Artificial intelligence (AI) is reshaping financial services at breakneck speed. From fraud prevention and underwriting to portfolio modeling and customer personalization, AI is no longer just a futuristic concept; it is already reshaping client expectations and competitive dynamics. Yet despite the excitement, many mid-market firms wrestle with a practical question: how do we begin?
The answer lies not in skipping straight to complex models, but in first building a foundation of disciplined data and analytics. The Innovation Vista Financial Services Analytics Maturity Survey provides a unique lens into how firms across banking, lending, wealth management, insurance, and payments are progressing. Its findings make clear: success in AI requires first stabilizing and optimizing data and business intelligence (BI), and then pushing into monetization where advanced analytics and AI deliver measurable ROI.
Survey Insights: Where Financial Services Stands
The survey tracks maturity across three domains (Data, BI, and AI) using three categories of competence: Stabilized, Optimized, and Monetized.
- Stabilized reflects the basics: central repositories, structured refreshes, dashboards, and pilots.
- Optimized reflects governance and discipline: catalogs, literacy programs, semantic layers, MLOps practices.
- Monetized reflects measurable ROI: enterprise-wide master data, predictive analytics, production AI, and customer-facing value.
Across all three domains, Financial Services emerges as a leader among mid-market industries. By 2025, stabilization and optimization are essentially universal, and monetization rates in both BI and AI are 10–15 points higher than mid-market averages. Financial Services firms who haven’t progressed on this curve are running huge risks for their future survival.
- Data: By 2025, virtually all firms have stabilized and optimized their data, and monetization surpasses 55% even in $10–$100M companies, exceeding 80% in $250M–$1B organizations. Data products and enterprise master data are becoming revenue drivers, embedded in risk models, segmentation, and regtech.
- BI: By 2025, BI monetization sits at 54% for $10–$100M firms and reaches 80–90% in larger companies. Predictive analytics for fraud detection, credit risk, and portfolio modeling are being embedded directly into client offerings.
- AI: Here the leadership edge is even more striking. By 2025, 73% of $10–$100M firms have stabilized AI pilots, nearly half have optimized practices, and one in five are monetizing. Larger mid-market companies push further, with 40% monetizing AI at $250M–$1B and 60% at $1B+.
These numbers confirm two truths: Financial Services is ahead of the curve, and yet monetization remains the key hurdle. Stabilization and optimization are table stakes; monetization separates leaders from laggards.
Elevating Your Treatment of Data
The survey shows that stabilization and optimization of data are nearly universal in Financial Services. But moving into monetization requires more than technical infrastructure; it requires cultural and strategic commitment.
Stabilization begins with a central data warehouse or lake, scheduled ETL processes, and a starter dictionary. Optimization brings daily refreshes, glossaries, and master data management (MDM). Monetization takes the next leap: enterprise-wide MDM, cross-functional data products, and measurable ROI.
Financial Services firms that have achieved monetization report turning data into direct revenue streams. Examples include embedding risk models into product pricing, or using enriched segmentation to drive personalized wealth management offerings. The survey confirms that monetized data is not an aspiration – it is already differentiating competitors.
Why BI Deserves Equal Attention
If data is the foundation, BI is the proving ground. According to the survey, BI monetization in Financial Services is significantly ahead of other sectors. Stabilized firms have dashboards and instrumentation; optimized firms add governance, KPI ownership, and data literacy. Monetized firms push further, embedding predictive analytics, scenario planning, and automated responses directly into workflows.
By 2025, more than half of $10–$100M firms and the vast majority of larger firms report monetized BI. These organizations aren’t just reporting history – they are using BI as a competitive weapon. Predictive credit risk models inform lending decisions. Fraud detection dashboards proactively flag anomalies. Scenario planning tools shape portfolio strategies.
For employees, BI demonstrates the payoff of disciplined data entry. Sales teams see cleaner pipelines. Operations teams get earlier warnings. Relationship managers access richer client views. The survey confirms that BI both builds confidence and motivates adoption – critical steps to position the organization for successful AI.
