The Complete Guide to Using AI in the Financial Services Industry in Chile in 2025

Chile's financial services sector is at an inflection point in 2025: with over 250 fintechs now operating and a progressive Fintech Law plus an Open Finance rollout, AI isn't optional - it's the engine for faster credit decisions, smarter fraud detection, and truly personalised customer experiences across banks and startups alike.

Regulators like the CMF are pushing secure data-sharing and tighter governance as firms adopt machine learning for underwriting and automated advisory, while industry voices highlight generative AI's role in hyper-personalisation and automation for Latin American banking (think credit decisions in seconds).

Learn more about Chile's regulatory push and Open Finance in the Chambers Fintech 2025 guide and see why generative AI is reshaping regional banking in this analysis; for teams ready to apply these trends at work, the AI Essentials for Work bootcamp (Nucamp) offers practical, nontechnical training to turn AI tools and prompts into real business impact.

Attribute	Information
Description	Gain practical AI skills for any workplace; use AI tools, write effective prompts, apply AI across business functions (no technical background needed).
Length	15 Weeks
Courses included	AI at Work: Foundations; Writing AI Prompts; Job Based Practical AI Skills
Cost	$3,582 early bird; $3,942 afterwards; paid in 18 monthly payments, first payment due at registration
Syllabus / Registration	AI Essentials for Work syllabus (Nucamp) • Register for AI Essentials for Work (Nucamp)

Chile's financial ecosystem in 2025 mixes a robust, well-regulated banking core with a rapidly evolving fintech layer: the Central Bank continues to anchor monetary stability and liquidity rules while the Financial Market Commission (CMF) drives supervision, governance and the Fintech Law rollout - including the new Registry of Financial Service Providers and the technical build‑out for Open Finance.

The CMF now oversees a vastly expanded perimeter (more than 8,000 supervised entities managing roughly 76.5% of market assets, some USD 604 billion) and, as of April 23, 2025, had already received 372 enrollment applications and 249 authorization requests for fintech providers, underscoring the supervisory challenge ahead.

Regulatory milestones such as the CMF's NCG 514 (the Open Finance System, implemented on a phased timetable) and recent amendments to NCG 502 tighten governance, operational capacity and consumer‑consent rules for APIs, payment initiation and data sharing, while AML supervision (UAF), tax oversight (SII) and a fintech sandbox provide complementary controls and pathways to market.

Picture regulators juggling thousands of entities while wiring the “plumbing” for secure, consented data flows - a practical shift that directly affects how banks and fintechs deploy AI for credit, fraud and personalised services.

“Regulation has allowed the country to have a solid financial structure capable of responding to new global challenges”

Chile's stance on AI in 2025 is pragmatic and nationally coordinated: the Ministry of Science, Technology, Knowledge and Innovation (Minscience) leads the Chilean AI Policy 2021–2030, a strategy built on three clear pillars - enabling factors, development and adoption, and ethics/regulatory & socio‑economic impacts - with an action plan and monitoring mechanism to turn policy into practice (see the Chilean AI Policy 2021–2030 for details).

Complementing the strategy, a May 2024 draft AI bill frames regulation around a risk‑based approach (comparable to the EU AI Act), flagging prohibited applications and stricter obligations for high‑risk systems so organizations must tighten governance, documentation, transparency and meaningful human oversight; this regulatory direction is summarized in the AI Regulation Chile policy framework overview.

The net effect for financial services is a clear

so what?

- AI adoption is encouraged, but banks and fintechs will need robust lifecycle controls and compliance workflows to both unlock innovation and avoid regulatory friction.

Attribute	Information
Policy name	Chilean AI Policy 2021–2030
Lead ministry	Ministry of Science, Technology, Knowledge and Innovation (Minscience)
Start year	2019 (policy active, 2021–2030)
Core pillars	Enabling factors; Development & adoption; Ethics, regulatory aspects & socio‑economic impacts
Legislative status	May 2024 draft AI bill (risk‑based approach; provisions for prohibited/high‑risk systems)
Monitoring	Action plan with defined responsibilities and monitoring mechanism

The industry outlook for 2025 makes clear that AI in Chile is moving from pilot projects to scaled deployments that matter for finance: market analyses show rapid expansion - Grand View Research forecasts generative AI revenues approaching US$459.2 million by 2030 (roughly a low‑to‑mid‑30% CAGR from 2025–2030) and Mordor Intelligence pegs the Chile AI data‑center market at about US$245.27 million in 2025 (with ~17.9% CAGR), signalling that both software and infrastructure spending are already material for banks and fintechs.

6Wresearch further documents broad enterprise adoption across finance, healthcare and retail, driven by ML, NLP and automation use cases that directly enable faster credit decisions, smarter fraud detection and more personalised customer service.

The practical “so what?” is vivid: expect more local capacity for cloud and colocation, rapidly expanding vendor choices, and greater pressure to hire AI skills and shore up governance so models can be deployed at scale without tripping compliance or privacy rules - precisely the operational shift Chile's financial sector is preparing for as Open Finance and tighter supervision reshape data flows.

