Finance

In finance, AI is not the future. It's what your competitors already use.

Real cases of how banks, fintechs, and insurers use AI to detect fraud in milliseconds, automate processes, and make better credit decisions.

Incumbents that don't move in the next 3 years will lose ground they won't recover.

The AI market in financial services exceeds US$38 billion and grows at 31% annually. From real-time fraud detection to alternative scoring models, AI is redefining what is possible across every function of the financial business.

0%

fraud detection accuracy with AI models vs. 60% with traditional static rules

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of bank onboarding processes can be automated with AI without sacrificing compliance

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reduction in default rates with alternative scoring models that incorporate non-traditional data

Real cases

What other financial institutions have already achieved

Not endless pilots. Production implementations, in real operations.

JPMorgan Chase: AI to review legal contracts in seconds

PROCESS AUTOMATION

JPMorgan Chase — EE.UU. — Sistema COiN — desde 2017

JPMorgan implemented COiN (Contract Intelligence), an AI system to review commercial loan contracts. A task that previously required 360,000 hours of legal work per year — equivalent to 180 full-time lawyers — is now processed in seconds with greater accuracy. The system extracts key clauses, detects inconsistencies, and automatically generates risk alerts.

0hrs

of legal work eliminated per year

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accuracy in extracting key clauses

Mastercard: real-time fraud detection with AI

FRAUD PREVENTION

Mastercard — global — Decision Intelligence Pro — 2024

Mastercard uses recurrent neural networks that analyze the complete transaction history of each card to detect anomalous patterns in milliseconds. The Decision Intelligence Pro system reduces false positives — legitimate transactions incorrectly blocked — by 85% compared to previous rule-based systems, improving customer experience without sacrificing security.

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in false positives vs. previous rule-based system

0ms

average decision time per transaction

Nubank: alternative credit scoring for people without credit history

CREDIT RISK

Nubank — Brasil, México, Colombia — desde 2014

Nubank built credit scoring models that incorporate hundreds of non-traditional variables — app behavior, cell phone usage patterns, consistency of declared information — to extend credit to people without a banking history. The result: financial access for millions excluded from the system, with default rates that compete with traditional banks that only serve lower-risk segments.

0M+

customers served in LatAm with alternative scoring

-0%

in defaults vs. sector average in segments without credit history

What we see for your organization

Three concrete starting points

Not what could happen. What similar financial organizations are already executing.

01

Fraud detection and prevention with AI

Transactions, onboarding, credit applications. Each process has signals that static rule systems cannot process at the necessary speed. AI models analyze the full context of each operation in milliseconds and continuously learn from new fraud patterns. Fewer losses, less friction for the legitimate customer.

Direct and measurable ROI — start with the highest-exposure process
02

Onboarding and KYC process automation

Document validation, identity verification, watchlist screening, inconsistency detection. All of this can be automated with AI, reducing onboarding time from days to minutes and freeing the compliance team to handle cases that truly require human judgment.

Direct impact on conversion and operational cost
03

Customer service assistant with generative AI

Balance inquiries, application status, product explanations, simple claim resolution. A well-trained assistant resolves 70-80% of inquiries without human intervention, 24/7, on any channel. The human team focuses on complex cases where their judgment adds real value.

High adoption — fast implementation — positive NPS

We don't sell AI,
we sell adoption.

We understand how your company works today and build the bridge so AI does the heavy lifting, giving your team back time for strategic tasks.

01
Discover
Week 1–2

We audit processes, interview teams and map the highest-impact opportunities. You leave with a prioritized roadmap.

02
Pilot
Week 3–6

We build the first agent or workflow in production. We measure ROI from day one. No PowerPoints, only results.

03
Adopt
Week 7–10

We train teams to own the technology. The agent becomes their tool, not ours.

04
Scale
Week 11+

We expand what works. New processes, new teams. AI stops being a project and becomes an operational advantage.

Finance

We don't sell AI. We sell smarter financial decisions.

We want to understand how your organization operates today, which processes consume the most time, and where delayed decisions carry the highest cost.

AI in Finance | Fraud Detection and Automation — fuubo.ai