients expect frequent, personalized communication [37]. Legacy systems, however, often fall short when it comes to supporting timely and consistent interactions – especially as a firm’s client base grows. And the stakes are high: 86% of customers are willing to pay more for an excellent experience, while 73% rank customer service as a critical factor in their decision-making [38]. A single bad review can cost a business up to 22% of potential customers, and inefficiencies can drain as much as 30% of annual revenue [32].
Security is another area where outdated systems fail. With the average cost of a data breach hitting $4.45 million in 2023, firms handling sensitive financial data are prime targets for cyberattacks like phishing and ransomware [38]. Alarmingly, 60% of small businesses impacted by such attacks shut down within six months [37]. For wealth management firms, these vulnerabilities highlight the urgent need for secure, modern platforms that can safeguard client trust while delivering a seamless experience.
8. Missed Opportunities and Falling Behind Competitors
Relying on outdated systems can seriously limit a company’s ability to seize new market opportunities and stay ahead of the competition. In a world increasingly driven by data, firms using legacy technology are at a clear disadvantage.
Impact on Operational Efficiency and Costs
Data-driven companies are 23 times more likely to acquire customers, six times more likely to retain them, and 19 times more likely to be profitable [39]. Yet, legacy systems often fail to provide the real-time financial and operational insights needed for quick, informed decision-making [2]. This lack of timely data delays critical actions. While competitors using modern platforms can make swift investment decisions, firms stuck with outdated systems often operate in silos, relying on manual data reconciliation. This fragmented approach slows their response time in fast-changing markets [40]. The contrast between these inefficiencies and the streamlined agility of modern platforms is striking.
Challenges in Integrating Modern Technologies (e.g., AI, Automation)
Legacy systems also act as a barrier to adopting new technologies. Their rigidity can prevent teams from modernizing processes to meet evolving customer expectations and market demands [7]. On the other hand, modern, cloud-native tools enable teams to analyze performance and risks more efficiently, offering real-time reporting that supports smarter, faster decision-making [7]. These tools not only enhance accuracy but also allow businesses to evolve alongside technological advancements.
Scalability and Adaptability to Market Changes
In today’s digital-first environment, legacy systems create significant hurdles [39]. Fragmented data and inefficiencies increase operational risks, making firms more vulnerable to errors, data breaches, and even compliance failures [40]. When markets shift or new regulations emerge, companies tied to outdated systems often struggle to adapt quickly. Meanwhile, modern platforms give businesses the flexibility to pivot strategies and seize opportunities without delay. This growing gap between firms using legacy systems and those leveraging modern technology makes it increasingly difficult for the former to attract new clients or retain existing ones. Modern platforms not only eliminate these inefficiencies but also position businesses for growth and sustained competitiveness.
9. Higher Risk of System Failures
Legacy systems often set the stage for critical system failures, especially during high-pressure moments when businesses can least afford downtime. These older platforms weren’t built to handle today’s demanding workloads, making them a risky foundation for modern operations.
Impact on Operational Efficiency and Costs
The reliance on outdated technology comes at a steep cost to both efficiency and finances. Here’s the reality: more than 66% of enterprises still depend on aging hardware for core operations, and over 60% use legacy systems for customer-facing tasks [28]. This dependency creates glaring vulnerabilities. When these systems fail, employees can lose up to 22 minutes of productivity due to downtime [28].
On top of that, the rigid architecture of legacy systems makes scaling – both horizontally and vertically – a challenge. This leads to performance bottlenecks and sluggish response times, especially during peak periods. Outdated software and neglected maintenance only add to the risk of failure [30].
Scalability and Adaptability to Market Changes
Scaling with legacy systems is another uphill battle. Their outdated hardware and inflexible design often result in poor performance during high-traffic periods – an issue that modern cloud-native platforms are specifically designed to avoid [30][41]. This inability to scale effectively not only strains IT resources but also drives up long-term operational costs [41].
Modern cloud-native platforms, on the other hand, offer flexible scaling and stability even during peak usage [30]. They eliminate the need for constant on-premises hardware upkeep and support agile development for new features. Additionally, these platforms use standard integration protocols, making it easier for systems to communicate seamlessly and enabling quicker decision-making in dynamic market conditions [30]. While legacy systems struggle to keep up with the performance demands of today’s business environment [41], modern platforms can handle high transaction volumes without faltering. This reliability gap leaves companies using outdated technology at a serious disadvantage, especially in fast-changing markets.
