How Partnerships Are Redefining Competitive Advantage in Banking

Executive summary

For personal and business banking organisations, partnerships are no longer a peripheral innovation activity. They are becoming a core route to customer ownership, data advantage, lower-cost distribution, stronger risk management and new fee income.

The global banking industry remains highly profitable, but the competitive pressure is changing. McKinsey’s 2026 Global Banking Annual Review notes that global banking net income rose to $1.3 trillion in 2025, while also highlighting a “tipping point for customer ownership” and the accelerating impact of AI on banking strategy. Deloitte’s 2026 banking outlook similarly frames 2026 as a defining year in which banks must deal with macro pressure, non-bank competition, stablecoins, AI industrialisation, brittle data infrastructure and faster-moving financial crime.

The implication for C-suite banking leaders is clear: the next competitive edge will come less from isolated banking products and more from orchestrating the right ecosystem around customers’ financial lives and business workflows.

This paper identifies the five partnership categories most likely to create competitive advantage for personal and business banks:

1. SME operating-system partnerships

2. Embedded finance and life-event ecosystem partnerships

3. Payments, merchant and programmable-money partnerships

4. Data, AI, cloud and core-modernisation partnerships

5. Digital identity, cyber, fraud and trust partnerships

The common thread is that each partnership type moves the bank closer to a critical control point: the customer’s daily activity, the SME’s operating workflow, the payment flow, the intelligence layer, or the trust layer.

1. SME operating-system partnerships

Strategic rationale

The most attractive business banking partnerships are no longer simply with fintech lenders or card processors. They are with the platforms that run the daily operations of SMEs: accounting software, payroll platforms, POS providers, e-commerce platforms, tax tools, invoicing systems, inventory platforms, logistics tools and vertical SaaS providers.

BCG argues that vertical SaaS platforms have become the de facto “operating systems” for many SMEs, while more than 80% of the embedded finance market remains in play. It estimates the embedded finance total addressable market in North America and Europe at about $185 billion across payments, capital solutions, accounts and card issuing. The IFC’s MSME banking handbook specifically recommends that financial institutions partner with fintech firms, accounting software providers and e-commerce platforms to create integrated ecosystems that support MSMEs at every stage of growth.

Why this matters for banks

SME banking is often underserved because the bank sees the account, but not the business. It sees deposits, payments and credit applications, but often lacks the richer operating data that shows sales cycles, payroll commitments, supplier pressure, invoice ageing, margin movement and cash-flow stress.

Partnerships with SME operating platforms can change that. They allow the bank to move from reactive product selling to proactive financial enablement.

High-value use cases

For business banking, the strongest use cases include:

• Cash-flow forecasting linked to live accounting and invoice data.
• Pre-approved working capital based on trading behaviour, not only historical financial statements.
• Merchant cash advances linked to POS and card turnover.
• Automated reconciliation between bank accounts, invoices, VAT and payroll.
• Sector-specific lending for restaurants, medical practices, trades, e-commerce merchants or professional services firms.
• Integrated business insurance, asset finance and supplier payments.

For personal banking, the relevance is also significant. Many customers are sole proprietors, freelancers, side-hustle operators or owner-managers. A bank that understands the blurred line between household finance and small-business finance can create more relevant propositions.

Competitive edge

The bank gains a stronger data advantage, improved credit decisioning, better retention and more frequent engagement. The customer gains a bank that understands the business rather than merely providing an account.

The strategic choice is whether the bank wants to be the visible orchestrator of the SME ecosystem or the regulated financial engine behind someone else’s platform. In either case, doing nothing allows software platforms and non-bank providers to capture the workflow layer before the bank does.

C-suite questions

The C-suite should ask:

• Which SME segments are most strategically important to us?
• Which software platforms already control the daily workflow of those businesses?
• Where can we use partner data to improve credit, cash-flow support and retention?
• Do we have the API, risk and compliance capability to partner at scale?
• Are we willing to build vertical propositions rather than generic SME bundles?

2. Embedded finance and life-event ecosystem partnerships

Strategic rationale

Customers do not wake up wanting a banking product. They want to buy a home, run a business, travel, educate children, manage household costs, buy a car, start a side business, protect their family, or improve their financial position.

Embedded finance partnerships allow banks to appear at the point of need, not only inside the banking app. Relevant partners include retailers, property platforms, telcos, mobility platforms, travel platforms, education providers, loyalty ecosystems, healthcare and wellness providers, payroll platforms and large consumer marketplaces.

Accenture’s 2026 banking trends describe banking experiences as becoming conversational, adaptive and present wherever customers are. It recommends that banks build “life event” ecosystems and expose their brands through partner APIs, generative AI platforms, message platforms and wearables. Capgemini’s World Retail Banking Report 2025 also notes that neobanks, instant payments and digital wallets are accelerating competition, while only 26% of customers are satisfied with their current card-related banking experiences.

