For bank executives, quarterly earnings from core providers and fintechs can provide an early read on where technology budgets are holding up, where priorities are shifting, and where tools like AI are beginning to move from promise to practice. This week, we examine second quarter results from FIS, Q2 Holdings, Fiserv, Alkami, and others to highlight the trends that matter most for bank leaders — from IT spending trends and core modernization to the growing focus on efficiency and AI-enabled productivity.
Key Takeaways:
- Fraud Remains a Focal Point for Investment. Based on a measurable ROI and a significant step-up in effectiveness due to AI, fraud solutions were highlighted as a key investment priority for banks by numerous vendors in 2Q.
- AI Is Only as Effective as the Underlying Data. API-driven architectures enable upgrades to modular tools for lending, fraud, and payments — but only if the bank’s data is in order.
- Efficiency Remains a Key Priority. Like their bank clients, tech vendors emphasized operating leverage and efficiency, highlighting internal process automation, improved implementation timelines, and tighter management of AI infrastructure costs as key priorities.
- Not Every Market Signal is an Industry Signal. Fiserv’s stock reaction appears driven more by company-specific factors than by a deterioration in broader bank technology trends. The 780bps of Y/Y margin contraction reported in 2Q was an outlier relative to peers that the company attributed to catch-up investments in service and tech capabilities.
Fraud – A Key Priority Based on Measurable ROI
“[F]raud has become a continuous enterprise-wide challenge that spans retail, small business and commercial banking, and it is driving increasing levels of attention and investment from our customer.” – Matthew Flake, CEO, Q2 Holdings, Inc (QTWO)
The fraud “arms race” continues. For fraudsters, AI has also advanced the effectiveness of solutions, making the product category a focal point for investment. This quarter, several vendors including FIS and QTWO highlighted strong demand for fraud and risk management solutions, driven by the automation of compliance-related functions and improved detection metrics, including a reduction in false positives. Commentary suggests a re-allocation of investment spend towards fraud, as opposed to an overall increase in spending levels by financial institutions, which are prioritizing areas with a clearer ROI.
The improved effectiveness is driven by the ability to analyze large volumes of transaction, customer and behavioral data simultaneously, facilitating the identification of patterns and anomalies that may otherwise go undetected. As a result, newer solutions can be more dynamic and predictive, relative to traditional fraud capabilities that have been more rules-based and reactive.
Core Modernization and AI: Two Sides of the Same Coin
Within the core banking market, management commentary suggests that AI has accelerated the shift towards modular, API-driven architectures with cleaner data models and real-time access. This transition away from the traditional monolithic systems has provided institutions with the flexibility to upgrade individual capabilities such as payments, lending, and fraud rather than undertaking a multi-year core conversion. More importantly, institutions can better leverage customer, transaction, and operational data — which has historically been fragmented across product silos and legacy systems — to generate more actionable insights.
So what does this mean for bank executives? Simply put, the degree of investment into the core/tech stack required to take advantage of AI-based tools must be factored into a bank’s ROI calculus, as the theoretical benefit from AI is largely driven by the usability and effectiveness of data.
Efficiency Remains a Key Priority, But AI Is Not Yet the Driver.
Like their bank clients, management teams across the tech vendor space emphasized operating leverage and efficiency, highlighting internal process automation, improved implementation timelines, and tighter management of AI infrastructure costs as key priorities. Additionally, Fiserv (FISV) discussed plans to divest non-core assets within its portfolio, while FIS indicated a willingness to sell non-strategic products within its Capital Markets business.
FIS (+193bps Y/Y), QTWO (+510bps Y/Y), and ALKT (+430bps Y/Y) all reported strong margin expansion, driven by cost savings and a mix shift toward higher-margin subscription revenue. Furthermore, both QTWO and ALKT have outlined multi-year frameworks for continued margin expansion, suggesting that the 2Q improvement is not viewed as a one-time event. FISV was the notable exception — a separate story, discussed below.
The takeaway for banks? AI remains an important potential incremental driver of efficiency, but management commentary suggests it is not yet the primary driver of the current margin gains.
Fiserv’s Stock Reaction Is Company-Specific
Shares of FISV remain 3%-4% below pre-earnings levels following yet another guidance reset which was largely due to company-specific factors as opposed to broader industry themes and trends. The reset, which follows an unexpected CEO transition in June, was attributed to 3 factors: 1) Weaker macro conditions in Argentina and a slower ramp of client-driven implementation timelines, 2) A slower pace of execution on growth initiatives, which highlights the need for investment, and 3) The decision to make incremental investments in technology, infrastructure, and cybersecurity that primarily supports its Financial Solutions business.
In our view, the incremental investment headwind, which drove 780bps of margin contraction in 2Q, follows a period of “under-investment” and over-emphasis on earnings results — particularly in the Financial Solutions segment. While scale and product breadth remain advantages for the company, the market’s reaction reflects skepticism around execution and the degree of investment necessary for the company to maintain its competitive positioning in the market.
Based on this quarter’s earnings, there are three questions bank executives should be asking as they head into their next QBRs:
- Is your data actually AI-ready? The ROI is only as good as the underlying data, so ask your vendor to walk through what core/data investment is required on your end to realize the promised lift — not just what the tool can theoretically do.
- Where’s the Measurable ROI on fraud spend, specifically? Push vendors for hard numbers — false positive reduction, dollars recovered, detection lift — rather than the general AI narrative.
- Where are fraud attacks originating, and is our vendor’s detection keeping pace with the vector? Are the vendor’s models trained on data that reflects your institution’s actual exposure, not just industry-wide averages?