10. Cannot Meet Future Rules and Market Changes
Legacy systems don’t just lag in performance – they also fail to keep up with shifting regulatory requirements and market dynamics. Asset management firms relying on outdated technology find it increasingly hard to adapt to new compliance standards and seize emerging opportunities. This creates a ripple effect, heightening operational, security, and strategic risks.
Risk of Regulatory Non-Compliance and Security Breaches
The regulatory environment in asset management evolves quickly, with agencies like the SEC and FINRA issuing frequent updates. Legacy systems, built in a different era, simply lack the flexibility to keep up. These systems rely on outdated reporting methods, which regulators often scrutinize [42][20]. When firms can’t deliver accurate, timely data, they resort to manual fixes – introducing errors and compounding compliance risks.
Take the growing emphasis on data privacy laws and regulations governing digital client interactions. Firms with legacy systems have struggled to adjust, while competitors using modern technology have adapted seamlessly to meet these new standards.
Impact on Operational Efficiency and Costs
Maintaining legacy systems isn’t just cumbersome – it’s expensive. Some firms spend up to 78% of their IT budgets just keeping these outdated platforms running, leaving little room for innovation or quick adaptations [42][20].
The financial toll doesn’t stop there. Operational costs tied to legacy systems can be ten times higher than those of firms operating on modern infrastructure [42]. These inefficiencies slow down product launches and updates, eroding both competitiveness and profitability.
One striking example comes from a leading asset management firm managing over $1 trillion in assets. Before modernizing, they allocated 80% of their tech budget to maintaining legacy systems. After transitioning to cloud-based platforms, they flipped the script – now planning to dedicate 70% of their budget to business transformation by 2025 [20].
Ability to Integrate Modern Technologies (e.g., AI, Automation)
Modern technologies like AI and automation offer powerful tools for growth and efficiency – but only if a firm’s infrastructure can support them. Legacy systems, often isolated and rigid, make integrating these tools nearly impossible [20][44].
This technological disconnect puts firms at a serious disadvantage. While competitors use AI to spot market trends and automate compliance tasks, firms stuck with legacy systems remain bogged down by manual processes and outdated analytics.
The workforce readiness gap only amplifies the issue. Although 80% of asset managers recognize the importance of technologies like AI and big data for driving revenue, only 39% are actively preparing their teams to use them [44]. This disconnect between awareness and action creates a dangerous gap, leaving firms ill-equipped to leverage new tools.
Scalability and Adaptability to Market Changes
Legacy systems’ inability to scale and adapt further threatens long-term success. The asset management market is evolving rapidly. For instance, since March 2021, $60 billion in assets have shifted from mutual funds to ETFs, driven by investor demand for more flexible, cost-effective options [43]. Firms relying on outdated systems struggle to keep up with these trends.
The rigid, monolithic design of legacy platforms makes it hard to launch new products, manage higher transaction volumes, or expand into new markets. This lack of scalability leads to system bottlenecks and diminished client service – right when firms need to act quickly to capture growth opportunities [42][20].
The numbers paint a stark picture: 44% of wealth managers admit their technology is outdated, and 31% say it’s no longer fit for purpose [45]. Firms that fail to adapt risk losing clients to nimbler competitors and missing out on new revenue streams. In today’s fast-paced markets, this kind of inflexibility isn’t just a nuisance – it’s a serious threat to survival.
Legacy vs Modern Systems Comparison
Legacy and modern systems differ in critical areas like cost, security, scalability, and integration – factors that significantly influence asset management. As previously discussed, the increasing costs and security risks tied to legacy systems make modernization an urgent priority.
Consider this: A Deloitte study found that 55% of IT budgets are allocated to maintaining legacy systems, with each system costing as much as $30 million annually. This leaves a mere 19% for innovation, while technical debt is projected to consume 40% of budgets by 2025 [46][5].
The U.S. Federal government provides a striking example of the problem. In 2019, 80% of its IT budget went to operating and maintaining aging legacy systems. Yet, retiring these systems could slash hardware and operational costs by a staggering 65% [5].
Here’s a side-by-side look at how legacy and modern systems stack up:
| Aspect | Legacy Systems | Modern Systems |
|---|---|---|
| Maintenance Costs | Constant patches, bug fixes, and hardware upgrades, leading to rising and unpredictable expenses | Predictable, often lower costs due to cloud-based infrastructure and automated maintenance |
| Security | Outdated encryption and compliance measures, resulting in higher breach risks | Advanced security with zero trust models and AI-driven threat detection, reducing security expenses |
| Scalability | Struggles to handle growing workloads, causing performance issues and lost revenue | Built for elasticity, ensuring smooth scaling with demand |
| Integration | Difficulties connecting with modern APIs, CRMs, and cloud services; often requires workarounds | Seamless integration with modern tools, enabling faster innovation |
Modernizing infrastructure isn’t just about reducing costs – it’s about driving growth and efficiency. For instance, 66% of business leaders are actively migrating users and data off legacy systems, and organizations that modernize their infrastructure report 2.5 times higher revenue growth [30].
