Real-World Case Studies and Customer Success Stories with H2O Driverless AI

H2O. ai helped CBA cut scam losses by 70% using real-time generative AI. The bank trained over 900 analysts and...reduced fraud by 30%. CBA used thousands of AI models on billions of data points to improve customer service and safety. AI powered solutions like real-time fraud detection, bills sense, and benefits finder. CBA saw a 76% drop in scam losses from their 2022 peak.
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Document AI from H2O. ai helps Commonwealth Bank of Australia process millions of documents daily. The bank uses Document AI...to automate KYC, credit assessment, and invoice processing. Automation accuracy now reaches 50-85% on different document types. This reduces manual work and speeds up customer onboarding. The solution unlocks value from unstructured data and improves operational efficiency.
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H2O Driverless AI helped Visión Banco cut model build time from 6 months to less than a week. The bank used... the platform to improve credit risk scoring and customer churn prediction. With H2O, Visión Banco doubled its customer propensity to buy rate. The solution increased model accuracy and led to higher revenue. Data scientists at the bank now deploy models faster and with better results.
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Commonwealth Bank of Australia partnered with H2O. ai to boost its AI capabilities. The bank can now scale machine learning...across the organization. Model prototyping time dropped from weeks to just 2 days. CBA uses AI to deliver personalized offers and predict bills for customers. The partnership helps customers manage finances and reduce energy use. CBA aims to be a leader in AI-powered banking services.
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H2O. ai helped Commonwealth Bank of Australia use real-time Generative AI to fight fraud. CBA built a customer engagement engine...with thousands of models running over billions of data points. The solution improved service experience and decision-making. CBA saw a 30% reduction in fraud and a 70% reduction in scam losses. Over 900 H2O.ai analysts were trained, supporting more than 16 million customers.
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AT&T used H2O. ai to cut iPhone fraud by over 80%. The company saved $7M per year by predicting truck...battery failures and reducing breakdowns. Route optimization models built with H2O.ai saved more than $10M annually in fuel costs. AT&T moved from open source to an AI-as-a-Service platform, speeding up AI project delivery. The H2O AI Feature Store helped teams build faster, more accurate models. AT&T now runs many AI projects across its business units.
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AT&T used H2O. ai's small language models to transform its call center operations. The company achieved 90% lower costs and...3x faster processing. AT&T improved latency by 75% and increased scalability by 5x. The solution delivered 91% accuracy, matching previous expensive models. H2O Danube and LLM Studio enabled efficient, AI-powered customer service at scale.
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H2O LLM Studio helped AT&T fine-tune a small language model for text-to-SQL tasks. The CDO Office team wanted a tool... for non-technical users to get database insights using plain English. They needed high accuracy and lower costs. Fine-tuning with H2O LLM Studio cut costs, improved query speed, and matched the performance of larger models. The new solution is nearly free to use, replacing a system that cost two cents per call. AT&T achieved higher customization, accuracy, and faster decision making.
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AT&T used H2O LLM Studio to help non-technical users query databases using plain English. The team needed to identify new... and existing customer opportunities with high accuracy. High costs of large language models were a challenge. By fine-tuning a smaller model with H2O LLM Studio, AT&T cut costs and kept performance high. The solution improved decision speed and made insights more accessible.
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AT&T used H2O. ai’s generative AI to transform its call center operations. The company processes 15 million customer calls each...year. By deploying fine-tuned small language models, AT&T cut costs by 90%. The new solution improved processing speed by 3x and reduced latency by 75%. AT&T achieved 91% accuracy in classifying customer interactions, closely matching previous solutions at a fraction of the cost.
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G5 used H2O Driverless AI and AWS to improve lead scoring for real estate marketing. The company processed 100,000 call... transcripts to build machine learning models. Lead scoring accuracy rose to over 95%, up from 14%. Model development time dropped by 80%. One customer saved $500,000 each year. Leasing agents now connect with qualified leads 85% of the time.
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H2O Driverless AI helped AIMIA cut machine learning model development time in half. AIMIA used the platform to power its... SmartJourney methodology for customer engagement and loyalty. The solution delivered a 700% increase in campaign cost savings and an 11% boost in ROI for AIMIA's clients. Predictive churn models let AIMIA's customers act early to prevent churn. The platform also improved transparency and trust in AI for business teams.
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H2O. ai helped Epsilon improve its Abacus data Coop platform with machine learning. Epsilon used H2O.ai to build custom models...for over 3,000 brands, boosting direct mail response rates by 3-5%. This led to an average of 15,000 more highly relevant customers per campaign. Epsilon's clients saw over $9 million in incremental revenue. The solution allowed Epsilon to better tie advertising costs to revenue and deliver stronger marketing ROI.
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H2O. ai helped Epsilon improve its marketing campaign results. Epsilon used H2O.ai to build over 100,000 machine learning models a...year. This led to a 3-5% increase in direct mail response rates. Epsilon found 15,000 more relevant customers per campaign. One campaign drove $9 million in extra revenue. The solution also improved model transparency and compliance.
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Deserve used H2O Driverless AI to improve credit scoring for underserved populations. The company built fraud detection, self-scoring, and underwriting... models using alternative data sources. Model development time dropped from months to weeks. Explainability features helped meet regulatory requirements. The data science team increased productivity and trust in machine learning models.
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Airvantage used H2O Driverless AI to improve its risk scoring for airtime advances. Before, Airvantage relied on static business rules... that often declined good customers. The team trained a new model using real customer data. They evaluated over 30 data science platforms and chose H2O Driverless AI for its strong integration. This helped Airvantage reduce false negatives and make better credit decisions.
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H2O Driverless AI helped Acordo Certo retire over $10M in consumer debt per month. The platform reduced model development time... by 70%. Model accuracy improved to nearly 80%. Acordo Certo expanded partnerships with retail and banking firms. The AI solution made debt collection faster and more accurate. The team used machine learning interpretability to build trust with partners.
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