Goldman Sachs is positive on AI entering the digital banking development stack and prefers QTWO over ALKT

Overview

This report reviews the recently launched AI development tools from Q2 Holdings and Alkami. Goldman Sachs believes Q2 Code and Alkami Code Studio indicate that digital banking software vendors are extending AI from the front-end experience layer into the platform development stack to accelerate customization, deployment, and partner innovation. This trend should help modern digital banking platforms differentiate themselves from traditional core system vendors.

Core views

Goldman Sachs holds a constructive view on both QTWO and ALKT because both companies are using AI to reduce ecosystem development friction and strengthen platform stickiness, speed to market, and customer and partner engagement. However, the report prefers QTWO because Q2 already has the Innovation Studio foundation, so its AI-driven development environment may generate incremental value more quickly; ALKT’s Code Studio direction is also aligned with its open architecture and scalable platform strategy, but it is still in the early beta stage.

Analysis framework

The report uses an event-driven review and relative company comparison approach, evaluating the potential impact of the two companies’ AI development tools around product functionality, platform ecosystem, customer adoption, governance and security requirements, valuation framework, and key risks. On valuation, the 12-month target prices for both QTWO and ALKT are based on a weighted combination of fundamental EV/FCF value and theoretical M&A EV/Sales value.

Methodology notes

• Valuation methodsEV/FCF and EV/Sales weighted valuation

  The target price consists of 85% fundamental value and 15% theoretical M&A value.

  QTWO’s $86 target price is based on 85% of 22.0x Q5-Q8 EV/FCF fundamental value and 15% of 6.5x EV/Sales theoretical M&A value; ALKT’s $18 target price is based on 85% of 19.0x Q5-Q8 EV/FCF fundamental value and 15% of 6.0x EV/Sales theoretical M&A value.

• factor_profileGS Factor Profile

  Compares stock characteristics across growth, financial returns, valuation multiples, and composite percentiles.

  The Goldman Sachs factor framework uses standardized rankings of metrics such as sales, EBITDA, and EPS growth; ROE, ROCE, and CROCI; and P/E, P/B, EV/EBITDA, and EV/FCF to provide investment context for stocks relative to the market and peers.

• corporate_activityM&A Rank

  Uses an M&A rank from 1 to 3 to assess the probability of a company becoming an acquisition target.

  Rank 1 represents high probability, Rank 2 medium probability, and Rank 3 low probability; for companies ranked 1 or 2, Goldman Sachs includes an M&A component in the target price under sector guidelines.

Asset mapping & comparison

Structured mapping from thesis to named assets (strengths, weaknesses, peers, risks).

• Q2 Holdings Inc. (US.QTWO)

  Directly covered company; publisher of Q2 Code

  Strengths

  Existing Innovation Studio ecosystem, with a stronger customer and partner base; the AI development environment may translate more quickly into customer acquisition and expansion value; Goldman Sachs maintains a Buy rating.

  Weaknesses

  Affected by financial institution IT budgets, limited transaction volumes, and the time required to realize value from new customers.

  Comparison

  Compared with ALKT, Goldman Sachs prefers QTWO because its existing platform and ecosystem foundation make the near-term incremental value of AI development tools more visible.

  Risks

  Macro pressure affecting financial institution technology spending, longer time to realize value, intensifying competition, regulatory changes affecting financial institutions with assets below $250bn, and attrition driven by industry consolidation.

• Alkami Technology Inc. (US.ALKT)

  Directly covered company; publisher of Alkami Code Studio

  Strengths

  Code Studio aligns with the open architecture platform and DSSP strategy, supports faster deployment cycles while retaining the governance controls required by bank and credit union customers, and continues to invest in data accessibility and a secure AI access layer.

  Weaknesses

  The product is still in beta, and its near-term commercial impact and scale of adoption have not yet been fully validated; its competitive strength on the banking side still needs to be continuously proven.

  Comparison

  Compared with QTWO, ALKT also benefits from AI moving into the development stack, but Goldman Sachs rates it Neutral, viewing the risk-reward as more balanced.

  Risks

  Pressure on financial institution technology budgets, regulatory changes, longer time to realize value from new deals and cross-sell, slower-than-expected progress in the banking market competitive position, and lower-than-expected MANTL synergies.

Key data

• Q2 Code functionalityConverts natural-language business requirements into Q2 SDK-compliant codeBuilt using Anthropic Claude Code and Amazon Bedrock, for financial institutions and partners to build extensions and integrations on the Q2 Digital Banking Platform.
• Q2 Code development cycle targetCompressed from weeks to daysWhile preserving the governance, security, and platform consistency required in regulated financial services environments.
• Q2 Innovation Studio ecosystemMore than 200 technology partners, more than 2,200 external developers, and approximately 4.5 million active end usersAs of December 31, 2025, Innovation Studio was present in nearly every net new digital banking deal.
• Alkami Code Studio statusbeta stageEmbedded in SDK Wizard and paired with One-Click SDK Manager to help developers create, validate, and deploy SDK components in a secure, governed environment.
• Alkami AI infrastructureClosed-loop LLM and secure AI access layerAlkami emphasizes running closed-loop LLMs within its own secure infrastructure and using model context protocol to support longer-term AI embedding across the platform.
• Next catalyst1Q26 earnings call on 2026-04-29Goldman Sachs expects management at both companies to provide more information when 1Q26 earnings are released.

Impact & implications

If these tools are successfully rolled out, digital banking software vendors could improve customer retention and expansion opportunities through faster custom delivery, lower development barriers, and stronger partner ecosystems. For QTWO, AI development tools could further amplify the existing ecosystem advantage of Innovation Studio; for ALKT, Code Studio could help reinforce its open architecture and DSSP strategy, though commercialization and large-scale adoption still need to be validated.

Risks

• Macro headwinds may suppress financial institution technology budgets.
• If the time to realize value from new deals and cross-sell lengthens, growth could be affected.
• Rising competitive intensity may weaken the current favorable win rate.
• Regulatory changes may negatively affect financial institution customers with assets below $250bn.
• Industry consolidation may lead to customer attrition.
• AI development tools are still in an early or limited rollout stage, and actual adoption rates, commercialization speed, and ROI remain to be validated.

What to watch

• Additional commentary from management on Q2 Code and Alkami Code Studio in the two companies’ 1Q26 earnings on 2026-04-29.
• Progress of the Q2 Code early access program expansion in 2026 and the timeline for broader availability.
• The pace at which Alkami Code Studio moves from beta to formal launch.
• Whether AI development tools drive faster implementation, higher cross-sell, stronger partner engagement, and lower customer churn.
• Changes in financial institution IT budgets, the regulatory environment, and competitive intensity in digital banking platforms.