Buy vs. Build

A Strategic Guide for Financial Institutions

Building banking AI in-house is exponentially harder and more expensive than it was two years ago.

This guide shows you how to decide, and what the stakes are.

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A Strategic Guide for Financial Institutions

Building banking AI in-house is exponentially harder and more expensive than it was two years ago.

This guide shows you how to decide, and what the stakes are.

Slower

to build in-house vs. buying a solution

More Expensive

to build than to invest in a third party platform

Productivity Gain

within 18-24 months when buying vs building

Why 61% of banks still build in-house, and the mounting cost of that decision in an AI-first world.

Why building banking-grade AI in-house is exponentially harder, and a 3 phase roadmap of implementation.

Speed resources, and strategic impact; 3 critical lenses for the buy vs. build decision.

"We were just trying to build exactly what nCino was. It would give us an enhanced speed to market."

Louise Bird, Product Officer, Shawbrook Bank

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"We had to make a decision on time-to-market, adaptability, and being able to buy technology."

Satyajeet Roy, CEO, Habib Bank AG Zurich

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"Do you want to recreate your current processes, or do you want to adopt standard processes created by a solution made for credit granting? That's the choice you have to make at the start of the project."

Clement Loubeyres, Program Manager, Banque Raiffeisen

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Explore nCino's AI Capabilities

5-role based AI agencts for banking workflows

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Peer benchmarking across 150+ institutions

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Conversational AI interface across the platform

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15 pages of frameworks, benchmarks, and real EMEA case studies. No fluff. Just the decision-making clarity your institution needs.