Enterprise Account Executive

Why the smartest capital allocation decision in financial services risk infrastructure isn’t build vs. buy, it’s knowing what’s actually worth building. 

The competitive environment in financial services has fundamentally changed. Margins are compressed. Regulatory complexity is accelerating. Customer acquisition costs are at historic highs. And the fintechs gaining ground aren’t necessarily the ones with the most sophisticated technology, they’re the ones deploying it fastest. 

That context matters when you’re evaluating whether to build proprietary risk decisioning infrastructure from scratch. 

The true cost of building a decisioning platform compounds over time. 

The upfront capex is significant: architecture design, engineering resources, data integration across bureau and alternative data providers, security infrastructure, compliance frameworks. Organisations that have gone through this report 18 to 36 months before a production-ready system is operational. In a market where a competitor can launch a new credit product in weeks, that gap carries direct revenue implications. 

The ongoing opex picture is frequently underestimated at approval stage. Maintaining data integrations as providers update APIs. Rebuilding model deployment pipelines as cloud infrastructure evolves. Keeping pace with regulatory change across markets. Resourcing the support function so the decisioning engine doesn’t become a bottleneck to every product iteration. These aren’t exceptional costs. They’re structural, recurring, and they scale with complexity. 

McKinsey research consistently shows that large-scale internal technology builds in financial services exceed budget in many cases, with five-year total cost of ownership frequently running 40–60% above initial projections. The resource drag on engineering teams is harder to quantify but equally real. Senior talent allocated to infrastructure maintenance is senior talent not working on competitive differentiation. 

Digital-native lenders are entering established segments with lower cost bases and faster decisioning cycles. Embedded finance is putting credit products inside customer journeys that traditional institutions don’t own. Open banking and alternative data are changing what good underwriting looks like. Regulators are demanding more explainability and auditability. 

The organisations gaining ground can test, launch, and iterate on new products in weeks, not quarters. That agility is very difficult to sustain when the decisioning infrastructure itself requires lengthy development cycles every time the business wants to change something. 

Provenir’s Decision Intelligence Platform is built for exactly this trade-off. The infrastructure is already built, maintained, and continuously updated: cloud-native deployment, a marketplace of integrated data providers, model management, compliance and auditability frameworks. What organisations configure on top of it is entirely their own. 

Rather than funding a multi-year infrastructure build, capital goes into configuration, integration, and the proprietary decisioning logic that actually differentiates the business. Time to production is measured in weeks, not years. 

The opex shift is equally significant. Data provider integrations, infrastructure scaling, security patching, regulatory update cycles all move from internal cost centres to the platform’s responsibility. Engineering resource shifts from maintaining infrastructure to building product. The ongoing cost base is predictable, subscription-based, and scales with usage rather than requiring constant reinvestment just to stand still. 

BBVA, Atom Bank, and SoFi each deployed Provenir to run fundamentally different business models: global commercial lending, retail digital banking, consumer refinancing, at different scales and in different regulatory environments. The underlying platform is common. The decisioning logic, risk models, and customer strategies are not. 

The executive concern about IP is legitimate and worth addressing directly. Competitive advantage in financial services credit sits in the credit policy, the data strategy, the risk appetite calibration, and the customer relationships built on top of the engine. On Provenir’s platform, all of that remains entirely proprietary. Scoring models are deployed inside the platform, not exposed. Decision logic is configured by your team to reflect your underwriting philosophy. Two organisations on the same infrastructure share no more of their competitive advantage than two companies hosting on AWS share their code. 

What Provenir removes is the infrastructure layer: the part that costs the most, delivers the least competitive differentiation, and consumes the most ongoing resource to maintain. 

There’s also value that’s difficult to replicate internally. The R&D investment across Provenir’s global client base creates platform capabilities that no single organisation, building in isolation, could justify on its own. 

The build option carries significant upfront commitment, multi-year timelines, and a structural opex burden that compounds over time. In a market where speed and adaptability are increasingly decisive, it also means slower product iteration and delayed competitive response. 

Provenir reframes the question from build vs. buy to where you deploy your capital and your talent. The platform provides the infrastructure. Your team builds the advantage. Your IP, your models, your risk strategy are fully proprietary, executing faster and at materially lower total cost than the build alternative. 

That’s a strategic decision, not just a procurement one.