Survey Reveals Why 77% of Financial Leaders Are Going Big on Decision Intelligence This Year

The financial services sector has spent the better part of a decade automating its decision-making processes. Loan approvals, fraud checks, and credit scoring are all increasingly handled by algorithms rather than humans. But a growing consensus among industry leaders suggests that automation alone is no longer enough. The next frontier is not just making decisions faster, but making them smarter, continuously, and with full transparency.

A global survey of senior financial services decision-makers by Provenir found that 77% now consider decision intelligence (the practice of using AI to not only execute decisions but to learn from their outcomes and optimise in real time) as a strategic priority for the next two to three years.

That figure signals more than passing interest. It points to a fundamental rethinking of how financial institutions operate.

From Autopilot to Co-Pilot: What Has Changed

For years, the standard approach to AI-powered decisioning followed a predictable rhythm. Build a model, deploy it, review its performance every quarter, update it if needed. Governance and explainability were handled as separate workstreams, often by different teams entirely.

Decision intelligence collapses that cycle. Instead of periodic reviews, it creates a continuous feedback loop where decisions are executed, outcomes are measured, lessons are drawn, and strategies are refined without waiting for the next scheduled audit. Governance and transparency are embedded in the platform itself, rather than bolted on as afterthoughts.

The shift is already well underway. According to the survey data, 75% of financial institutions are actively collaborating on AI-driven decision intelligence initiatives, with a further 18% exploring partnerships. And when it comes to budget allocation, 60% of respondents confirmed they plan to invest in AI or embedded intelligence for decisioning this year, making it their single largest investment priority.

The Features That Matter Most to Financial Leaders

Not all AI capabilities carry equal weight in the eyes of senior decision-makers. When asked which features deliver the most value, respondents consistently pointed to four areas.

First, 51% highlighted the ability to use generative AI for natural language queries, allowing business users, compliance teams, and executives to interrogate decisioning data conversationally, without needing technical expertise or SQL knowledge. This democratisation of insight access is reshaping who participates in data-driven decision-making within large organisations.

Second, 49% cited real-time decisioning across customer touchpoints. Speed and consistency across channels reduce operational friction and improve the customer experience, particularly in sectors like lending and payments where milliseconds matter.

Third, transparency and explainability of AI models ranked as a top concern for 50% of respondents. With regulators worldwide tightening expectations around algorithmic accountability, financial institutions need AI systems they can defend under scrutiny, not black boxes that produce answers without showing their working.

Fourth, integration with existing systems emerged as a practical priority for 47% of those surveyed. Most institutions are not in a position to rip out their technology stack and start again. Decision intelligence platforms need to work alongside legacy infrastructure, not demand its wholesale replacement.

The Payoff: Efficiency, Accuracy, and Speed to Market

The business case for decision intelligence rests on tangible outcomes rather than theoretical promise. Among those surveyed, 62% pointed to operational efficiency gains: fewer manual reviews, faster processing, lower costs, and greater consistency across decisions. A further 58% cited improved accuracy of models and strategies, driven by the continuous learning loop that allows systems to refine their own performance over time.

Better customer experience was highlighted by 52% of respondents. Faster decisions, less friction, and more personalised interactions translate directly into improved customer retention and acquisition. And 56% said decision intelligence accelerates the deployment of new decision strategies, enabling organisations to test, learn, and adapt more rapidly as market conditions shift.

These are not one-off gains. Because decision intelligence systems improve iteratively, the benefits compound over time. Organisations that adopt this approach are not simply making better decisions today. They are building infrastructure that gets progressively smarter.

The Barriers That Still Need Clearing

Momentum does not mean the path is obstacle-free. Explainability remains a persistent challenge. While decision intelligence platforms are designed to surface the reasoning behind AI-driven outcomes, many organisations are still building the internal capability to interpret and communicate those insights to regulators, auditors, and boards.

Governance is another area where progress is needed. Connecting individual decisions to broader business outcomes (risk exposure, revenue impact, customer satisfaction) makes oversight more meaningful, but it also requires a more sophisticated approach to measurement than many institutions currently have in place.

Integration complexity and the speed at which organisations can detect and respond to fraud were also flagged as ongoing concerns, with 50% of respondents identifying speed as their biggest obstacle in fraud detection specifically.

What This Means for the Industry's Next Chapter

The data paints a clear picture. Financial services leaders are not debating whether decision intelligence matters. They are debating how fast they can implement it. With 77% viewing it as strategically valuable, 75% already collaborating on implementation, and 60% committing investment in 2026, the industry is placing a significant collective bet.

The institutions that move earliest and most decisively will not simply gain a short-term advantage. They will build compounding systems, platforms that learn, adapt, and improve with every decision made. In an industry where marginal gains in accuracy, speed, and customer experience translate into substantial commercial outcomes, that compounding effect may prove to be the most important competitive differentiator of the decade.

The rankings and opinions expressed in this article reflect editorial research and assessment only, and do not represent the views of The Industry Leaders, its owners, or affiliates.