Chime

A reporting-period timeline of the company’s AI and machine-learning disclosures, grounded in official investor materials and exact source excerpts.

Products and use casesRisk and governanceAI strategyProductivity and efficiency

Use-case evidence

AI use cases in official disclosures

Each row is a distinct, evidence-linked use case or initiative identified in official results and investor materials. Expand a row’s evidence to inspect the exact source wording.

4 verified use cases

Newest disclosure first

Products and use casesContinuing

AI and ML models leverage member data for liquidity product underwriting

Chime's risk models for its liquidity products (such as SpotMe, MyPay, and Instant Loans) utilize AI and ML algorithms to analyze historical transaction data, platform engagement, and credit bureau data to manage fraud, credit, and financial crimes risk.

7 May 2026Quarterly reportSEC EDGAR

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“The risk models used for the liquidity products offered through our platform leverage AI and ML models along with comprehensive member data, including information regarding a member’s historical transaction and engagement activity through Chime, as well as traditional and alternative credit bureau data and other external data sources.”

Context: Risk Factors

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Risk and governanceContinuing

Evolving fair-lending and consumer protection laws threaten AI credit models

The application of fair-lending and consumer financial protection laws, such as the Equal Credit Opportunity Act and Regulation B, to AI/ML credit risk models remains subject to evolving interpretation by regulators, which may require model modifications, reduce product flexibility, or increase compliance costs.

7 May 2026Quarterly reportSEC EDGAR

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“For example, the application of existing fair-lending and consumer financial protection laws, including the Equal Credit Opportunity Act and Regulation B, to credit risk models that use alternative data, automated decision-making, or AI and ML remains subject to evolving regulatory interpretations.”

Context: Risk Factors

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AI strategyExpanding

AI and automation targeted to drive long-term cost efficiencies

Chime expects its member support and operations, sales and marketing, and technology and development expenses to decrease as a percentage of revenue in the long term as the company scales and drives operational efficiencies using AI and automation.

7 May 2026Quarterly reportSEC EDGAR

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“As a percentage of revenue, we expect that member support and operations expenses will fluctuate from period to period in the near term and decrease in the long term as we scale and continue to drive operational efficiencies, including through the use of AI and automation.”

Context: Management's Discussion and Analysis of Financial Condition and Results of Operations, Section: Component of Results of Operations

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Productivity and efficiencyExpanding

AI-assisted code development scales to eighty-four per cent of shipped code

Chime's AI-assisted code development adoption increased from approximately 29% to 84% of shipped code within a four-month timeframe. This change has increased product velocity and supported operating leverage by raising output levels without increasing headcount.

6 May 2026Investor presentationSEC EDGAR

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“AI-assisted code development has scaled from about 29% to 84% of code shipped in just four months, significantly increasing product velocity.”

Context: Deploying AI across Chime section

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Use case or initiative	Area	Direction	Disclosed	Evidence
AI and ML models leverage member data for liquidity product underwriting Chime's risk models for its liquidity products (such as SpotMe, MyPay, and Instant Loans) utilize AI and ML algorithms to analyze historical transaction data, platform engagement, and credit bureau data to manage fraud, credit, and financial crimes risk. Read exact evidence “The risk models used for the liquidity products offered through our platform leverage AI and ML models along with comprehensive member data, including information regarding a member’s historical transaction and engagement activity through Chime, as well as traditional and alternative credit bureau data and other external data sources.” Context: Risk Factors	Products and use cases	Continuing	7 May 2026Quarterly reportSEC EDGAR	Open
Evolving fair-lending and consumer protection laws threaten AI credit models The application of fair-lending and consumer financial protection laws, such as the Equal Credit Opportunity Act and Regulation B, to AI/ML credit risk models remains subject to evolving interpretation by regulators, which may require model modifications, reduce product flexibility, or increase compliance costs. Read exact evidence “For example, the application of existing fair-lending and consumer financial protection laws, including the Equal Credit Opportunity Act and Regulation B, to credit risk models that use alternative data, automated decision-making, or AI and ML remains subject to evolving regulatory interpretations.” Context: Risk Factors	Risk and governance	Continuing	7 May 2026Quarterly reportSEC EDGAR	Open
AI and automation targeted to drive long-term cost efficiencies Chime expects its member support and operations, sales and marketing, and technology and development expenses to decrease as a percentage of revenue in the long term as the company scales and drives operational efficiencies using AI and automation. Read exact evidence “As a percentage of revenue, we expect that member support and operations expenses will fluctuate from period to period in the near term and decrease in the long term as we scale and continue to drive operational efficiencies, including through the use of AI and automation.” Context: Management's Discussion and Analysis of Financial Condition and Results of Operations, Section: Component of Results of Operations	AI strategy	Expanding	7 May 2026Quarterly reportSEC EDGAR	Open
AI-assisted code development scales to eighty-four per cent of shipped code Chime's AI-assisted code development adoption increased from approximately 29% to 84% of shipped code within a four-month timeframe. This change has increased product velocity and supported operating leverage by raising output levels without increasing headcount. Read exact evidence “AI-assisted code development has scaled from about 29% to 84% of code shipped in just four months, significantly increasing product velocity.” Context: Deploying AI across Chime section	Productivity and efficiency	Expanding	6 May 2026Investor presentationSEC EDGAR	Open

Official document coverage2 checked

Quarterly report7 May 20263 findings

Chime quarterly report filed 7 May 2026

Primary source

Investor presentation6 May 20261 finding

Chime results filing filed 6 May 2026

Primary source