VOL. XCIV, NO. 247
★ MOAT STOCKS & COMPETITIVE ADVANTAGES ★
PRICE: 5 CENTS
Thursday, December 25, 2025
Jack Henry & Associates, Inc.
JKHY · Nasdaq
Weighted average of segment moat scores, combining moat strength, durability, confidence, market structure, pricing power, and market share.
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Overview
Jack Henry & Associates, Inc. provides core processing platforms, payments processing, and complementary digital/operational software to U.S. community and regional banks and credit unions. The Core segment has durable stickiness driven by long-term contracts and high conversion/switching costs, and it is used as a distribution base for add-on products. Payments and Complementary benefit from integration into the installed base and compliance/operational capabilities, but face more competitive pressure and renewal-driven pricing friction.
Primary segment
Payments
Market structure
Competitive
Market share
—
HHI: —
Coverage
3 segments · 7 tags
Updated 2025-12-25
Segments
Core
Core processing platforms for community & regional banks and credit unions
Revenue
31.1%
Structure
Oligopoly
Pricing
moderate
Share
18%-20% (implied)
Peers
Payments
Payment processing and transaction services for financial institutions (card, ACH, bill pay, faster payments, settlement support)
Revenue
36.8%
Structure
Competitive
Pricing
moderate
Share
—
Peers
Complementary
Complementary fintech software and services for financial institutions (digital banking, lending, risk/security, imaging, analytics, operations)
Revenue
28.4%
Structure
Competitive
Pricing
weak
Share
—
Peers
Moat Claims
Core
Core processing platforms for community & regional banks and credit unions
Revenue_share is computed from FY2025 GAAP segment revenue (Core $739.277m of total $2,375.288m). Source: Exhibit 99.1 press release filed with the SEC: https://www.sec.gov/Archives/edgar/data/779152/000077915225000053/jkhy-20250630xex99pressrel.htm
Long Term Contracts
Demand
Long Term Contracts
Strength: 4/5 · Durability: durable · Confidence: 5/5 · 2 evidence
Core processing/hosting revenue is anchored by multi-year contracts (often ~6 years) with recurring fees and minimums, reducing churn and supporting planning/scale.
Erosion risks
- Renewal price compression
- Client M&A causing deconversions
- Cloud-native core competitors lowering switching barriers
Leading indicators
- Core renewal rate and renewal pricing deltas
- Net new core wins vs deconversions
- Mix shift to hosted/private cloud
Counterarguments
- Renewal cycles still create a natural switching window for motivated clients
- API-first architectures can reduce vendor lock-in over time
Switching Costs General
Demand
Switching Costs General
Strength: 4/5 · Durability: durable · Confidence: 4/5 · 2 evidence
Core conversions require planning, data conversion/testing, training, and operational change management; disruption risk makes core replacements infrequent.
Erosion risks
- Regulators encouraging portability/open banking standards
- Modular architectures reducing conversion scope
- Improved migration tooling from competitors
Leading indicators
- Customer retention and deconversion revenue
- Average implementation timelines
- Incidence of core replacement RFPs in the base
Counterarguments
- Some newer institutions may prefer modern cloud-native cores and accept conversion risk
- Switching costs are real but not absolute when contract terms end
Suite Bundling
Demand
Suite Bundling
Strength: 3/5 · Durability: medium · Confidence: 4/5 · 2 evidence
Core clients often buy adjacent complementary/payment modules from the same vendor, increasing integration depth and raising exit barriers vs point solutions.
Erosion risks
- Best-of-breed fintech adoption in digital/lending
- Open APIs enabling more vendor mix-and-match
- Bundled-suite pricing pressure from procurement teams
Leading indicators
- Attach rate of add-on modules per core client
- Revenue per core client over time
- Competitive win/loss trends vs specialist fintechs
Counterarguments
- Many complementary modules are substitutable and face strong category competition
- Banks may prefer multi-vendor stacks to avoid over-dependence on one provider
Payments
Payment processing and transaction services for financial institutions (card, ACH, bill pay, faster payments, settlement support)
Revenue_share is computed from FY2025 GAAP segment revenue (Payments $873.498m of total $2,375.288m). Source: Exhibit 99.1 press release filed with the SEC: https://www.sec.gov/Archives/edgar/data/779152/000077915225000053/jkhy-20250630xex99pressrel.htm
Compliance Advantage
Legal
Compliance Advantage
Strength: 3/5 · Durability: medium · Confidence: 4/5 · 2 evidence
Operating payments platforms at scale requires ongoing compliance with payment network rules/standards and regulators' expectations; established compliance programs reduce execution risk for clients.
Erosion risks
- Network rule changes increasing costs
- Regulatory enforcement after incidents/outages
- Compliance seen as table-stakes by buyers
Leading indicators
- PCI/DSS and network certification status
- Regulatory exam outcomes/remediation items
- Incident/outage frequency and severity
Counterarguments
- Large processors can match compliance investment; it may not confer lasting differentiation
- Compliance costs can compress margins if pricing can't keep up
Scale Economies Unit Cost
Supply
Scale Economies Unit Cost
Strength: 3/5 · Durability: medium · Confidence: 3/5 · 1 evidence
Payments processing has meaningful fixed costs in infrastructure, security, and operations; higher volumes can improve unit economics and fund product/compliance investment.