For deeper reads, see Grand View's regional generative AI outlook, Mordor's data‑center forecast and 6Wresearch's enterprise AI report.

Metric	Value (Source)
Generative AI projected revenue (2030)	US$459.2 million (Grand View Research)
AI Data‑Center market (2025)	US$245.27 million; CAGR ~17.88% (Mordor Intelligence)
Enterprise AI outlook	Significant cross‑industry growth; demand for ML, NLP, automation (6Wresearch)

By 2025 Chilean banks and fintechs are using AI across a familiar - but rapidly maturing - playbook: machine‑learning credit scoring that taps alternative data to widen access, real‑time fraud detection that flags anomalies before funds move, and generative‑AI driven chatbots and voice assistants that shrink call‑centre costs while delivering Chilean‑Spanish customer experiences.

These capabilities show up as robo‑advisers and automated trading systems for investment customers, hyper‑segmented personalisation engines that tailor offers to life‑stage and behaviour, and regtech tools that automate AML checks and compliance reporting under Open Finance‑enabled data flows; the result is faster decisions and more inclusive lending options (see the IADB analysis on AI and credit access).

Practical examples and regulatory context are already mapped in the market overview - from credit scoring and fraud use cases to personalised advice - in the Chambers Fintech 2025 guide, while industry writers note generative AI's growing role in preventing fraud and driving automation across Latin American banking.

The “so what?” is tangible: faster, safer services that can reach underserved customers without abandoning the governance and transparency the CMF now expects.

(Chambers Fintech 2025 guide - Chile trends and developments; IADB analysis: Can AI help expand credit access in Latin America; Generative AI and Machine Learning: The New Architects of Banking in Latin America)

Open Finance in Chile is rapidly shifting from policy to the practical data plumbing that powers real AI use-cases: General Rule No. 514 (NCG 514) requires banks, card issuers and other participants to exchange client data only with express consent and via standardised APIs, a design that should make clean, model-ready data far easier to access - while also forcing stricter lifecycle controls for data used in machine learning.

The CMF's roadmap sets a clear start date (implementation begins 24 months after publication, i.e., July 4, 2026) and a staged rollout by participant type and data category, so AI projects must align with phased API availability and the CMF's technical Annexes and Directory of Participants.

think of the Directory as a live “phonebook” of authorised APIs and digital certificates

Recent 2025 amendments under public consultation add heavyweight operational safeguards - mandatory sandbox testing, secondary interfaces for continuity, reinforced consent rules and a user control panel to view/revoke permissions - which together mean data access for AI will come with stronger provenance, traceability and compliance obligations.

The upshot for financial services: richer, interoperable data to train scoring, personalization and fraud models, but only if organisations invest in consent-aware engineering, external validation in the CMF sandbox and airtight governance to meet the new security and audit requirements (see the CMF rule NCG 514 and the CMF public consultation on Technical Annex No.

3 for details).

Item	Detail
Regulation	CMF NCG 514 Open Finance System regulation - Carey analysis
Implementation start	24 months after publication - from July 4, 2026
Main data channel	APIs; CMF to publish API standards, performance and data quality rules
Key safeguards (2025 amendments)	Sandbox testing, secondary continuity mechanism, strengthened consent, Participant Directory enhancements (CMF public consultation on NCG 514 Technical Annex - Carey)

Regulation, compliance and risk management for AI in Chile in 2025 sits at the intersection of a pragmatic, risk‑based AI agenda and a tightly supervised financial sector: banks and fintechs must now marry the Chilean AI policy trends (risk classification, human‑centred safeguards and sandboxes) with concrete CMF rules that already govern providers' registration, governance, operational capacity and outsourcing.

The CMF's NCG 502 imposes clear expectations on corporate governance, internal controls, documentation and proportional risk management for fintech services, while NCG 514's Open Finance rules layer API, consent and continuity obligations on any data‑intensive ML or generative‑AI project - so lifecycle controls, traceability and sandbox testing are not optional.

Cloud or third‑party model hosting triggers specific outsourcing due diligence and business‑continuity rules (see RAN 20‑7 and related CMF guidance), and recent data‑protection updates (Law 21.719, 2024) plus the national cybersecurity framework tighten breach notification, data transfer and security expectations for model training data.

Practically speaking, teams deploying scoring, personalization or fraud models must create an auditable

paper trail

linking datasets, tests, performance metrics and meaningful human oversight - think of model documentation as the digital spine auditors will ask to see.

For implementation guidance, CMF rule summaries and updates are usefully explained in Carey analysis of CMF NCG 502 fintech regulation, cloud‑and‑outsourcing considerations appear in AWS Chile cloud compliance guidance for financial services, and the regional risk‑based approach to AI regulation is surveyed in the FPF overview.

