Alkami

Predictive models tag account holders by likely loan adoption, deposit growth and attrition risk, and fraud tools use machine learning, behavioral biometrics and anomaly detection. Strip those out and account opening, digital banking and the campaign tools still run, so the models sharpen a platform rather than carry it.

Fraud detection is described as stopping suspicious activity early, with no threshold, review queue or override path published for flagged sessions or payments. On the marketing side, model outputs arrive as data tags that staff use to build campaigns, so a person decides who is contacted and with what offer, and voice activated transactions hand off to live agents when needed.

Accuracy, validation and monitoring figures for the predictive models go unpublished, beyond the claim that they are purpose built for the financial industry. What Alkami does state is more than fifteen years of data modeling and analysis for regional and community banks and credit unions.

Gate City Bank, live since September 2024 on a Fiserv DNA core, reports a 63 times average return on the data and marketing solution over the last year, 61 percent more average monthly logins than on its previous platform, about 20 percent more digital banking users and retail accounts opened in 4.65 minutes on average, in a case study Alkami published in September 2026 and announced on September 29.

The same bank grew its treasury automated clearing house origination customers by 47.7 percent without adding staff, and through BioCatch in Alkami's partner ecosystem reached a 97 percent account takeover capture rate, deterring about $650,000 in fraud losses over six months.

Alliant Credit Union raised $500 million in deposits in six months with MANTL, more than half of Texoma's members adopted its new digital banking within two weeks, and Altra Federal Credit Union and Capital Credit Union are quoted on the engagement and cross sell models finding account holders their own lists had missed.

Whether one institution's account holder data trains models used for another, and how that data is bounded, is not addressed. The models draw on what Alkami calls proprietary insights from billions of transactions, plus the enriched first party data it produces for each institution.

The privacy policy covers information collected through Alkami's website, with retention tied to the purpose of collection, sharing with contracted service providers and rights to review, correct or delete. Account holder data inside the platform, including the transaction data that feeds its predictive models, falls outside that policy.

Security is described as a multi layered framework covering infrastructure, applications and data, with credential stuffing defense, continuous monitoring and phishing takedown offered to institutions, though no audit report or certification for Alkami's own operations is named alongside it.

Alkami supplies software to licensed banks and credit unions and states no regulatory position of its own. Its predictive models are described as purpose built for the financial industry to satisfy regulatory requirements, without naming the requirement or the supervisory guidance they meet.

Fairness statements, testing methods and a governance process are all absent for the models. Loan cross sell, deposit growth and attrition models decide which account holders see which offers, a targeting surface with fair lending relevance, while behavioral biometrics screen sessions for fraud.

Who bears the loss when a fraud model blocks a legitimate account holder or misses a fraudulent payment is unaddressed, and no route is described for an account holder to contest a flag.

Alkami names no provider for its predictive models and publishes no subprocessor list. Those models run on the enriched first party data it produces for each institution and on its own transaction insights. On the fraud side, at least one supplier is named: Gate City Bank's account takeover results came through BioCatch, a partner in Alkami's ecosystem.

Gate City Bank runs Alkami with a Fiserv DNA core, and MANTL supports 25 of the leading core systems. A software development kit, interface components and interfaces connect the platform to customer relationship management, loan origination and enterprise systems, data leaves by interface or batch extract into business intelligence tools, and a curated partner ecosystem supplies pre integrated fintech solutions, fraud monitoring tools among them. Connexus Credit Union built custom features on the kit and reports a return within three months.

Where the platform runs, in which regions and under what residency terms is not described, a gap for institutions whose examiners ask where account holder data sits.

Buying starts with a demo request. Price, tiers and the unit of charge for the platform and its data and marketing solution are unpublished, so cost becomes known only in a sales conversation.

Banks and credit unions each have their own material, and retail, small business and commercial account holders each get their own banking and onboarding products. Regional and community institutions are the buyers, from digital only Quontic Bank to credit unions such as Texoma and Raiz.