Real-world examples bring this to life. CVS Health, for example, transitioned from outdated systems to a scalable, open-source content platform. This move boosted its agility and flexibility [30]. Another case is the City of Lakeland, Florida, which adopted modern Enterprise Asset Management software to better serve its 120,000 residents [47].
"We were looking for a company that was mobile, flexible and allowed us to transition from an antiquated system. We have gained leaps and bounds by moving to this application."
– Lisa McCall, Systems and Applications Manager, City of Lakeland, FL [47]
Modern systems also streamline workflows, eliminating manual fixes and duplicate data entry – problems that plague legacy platforms. Additionally, modern solutions come equipped with advanced security measures, addressing vulnerabilities that older systems can’t handle [30].
The advantages go beyond operational efficiency. Legacy systems often lack robust encryption, leaving them exposed to risks, whereas modern platforms implement comprehensive security protocols. The cloud-based nature of modern systems further simplifies IT management, enabling seamless integration and smarter data sharing [30].
Ultimately, the choice between legacy and modern systems is about more than just technology; it’s a strategy for sustainable growth. Sticking with outdated systems means higher costs, greater security risks, and inefficiencies – making modernization a necessity, not an option.
Conclusion
Legacy systems pose risks that asset management firms can no longer afford to overlook. These outdated platforms drain up to 80% of IT budgets, with technical debt expected to account for 40% of these budgets by 2025 [5].
The inefficiencies caused by these systems translate directly into lost time and money. Studies reveal significant daily productivity setbacks, and 90% of IT decision-makers acknowledge that legacy systems obstruct digital innovation and operational progress [5].
Security vulnerabilities add another layer of urgency. High-profile breaches tied to outdated systems have exposed millions of records and resulted in hefty regulatory penalties [5].
Given these challenges, adopting modern, adaptable solutions is no longer optional – it’s essential. The future lies in modular, API-driven platforms that allow firms to modernize incrementally, without disrupting existing operations. Asset management companies need systems that integrate smoothly with current infrastructure while offering real-time insights and advanced analytics. Accio Quantum Core addresses these demands with its microservices-based architecture, enabling firms to update their systems step by step, avoiding costly and disruptive overhauls.
The industry’s evolution depends on solutions that tackle inefficiencies, bolster security, and provide the scalability required to keep pace with modern demands. It’s time to leave legacy systems behind and embrace tools designed for today’s challenges.
FAQs
What are the biggest financial risks of relying on legacy systems in today’s financial markets?
Relying on outdated systems in today’s fast-moving financial markets can be a costly gamble. Big institutions risk losing as much as $1.5 billion in revenue because of aging technology and sluggish integration processes. On top of that, maintaining just one legacy system can cost more than $30 million a year, adding up to an industry-wide expense that surpasses $1 trillion annually.
These hefty expenses stem from operational inefficiencies, increased risks related to regulatory compliance, and missed chances to leverage modern tools like AI-powered analytics and automation. Over time, these issues chip away at profitability and make it harder for firms to stay competitive in an ever-evolving market.
How do legacy systems create security and compliance challenges for businesses?
Legacy systems often fall short when it comes to modern security measures, making them prime targets for cyberattacks. Without regular updates or vendor support, these systems frequently miss out on essential security patches and fail to keep up with current encryption standards. This outdated technology can leave significant gaps in a company’s cybersecurity defenses.
On top of that, legacy systems can create compliance headaches. As regulations evolve, older systems may struggle to meet updated requirements, putting businesses at risk of non-compliance. Their lack of compatibility with modern tools also makes it harder to adopt advanced security solutions, leaving companies more vulnerable in today’s fast-moving, data-driven world.
How can companies modernize outdated systems to address risks and stay competitive in today’s financial markets?
To bring older systems up to speed, businesses can take a step-by-step approach. Options like replatforming, refactoring, or rehosting can help minimize disruptions while transitioning to modern technologies. It’s also important to set clear goals for the modernization process and use flexible architectures that align with the company’s specific needs.
Working with specialists and prioritizing scalable solutions can reduce operational risks, strengthen security, and create a solid foundation for AI-driven analytics. These updates not only boost efficiency but also help companies stay competitive in today’s fast-moving, data-focused markets.