Identifying Impactful AI Use-Cases
The survey shows that AI is stabilizing and optimizing quickly, but monetization is still concentrated in fewer firms. Those that succeed choose use-cases aligned with revenue and client value.
Stabilized AI means pilots, prompt libraries, and basic guardrails. Optimization involves MLOps practices, model registries, and evaluation frameworks. Monetization is the payoff: production AI delivering measurable ROI. By 2025, 20% of smaller mid-market firms and up to 60% of billion-dollar firms are monetizing AI, with use-cases including:
- AI-driven underwriting and risk scoring.
- Fraud prevention systems integrated into payments.
- Customer service chatbots reducing support costs.
- Algorithmic trading and portfolio optimization.
One company spotlighted in the survey illustrates this trajectory. A mid-sized payments provider stabilized by consolidating transaction data, optimized with BI dashboards for anomaly detection, and then monetized by embedding AI-driven fraud detection into a premium merchant service. What began as an internal control became a revenue-generating product, redefining the company’s competitive position.
This example embodies the survey’s broader message: monetization means moving beyond efficiency to embed AI in offerings that clients value and will pay for.
The Role of Senior Leadership
The survey reinforces a familiar truth: leadership commitment is the differentiator. Firms at the monetization stage consistently reported that CXOs championed data and AI as strategic priorities. In basic or early developing stages in other industries, leadership indifference was the most cited barrier, but in Financial Services, the expectation is already higher.
For firms aspiring to move from optimized to monetized AI, leadership must push adoption beyond pilots. It requires prioritizing ROI-focused projects, aligning investments with strategy, and ensuring governance keeps pace with regulation. Without top-down reinforcement, monetization stalls.
Calming Staff Fears, and Energizing Them with Delivered Value
The survey highlights that workforce adoption is critical. Employees must be convinced that AI is not a threat but a partner. Stabilized and optimized AI requires rigorous data entry, model monitoring, and adoption of new workflows. Firms that succeed balance this with clear employee benefits:
- Sales reps receive better-qualified leads.
- Compliance staff reduce manual checks through automation.
- Relationship managers access predictive insights for cross-sell opportunities.
The quid pro quo is clear: staff are asked to take more responsibility for data accuracy, in exchange for tools that make their roles easier and more impactful. When AI helps staff succeed, adoption accelerates.
The Highest-Leverage Use of Outside Expertise
Financial Services is leading the mid-market in analytics maturity, but the pace of change is staggering. That means it may be one of the first industries which squeezes out companies who are late to innovate. Even survey leaders admit difficulty keeping up with evolving AI tools, regulatory expectations, and competitive threats.
This is why outside expertise matters. Independent advisors bring cross-industry perspective, vendor-neutral guidance, and proven frameworks. For midsize firms, affordability is the challenge, and that is why offerings likeour CIO IQ® service prove valuable. They provide access to enterprise-level IT and AI strategy leadership at a fraction of the cost of a full-time executive, helping firms accelerate from optimization to monetization.
Getting Started
The Financial Services Analytics Maturity Survey makes one thing clear: stabilization and optimization are already table stakes. The real differentiator is monetization – embedding Data, BI, and AI directly into products, services, and revenue models.
For firms still in earlier stages, the path is clear:
- Elevate data discipline from stabilized to optimized.
- Expand BI beyond dashboards into predictive monetization.
- Choose AI pilots with measurable ROI, then scale into production.
Financial Services is the benchmark sector, but competition is fierce. Firms that move quickly from optimization to monetization will continue to set the pace. Those that hesitate risk losing ground to peers already compounding the benefits of monetized AI.
Among all areas of business, AI is changing the fastest and carries both the highest risks and rewards. For financial services leaders, outside guidance can accelerate this journey, ensuring not just stabilization and optimization, but the leap into monetization. With the right strategy and support, firms can “Innovate Beyond Efficiency®” and turn AI into a competitive weapon.