Regulation / Law	Key requirement	Notes / Effective
Carey analysis of CMF NCG 502 fintech regulation	Registration/authorization, governance, risk management, operational capacity	In force; updates issued Dec 2024 to refine governance and assessment methodology
Carey analysis of CMF NCG 514 Open Finance regulation	Standardised APIs, consent, sandbox testing, continuity & Participant Directory	Issued July 2024; phased implementation (start date per CMF timetable)
AWS Chile cloud compliance guidance for financial services	Outsourcing due diligence, contractual and operational controls for cloud providers	Relevant for cloud hosting, data processing and vendor management
Law 21.719 (Data protection updates)	Stronger consent rules, data subject rights, breach notification & international transfer rules	Enacted 2024 - impacts ML data governance

Building AI solutions in Chile means making pragmatic vendor and sourcing choices that balance talent, cost, control and compliance: the local outsourcing market is growing fast and offers options from IT outstaffing and Employer‑of‑Record models to full R&D hubs, so teams can scale engineers quickly without a local entity (see Alcor's guide to outsourcing to Chile for concrete models and pricing).

Vendor selection should include algorithmic‑transparency and procurement clauses now standard in Chilean public procurement - tools and audit checklists from the GobLab “Ethical Algorithms” project are a useful template for contract language and bias‑review requirements - and contracts must also spell out data‑sovereignty, GPU access and continuity plans as the AI data‑center decision (own vs outsourced) materially affects latency, security and regulatory compliance (Vertiv's analysis highlights why financial services weigh control against capex when sizing AI infrastructure).

Practical steps: require audit reports, define SLAs for model‑retraining/patching, build a vendor‑risk scorecard, and pilot in a sandboxed environment before wider rollout; a vivid, tangible data point: Chile already fields 61,000+ developers clustered in Santiago, Valparaíso and Concepción with data‑science salaries from about US$22k–38k, making near‑shore teams both capable and cost‑competitive for scaled AI work.

Metric	Value (Source)
IT outsourcing market (2024)	About US$657 million (Alcor)
IT outsourcing market (projected 2028)	Exceed US$1,000 million (Alcor)
Developer pool	61,000+ developers; hubs: Santiago, Valparaíso, Concepción (Alcor)
Data Scientist salary (gross, USD)	US$22,000–38,000 (Alcor)

“This not only improves the efficiency of government acquisitions but also strengthens public trust in government management and fosters equal opportunities for suppliers and contractors.”

Big AI bets in Chile in 2025 came from a mix of state-backed science consortia, national research centres and major cloud and data‑centre players: the National Center for Artificial Intelligence (CENIA) led the regionally ambitious Latam‑GPT project with contributions from 30+ institutions to build an open, culturally grounded LLM (initial rollout targeted for late 2025), while a Corfo‑managed, state‑funded push allocated 14 billion pesos to two national supercomputing centres - SCAI‑LAB in Santiago and CSIAA in Valparaíso - designed to provide training and inference capacity for industry and research (see the Inria Chile supercomputing announcement).

Organization / Project	Planned investment or role	Note
CENIA Latam‑GPT regional LLM project coverage	Regional LLM development; multi‑institution contributions	30+ regional partners; temporary Amazon Cloud hosting, planned migration to solar‑powered Atacama data centre
Inria Chile announcement on national supercomputing centres for AI	14 billion pesos (total; ~7B each)	Two AI supercomputing centres for training/inference in Metropolitan & Valparaíso regions
Global cloud & data‑centre firms	Data‑centre expansion & hosting	Google, AWS, Equinix among firms active or monitoring Chile's growth

“We wanted a model where you know where the data comes from. That level of transparency just doesn't exist in most commercial systems.” - Alexandra García, CENIA

Beginners should turn curiosity into a short roadmap: start by cataloguing every AI tool and model in use (a central AI registry is essential), run a basic AI impact assessment and human‑in‑the‑loop rule for any system that touches customers, and build simple, auditable documentation - model cards, data lineage and logs - that auditors and the CMF will expect; practical guides like GRSee's GRSee ISO 42001 compliance checklist and OneTrust's OneTrust EU AI Act compliance checklist make those first governance steps concrete.

Pair governance with consent‑aware engineering (OneTrust's consent guidance helps translate rules into UI and API controls) and pilot early in a sandboxed environment to prove performance and traceability under Chile's Open Finance timetable.

For hands‑on skills - prompt design, tool workflows and translating policy into day‑to‑day tasks - consider a practical course such as Nucamp's Nucamp AI Essentials for Work bootcamp (registration), which teaches nontechnical teams how to run safe, auditable AI projects in 15 weeks; one neat way to remember the priority is this: a single, well‑kept model card and an exportable audit log can save weeks during a compliance review, turning regulatory risk into competitive trust as Chile's market scales.

Attribute	Information
Description	Gain practical AI skills for any workplace; use AI tools, write effective prompts, apply AI across business functions (no technical background needed).
Length	15 Weeks
Courses included	AI at Work: Foundations; Writing AI Prompts; Job Based Practical AI Skills
Cost	$3,582 early bird; $3,942 afterwards; paid in 18 monthly payments, first payment due at registration
Syllabus / Registration	AI Essentials for Work syllabus (Nucamp) • Register for AI Essentials for Work (Nucamp)

“When a vendor delivers an ‘AI-powered' software solution, the responsibility for its performance, fairness and risk still rests with the deploying business.” - Adam Stone, AI Governance Lead (VKTR)