Read the full insight below or download the PDF version here.

 

A New Era for Mid-Tier Players

Historically, only the large global institutions had the technology budgets for resources and infrastructure to run advanced trading analytics combining petabytes of tick data, high-frequency backtesting models and enterprise-grade risk tools. Mid-tier firms such as regional asset managers, hedge funds, wealth firms and private banks were left competing with siloed systems, fragmented data and costly compliance obligations.

 

This dynamic has changed rapidly in recent years as global adoption of cloud-native analytics has accelerated at a pace and become an equalizer. 87% of financial services firms have increased cloud investment over the past two years, with 82% using hybrid/multi-cloud, and 91% advancing AI via the cloud, according to recent research (LSEG - Global Cloud Survey, July 2025 ).

 

Research also shows that the next wave of cloud innovation isn’t going to be about migrating infrastructure but monetising the intelligence from the data. (Read blog: From Migration to Monetization). Cloud-native analytics platforms are democratizing access to enriched, analytics-ready data and scalable models to get actionable, monetizable insight and product to market quickly.

 

  • Cloud analytics spend alone is set to grow from $39.88B in 2024 to $147B by 2030 (CAGR ~17%). Fortune Business Insights August 2025
  • 64% of wealth management firms report lower total cost of ownership from cloud migration, demonstrating faster ROI than in banking. McKinsey - Cloud adoption in financial services 2023

Today, mid-tier firms can access the same capabilities once reserved for Tier 1 players without prohibitive infrastructure costs or multi-year IT projects. This shift is more than just a technology upgrade, it represents a structural rebalancing of competitive advantage. Firms that embrace cloud-native analytics can “punch above their weight,” competing and even out-innovating larger rivals.

 

*LSEG Global Cloud Survey, July 2025

^ Fortune Business Insights, August 2025

87%

Of financial services firms that have increased cloud investment over the past two years*

82%

Are using hybrid/multi-cloud environments*

91%

Are advancing AI capabilities via the cloud*

$147B

Projected cloud analytics spend by 2030, up from $39.88B in 2024^

Three Competitive Pillars

1. Execution & Alpha

For hedge funds and asset managers, speed to insight is critical. Yet fragmented tick data sources and costly infrastructure slow access to data and insights. Cloud-native platforms change that by delivering curated, analytics-ready tick data and pre to post-trade models directly into quant workflows.

Capabilities unlocked:

  • Order book replay and market microstructure analysis
  • Benchmarking against VWAP/TWAP and implementation shortfall

 

  • Seamless integration into Python, R, and ML/AI environments (cloud or hybrid)
  • Intraday liquidity and slippage monitoring
2. Data Modernization

Regional and mid-tier asset managers often face ballooning data costs, rigid vendor contracts and escalating compliance demands. Analysts often spend more time wrangling data than generating investment insight and alpha.

Cloud-native data catalogs and marketplaces transform this reality by unifying fragmented datasets into governed, analytics-ready libraries. This enables advanced stress testing, correlation analysis, and ESG and factor modeling without costly re-platforming.

Capabilities unlocked:

  • Centralized data discovery across tick, reference and ESG data
  • Automated lineage and audit tracking to streamline compliance
  • Tiered storage models that reduce cost without reducing access
  • Direct delivery into portfolio optimization and risk system
3. Agility as an Advantage

Unburdened by sprawling IT estates, mid-tier firms can leapfrog directly into cloud-native operating models. This agility translates into lower cost-to-serve, faster time-to-market, and scalable compliance resilience.

Capabilities unlocked:

  • Hosted analytics (pre/post-trade, risk, liquidity) without upfront investment
  • Flexible adoption models: self-serve, hybrid, or fully outsourced
  • Modular delivery into client-preferred environments (SaaS, API, hybrid cloud)
  • Commercial flexibility: subscription, pay-as-you-go, or bundled analytics

 

Cloud-native analytics is the great equalizer. For hedge funds, asset managers, private banks and wealth firms, the barriers of scale and infrastructure have fallen. The winners will be those who adopt the fastest. Those who seize this opportunity will not just close the gap with the top-tier top tier firms but can even outpace them.

Seizing the Opportunity

RoZetta’s DataHex Platform delivers the modular, cloud-native foundation mid-tier firms need to compete with institutional-grade precision, without institutional-grade overhead.

Data Management Governed, centralized multi-asset data libraries

Marketplaces Internal and external catalogs to manage and monetize proprietary and third-party data

Analytics Pre/post-trade models, trading metrics, risk analytics, liquidity monitoring, backtesting and scenario replay

Indices & Portfolios Custom ETF and benchmark construction for thematic, ESG, and Smart Beta mandates

By liberating data’s potential, reducing cost, and minimizing operational risk, DataHex empowers Tier 2 and 3 firms to punch above their weight, trading smarter, managing risk with confidence and delivering differentiated client outcomes.

To learn more about how DataHex SaaS can unlock your potential for seamless collaboration, monetize data and drive innovation, visit us at rozettatechnology.com or email us at enquiries@rozettatechnology.com