Why this matters for banks

The traditional bank model assumes that customers come to the bank when they need a product. The ecosystem model assumes that customers are already somewhere else when the financial need arises.

A personal banking customer may be on a property platform before thinking about a mortgage. A small business may be inside an accounting system before thinking about working capital. A consumer may be checking out online before thinking about credit, rewards, insurance or instalments.

The bank that is present in these moments has a distribution advantage.

High-value use cases

For personal banking:

• Home-buying ecosystems combining mortgage pre-approval, property search, insurance, conveyancing and moving services.
• Vehicle ownership ecosystems combining finance, insurance, maintenance, fuel, tolling and resale.
• Retail and loyalty partnerships that link cards, wallets, rewards and personalised offers.
• Salary-linked propositions with employers, including financial wellness, savings, responsible credit and emergency liquidity.
• Education finance partnerships with schools, universities and training providers.

For business banking:

• Banking embedded into procurement, payroll, e-commerce, logistics or merchant platforms.
• Sector-based ecosystems for retail, agriculture, healthcare, hospitality, property services and professional services.
• Integrated merchant propositions combining payments, lending, loyalty, analytics and fraud protection.

Competitive edge

Embedded partnerships reduce customer acquisition cost, improve relevance, create richer behavioural data and increase daily engagement. They also defend the bank against becoming a back-end balance sheet provider while non-bank platforms own the customer interface.

The danger is disintermediation. If the bank only supplies regulated products in the background, it may lose the brand relationship, customer data and pricing power. The better model is selective visibility: the bank should decide where it must own the customer relationship and where it is comfortable being an invisible infrastructure partner.

C-suite questions

The C-suite should ask:

• Which life events or business moments are most strategically valuable?
• Which partners already own those moments?
• Where must the bank’s brand be visible?
• Where is white-labelling acceptable?
• What customer data, consent and conduct controls are required?

3. Payments, merchant and programmable-money partnerships

Strategic rationale

Payments are the bloodstream of banking. They generate data, daily engagement, deposits, merchant relationships and fee income. They are also one of the areas most exposed to disruption from fintechs, wallets, real-time payment rails, stablecoins, tokenised deposits and alternative payment methods.

Deloitte’s 2026 banking outlook explicitly raises the disruptive entrance of stablecoins and asks whether banks can industrialise AI while defending against more sophisticated financial crime. Accenture warns that digital currencies, stablecoins, central bank digital currencies and tokenised deposits are reshaping how money is stored, moved and used, and says banks need to decide whether they will lead as issuer, custodian or facilitator.

For South African banks, this issue is especially relevant. The South African Reserve Bank identifies payments as a strategic priority in its Strategy 2030, and its Payments Ecosystem Modernisation Programme aims to enable fast, simple, inclusive and secure digital payments across the country.

Why this matters for banks

If banks lose the payment flow, they lose more than transaction fees. They lose behavioural data, customer engagement, merchant relevance and early warning signals about financial stress or opportunity.

For business banking, payments are the gateway to merchant services, working capital, treasury, reconciliation, fraud protection and cash-flow insights. For personal banking, payments are the most frequent interaction customers have with their bank.

High-value use cases

The most important partnership areas include:

• Real-time account-to-account payments.
• Request-to-pay services for businesses and consumers.
• QR and low-cost merchant acceptance.
• Cross-border payments and remittance partnerships.
• Merchant acquiring and payment orchestration.
• Card scheme and wallet partnerships.
• Stablecoin, tokenised deposit and programmable payment experimentation where regulation allows.
• Fraud intelligence sharing across payment networks.

Competitive edge

A bank with stronger payments partnerships can protect transaction flows, deepen merchant relationships, improve SME propositions and create more defensible customer engagement. It can also use payments data to support credit, loyalty, pricing, fraud prevention and personalised offers.

The payment partnership strategy should not be treated as an operations issue. It belongs on the C-suite agenda because payment flows are becoming a strategic battleground for customer ownership.

C-suite questions

The C-suite should ask:

• Which payment flows are most at risk of moving outside the bank?
• Which merchant segments are strategically valuable?
• Where should the bank lead, co-create or participate in shared infrastructure?
• What role should the bank play in digital money: issuer, custodian, processor, facilitator or risk manager?
• How will payments data be converted into better customer propositions?

4. Data, AI, cloud and core-modernisation partnerships

Strategic rationale

AI is becoming a structural banking capability rather than a technology experiment. The 2026 Global AI in Financial Services Report, produced by the Cambridge Centre for Alternative Finance with institutions including the BIS, IMF, World Economic Forum and World Bank Group, surveyed 628 financial institutions, AI vendors and regulatory authorities across 151 jurisdictions. It found an execution gap between widespread early-stage AI adoption and true strategic transformation, with persistent constraints in data quality, legacy infrastructure and talent.

