<?xml version="1.0" encoding="UTF-8"?><rss xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:atom="http://www.w3.org/2005/Atom" version="2.0">
    <channel>
        <title><![CDATA[AI for Banking - Tools]]></title>
        <description><![CDATA[Find what banks, credit unions, and fintechs have done with AI — with actual results.]]></description>
        <link>https://aiforbanking.org?utm_source=aiforbanking.org&amp;utm_medium=rss</link>
        <generator>RSS for Node</generator>
        <lastBuildDate>Thu, 30 Jul 2026 14:05:29 GMT</lastBuildDate>
        <atom:link href="https://aiforbanking.org/rss/tools.xml" rel="self" type="application/rss+xml"/>
        <pubDate>Thu, 30 Jul 2026 14:05:29 GMT</pubDate>
        <copyright><![CDATA[2026 AI for Banking]]></copyright>
        <language><![CDATA[en]]></language>
        <ttl>14400</ttl>
        <item>
            <title><![CDATA[Personetics]]></title>
            <description><![CDATA[Personetics is the leading provider of AI-driven personalized financial insights and engagement for financial institutions. Their platform analyzes customer transaction data to surface timely, relevant insights — savings nudges, spending alerts, and product recommendations — delivered through mobile and digital banking channels. Deployed at Truist, BMO, Synovus, Akbank, Erste Group, and dozens of other banks globally, Personetics has delivered over 1 billion personalized insights to banking customers.]]></description>
            <link>https://aiforbanking.org/personetics?utm_source=aiforbanking.org&amp;utm_medium=rss</link>
            <guid isPermaLink="false">https://personetics.com</guid>
            <category><![CDATA[Customer Service]]></category>
            <category><![CDATA[Personalization]]></category>
            <pubDate>Sat, 28 Mar 2026 18:56:04 GMT</pubDate>
        </item>
        <item>
            <title><![CDATA[Posh AI]]></title>
            <description><![CDATA[Posh AI builds conversational AI solutions purpose-built for financial institutions, with deployments at community banks and credit unions across the US. Their virtual assistants handle inbound calls and digital inquiries, resolving routine service requests without human intervention. Published case studies include Citadel Credit Union ($660K saved annually, 1M+ calls handled, +6 NPS), Ion Bank, Camden National Bank, and Freedom First Credit Union ($225K saved, 25K calls/month automated).]]></description>
            <link>https://aiforbanking.org/posh-ai?utm_source=aiforbanking.org&amp;utm_medium=rss</link>
            <guid isPermaLink="false">https://www.posh.ai</guid>
            <category><![CDATA[Customer Service]]></category>
            <category><![CDATA[Process Automation]]></category>
            <pubDate>Sat, 28 Mar 2026 18:56:04 GMT</pubDate>
        </item>
        <item>
            <title><![CDATA[Feedzai]]></title>
            <description><![CDATA[Feedzai is a financial crime risk management platform that uses machine learning to protect banks and payment processors from fraud and money laundering. Their RiskOps platform analyzes transactions in real time, combining behavioral analytics, device intelligence, and network analysis to detect fraud with documented results including a 64% fraud reduction at CoreCard and deployments at TBC Bank and multiple global financial institutions.]]></description>
            <link>https://aiforbanking.org/feedzai?utm_source=aiforbanking.org&amp;utm_medium=rss</link>
            <guid isPermaLink="false">https://feedzai.com</guid>
            <category><![CDATA[Fraud Detection]]></category>
            <category><![CDATA[AML & Compliance]]></category>
            <pubDate>Sat, 28 Mar 2026 18:56:04 GMT</pubDate>
        </item>
        <item>
            <title><![CDATA[Zest AI]]></title>
            <description><![CDATA[Zest AI builds explainable machine learning models for credit underwriting that help lenders approve more creditworthy borrowers while reducing default rates. Their platform is deployed at banks and credit unions including First Hawaiian Bank, StagePoint FCU, Trius FCU, and Truliant FCU. Zest AI's models incorporate alternative data alongside bureau data to identify creditworthy borrowers with thin credit files, expanding lending portfolios while maintaining or improving loss performance.]]></description>
            <link>https://aiforbanking.org/zest-ai?utm_source=aiforbanking.org&amp;utm_medium=rss</link>
            <guid isPermaLink="false">https://www.zest.ai</guid>
            <category><![CDATA[Credit Underwriting]]></category>
            <category><![CDATA[Risk Management]]></category>
            <pubDate>Sat, 28 Mar 2026 18:56:04 GMT</pubDate>
        </item>
        <item>
            <title><![CDATA[Kasisto]]></title>
            <description><![CDATA[Kasisto's KAI banking AI platform powers virtual assistants for retail and commercial banking customers, with deep financial domain knowledge and integration capabilities for core banking systems. Their deployments include Nedbank's 'Enbi' virtual assistant, which reduced live chat volume by 70%, as well as implementations at multiple US and international banks. KAI is designed specifically for financial services with pre-built banking intents, account integration APIs, and regulatory compliance features.]]></description>
            <link>https://aiforbanking.org/kasisto?utm_source=aiforbanking.org&amp;utm_medium=rss</link>
            <guid isPermaLink="false">https://kasisto.com</guid>
            <category><![CDATA[Customer Service]]></category>
            <pubDate>Sat, 28 Mar 2026 18:56:04 GMT</pubDate>
        </item>
        <item>
            <title><![CDATA[Eltropy]]></title>
            <description><![CDATA[Eltropy provides AI voice and chat solutions for credit unions and community banks, with a focus on contact center automation and member service. Published case studies include Cobalt Credit Union (83% AI voice containment rate) and TruStone Financial Credit Union (20% call volume reduction, 46% of conversations handled entirely by AI). Their platform combines conversational AI with voice biometrics, appointment scheduling, and deep core banking integrations.]]></description>
            <link>https://aiforbanking.org/eltropy?utm_source=aiforbanking.org&amp;utm_medium=rss</link>
            <guid isPermaLink="false">https://eltropy.com</guid>
            <category><![CDATA[Customer Service]]></category>
            <category><![CDATA[Process Automation]]></category>
            <pubDate>Sat, 28 Mar 2026 18:56:04 GMT</pubDate>
        </item>
        <item>
            <title><![CDATA[Featurespace]]></title>
            <description><![CDATA[Featurespace developed ARIC Risk Hub, an adaptive behavioral analytics platform that creates individual behavioral baselines for each customer and detects anomalous events indicating fraud or financial crime. Deployed at NatWest, HSBC, SEB, and other major financial institutions, Featurespace's approach continuously adapts to evolving fraud patterns without requiring manual rule updates, maintaining detection accuracy as fraudsters change tactics.]]></description>
            <link>https://aiforbanking.org/featurespace?utm_source=aiforbanking.org&amp;utm_medium=rss</link>
            <guid isPermaLink="false">https://www.featurespace.com</guid>
            <category><![CDATA[Fraud Detection]]></category>
            <category><![CDATA[AML & Compliance]]></category>
            <pubDate>Sat, 28 Mar 2026 18:56:04 GMT</pubDate>
        </item>
    </channel>
</rss>