Erosion risks
- Price competition compressing take rates
- Disintermediation by real-time rails and bank-to-bank connectivity
- Dependence on third parties for parts of processing/settlement
Leading indicators
- Transaction growth vs revenue growth (take-rate pressure)
- Gross margin trend in payments
- Share of volumes on RTP/FedNow vs legacy rails
Counterarguments
- Scale alone may not protect margins if services commoditize
- Large non-bank processors may have superior scale advantages
Data Workflow Lockin
Demand
Data Workflow Lockin
Strength: 3/5 · Durability: medium · Confidence: 3/5 · 1 evidence
Payments products are often embedded into the FI's broader operating stack; integration with digital banking, fraud controls, and core workflows increases stickiness versus standalone processors.
Erosion risks
- Standardized APIs lowering switching friction
- Banks building orchestration layers over multiple vendors
- Fintech point solutions winning specific payment niches
Leading indicators
- Adoption of integrated payment + fraud bundles
- Partner ecosystem growth and usage
- Payment-product churn at renewal windows
Counterarguments
- Some payment functions can be swapped with limited disruption if interfaces are standardized
- Institutions may unbundle payments from other modules to negotiate price
Complementary
Complementary fintech software and services for financial institutions (digital banking, lending, risk/security, imaging, analytics, operations)
Revenue_share is computed from FY2025 GAAP segment revenue (Complementary $675.209m of total $2,375.288m). Source: Exhibit 99.1 press release filed with the SEC: https://www.sec.gov/Archives/edgar/data/779152/000077915225000053/jkhy-20250630xex99pressrel.htm
Suite Bundling
Demand
Suite Bundling
Strength: 3/5 · Durability: medium · Confidence: 4/5 · 2 evidence
A large installed base of core clients creates a distribution advantage for adjacent modules; bundling and cross-sell can raise exit barriers and reduce point-solution displacement.
Erosion risks
- Best-of-breed fintechs outperforming bundled modules
- CIO mandates to diversify vendors
- Rapid product cycles increasing competitive intensity
Leading indicators
- Attach rate of complementary modules per core client
- Win/loss rates in digital and lending modules
- Net revenue retention for complementary solutions
Counterarguments
- Buyers may prioritize feature depth over suite breadth in competitive categories
- Bundling can fail if integration or UX lags category leaders
Data Workflow Lockin
Demand
Data Workflow Lockin
Strength: 3/5 · Durability: medium · Confidence: 3/5 · 1 evidence
Complementary modules often sit on shared data models and workflows (reporting/analytics, entitlements, fraud controls), increasing switching friction when deeply integrated.
Erosion risks
- Standardized data layers (open banking) reducing proprietary data advantages
- Data portability requirements
- Client adoption of independent data warehouses/BI stacks
Leading indicators
- Usage growth of data hub/analytics modules
- API usage and third-party integration depth
- Module churn when cores remain unchanged
Counterarguments
- Some complementary tools can be replaced without changing the core system
- Institutions can decouple data from applications using modern integration layers
Brand Trust
Demand
Brand Trust
Strength: 3/5 · Durability: durable · Confidence: 4/5 · 2 evidence
In regulated, mission-critical environments, vendor trust and service reputation meaningfully influence selection and retention--especially for smaller institutions that value a single accountable partner.
Erosion risks
- Major outage or cybersecurity incident damaging trust
- Service quality degradation during growth or modernization
- Competitors matching service levels
Leading indicators
- Client satisfaction/NPS trend (if disclosed)
- Support ticket resolution times and escalation rates
- Incidents and public disclosures affecting reputation
Counterarguments
- Brand/service is harder to monetize in competitive module categories
- Switching barriers can be lower for some non-core modules
Evidence
...private and public cloud services... typically on a six-year contract...
Supports the claim that hosted core revenue is predominantly multi-year and recurring.
Clients... outsource their core processing typically sign contracts for six years... minimum guaranteed payments...
Shows long-term contract duration and minimums in outsourced core processing.
...implementation typically includes... data conversion... ensure that all data is transferred from the legacy system...
Directly supports operational/organizational switching costs for core migrations.
...experience converting diverse banks and credit unions to our core platforms...
Highlights the complexity of conversions (and vendor capability as a decision factor).
...strengthen exit barriers by cross selling additional products and services.
Explicitly links cross-sell to higher exit barriers.
Showing 5 of 17 sources.
Risks & Indicators
Erosion risks
- Renewal price compression
- Client M&A causing deconversions
- Cloud-native core competitors lowering switching barriers
- Regulators encouraging portability/open banking standards
- Modular architectures reducing conversion scope
- Improved migration tooling from competitors
Leading indicators
- Core renewal rate and renewal pricing deltas
- Net new core wins vs deconversions
- Mix shift to hosted/private cloud
- Customer retention and deconversion revenue
- Average implementation timelines
- Incidence of core replacement RFPs in the base
Curation & Accuracy
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