Deloitte similarly asks whether banks’ AI ambitions may be thwarted by brittle and fragmented data infrastructure. Accenture’s 2026 banking trends note that banking technology must move from keeping systems alive to powering growth, while highlighting that technical debt and legacy systems remain major constraints.

Why this matters for banks

AI will not create competitive advantage if it is bolted onto fragmented data, old core systems and disconnected customer journeys. Banks need partnerships with cloud providers, AI platforms, data-governance specialists, customer-experience platforms, model-risk specialists, cybersecurity providers and core-modernisation firms.

This is not about replacing internal capability. It is about accelerating capability where the bank cannot move fast enough alone.

High-value use cases

For personal banking:

• Personalised financial coaching.
• Next-best-action recommendations.
• Proactive savings, debt and cash-flow alerts.
• AI-assisted service resolution.
• Early identification of vulnerable customers.
• Dynamic fraud and scam warnings.

For business banking:

• SME cash-flow assistants.
• Relationship manager copilots.
• Automated credit-pack preparation.
• Early warning indicators for business distress.
• Sector-level portfolio analytics.
• AI-supported onboarding and KYC review.
• Working-capital recommendations based on trading behaviour.

For internal banking operations:

• Software development acceleration.
• Contact-centre productivity.
• Compliance monitoring.
• Collections prioritisation.
• Financial crime case summarisation.
• Document intelligence for credit and onboarding.

Competitive edge

The banks that win with AI will not necessarily be those with the most pilots. They will be those that integrate AI into data architecture, operating model, risk governance and customer journeys.

The partnership advantage comes from combining the bank’s trusted data and regulated balance sheet with external capabilities that bring speed, specialist expertise and scalable infrastructure.

C-suite questions

The C-suite should ask:

• Do we have the data quality and lineage to support AI safely?
• Which AI use cases create measurable revenue, cost, risk or customer outcomes?
• Which capabilities must remain proprietary?
• Which capabilities should be sourced through partnerships?
• How do we manage model risk, cyber risk, third-party concentration risk and conduct risk?

5. Digital identity, cyber, fraud and trust partnerships

Strategic rationale

Trust is becoming a competitive battleground. The faster banking becomes digital, the more exposed customers and banks become to identity fraud, deepfakes, synthetic identities, account takeover, scams, mule accounts, business email compromise and payment redirection fraud.

Entrust’s 2025 Identity Fraud Report states that a deepfake attempt occurred every five minutes in 2024, while digital document forgeries increased 244% year on year. Visa’s Spring 2025 Biannual Threats Report highlights rising scam activity, enumeration attacks, provisioning fraud, malicious mobile applications, POS vulnerabilities, one-time-passcode bypass scams and ransomware/data-breach incidents across the payment ecosystem. Entrust’s 2026 report also shows that fraud risk is elevated in areas such as lending, mortgages, remittance and FX, where high-value transactions or rapid digital onboarding are involved.

Why this matters for banks

A bank can have the best digital onboarding journey in the market, but if the fraud controls are weak, growth becomes dangerous. Conversely, a bank can have strong controls but lose customers if onboarding and authentication are too cumbersome.

The competitive advantage lies in combining security and convenience.

High-value partnership areas

Relevant partners include:

• Digital identity verification providers.
• Biometric and liveness detection firms.
• Device intelligence providers.
• Behavioural analytics specialists.
• Scam-detection and mule-network intelligence platforms.
• Regtech and AML/KYC providers.
• Threat-intelligence networks.
• Cyber-resilience and incident-response firms.
• Deepfake detection and synthetic identity specialists.

High-value use cases

For personal banking:

• Fast onboarding with stronger identity verification.
• Step-up authentication based on risk, not blunt friction.
• Scam warnings before high-risk payments are executed.
• Behavioural detection of account takeover.
• Protection for elderly or vulnerable customers.
• Secure recovery when credentials are compromised.

For business banking:

• Beneficial ownership verification.
• Business email compromise detection.
• Payment beneficiary validation.
• Supplier-change risk alerts.
• Suspicious invoice or payment-pattern detection.
• Director and authorised-user identity assurance.

Competitive edge

Trust partnerships reduce fraud losses, accelerate safe onboarding, protect customers and strengthen the bank’s brand. They are also increasingly important for ecosystem banking, because every new partner, API and embedded channel creates a broader attack surface.

The best banks will treat fraud prevention as a customer experience issue as much as a risk issue.

C-suite questions

The C-suite should ask:

• Are our fraud controls fit for AI-enabled fraud?
• Can we detect deepfakes, synthetic identities and mule networks?
• Are we sharing intelligence across the right industry networks?
• Do we know where customer friction is necessary and where it is avoidable?
• Is fraud prevention embedded into product design, not added after launch?

The five-partnership model

The most useful way for banking leaders to think about partnerships is not by vendor category, but by strategic control point.

The strongest banks will not pursue all partnerships equally. They will build a deliberate portfolio of partnerships linked to strategy, customer segments and measurable value pools.

How banks should prioritise partnerships

A practical C-suite screening framework should include five tests.

1. Does the partnership improve customer ownership?

The best partnerships give the bank access to a high-value customer moment or workflow. Weak partnerships merely add another channel without improving relevance or control.

2. Does it create a data advantage?

The partnership should improve the bank’s understanding of customer behaviour, business cash flow, risk, intent or need. Data without consent, governance and analytical capability is not an advantage.

3. Does it improve unit economics?

Partnerships should reduce acquisition cost, increase retention, improve risk selection, create fee income, deepen product holding or lower operating cost.

4. Does it strengthen strategic control rather than weaken it?

Some partnerships quietly disintermediate the bank. The bank should be clear on who owns the customer interface, data, pricing power, service experience and brand relationship.

5. Can it scale safely?

Partnerships must be scalable from a technology, regulatory, cyber, conduct, operational and third-party risk perspective. A good pilot that cannot pass risk review is not a strategic partnership.

Execution model: what C-suite leaders should put in place

Banks often fail with partnerships not because the strategy is wrong, but because the operating model is too slow. To make partnerships a genuine competitive advantage, banks need a more disciplined model.

1. Establish an executive partnership portfolio

Partnerships should be managed as a portfolio, not as scattered business-unit initiatives. Each partnership should be linked to one of the bank’s strategic priorities: personal banking growth, SME growth, payments, data and AI, fraud resilience, cost reduction or customer experience.

2. Create a clear “build, buy, partner” discipline

Not every capability should be partnered. The bank should own capabilities that are core to trust, data, risk, customer relationship and strategic differentiation. Partnerships should be used where they accelerate speed, reach, specialist capability or ecosystem access.

3. Build reusable API and integration capability

Without reusable APIs, sandboxes, consent management, data standards and security patterns, every partnership becomes a bespoke technology project. The result is slow execution and high integration cost.

4. Upgrade third-party risk management

Traditional vendor due diligence is not enough for ecosystem banking. Banks need ongoing monitoring of cyber resilience, data use, customer treatment, operational performance, financial stability, regulatory compliance and concentration risk.

5. Align incentives

Partnerships fail when economics are unclear. The bank and partner must agree how value is created, shared and measured. This includes revenue share, referral fees, balance-sheet returns, data usage, service obligations, customer ownership and exit rights.

6. Measure outcomes, not activity

The wrong measures are number of pilots, number of partners or number of innovation announcements. The right measures are active customers, cost of acquisition, conversion, retention, product holding, transaction growth, merchant growth, credit performance, fraud reduction, revenue uplift and return on technology investment.

Recommended 12-month C-suite agenda

First 90 days: diagnose and prioritise

The executive team should map the bank’s current partnership portfolio against the five control points: workflow, customer moment, transaction flow, intelligence and trust. It should then identify the two or three areas with the greatest strategic upside.

For many banks, the highest-priority opportunities will be SME operating-system partnerships, payments partnerships and fraud/identity partnerships.

Months 3 to 6: launch focused pilots

The bank should avoid broad experimentation. It should select a small number of high-value use cases with clear commercial owners, measurable outcomes and risk involvement from day one.

Examples include SME cash-flow lending through accounting data, merchant payments plus working capital through POS partnerships, or digital onboarding with improved identity and fraud controls.

Months 6 to 12: scale what works

The bank should move successful pilots into industrialised delivery. This requires reusable integration patterns, partnership playbooks, risk frameworks, customer-service models and executive-level performance tracking.

The objective is not to become a fintech investor or innovation showcase. The objective is to make partnerships a repeatable growth and resilience capability.

Conclusion

For personal and business banks, the partnership question is no longer: Which fintechs should we work with?

The better question is: Which partners can help us own the customer moments, business workflows, payment flows, intelligence layers and trust mechanisms that will define the next era of banking?

The top five partnership priorities are therefore:

1. SME operating-system partnerships to become embedded in business workflows.

2. Embedded finance and life-event ecosystem partnerships to be present at the point of need.

3. Payments and programmable-money partnerships to protect transaction flows and merchant relevance.

4. Data, AI, cloud and core-modernisation partnerships to turn information into personalised, scalable action.

5. Digital identity, cyber, fraud and trust partnerships to enable safe digital growth.

The banks that win will not simply have the most partners. They will have the most strategically coherent ecosystem, the strongest data and trust foundations, and the clearest view of where they must lead versus where they should partner.