A Framework for AI Opportunity in Financial Institutions AI is no longer a future-facing technology — it’s a present-day differentiator. Across banking, AI is reshaping how financial institutions operate, compete and deliver value. From marketing to compliance, the most promising AI use cases in banking help organizations improve decision-making, reduce operational risk and grow more efficiently. This article explores a sample of opportunities where AI creates the most value today by showing major areas of banking where artificial intelligence (either predictive or generative) can be useful. It also explains how financial institutions can safely begin or accelerate their AI journey and Examples of Current AI Applications Across Banking There are two primary forms of AI driving transformation: predictive AI, which forecasts outcomes and detects patterns, and generative AI, which creates new content from existing data sources. Current applications of artificial intelligence across banking fall into six core areas of opportunity, described below along with examples of how financial institutions are already benefiting from AI on these fronts: 1. Marketing and Sales AI enables personalized engagement and smarter targeting for bank and credit unions’ marketing and sales. ○ Predictive models forecast customer lifetime value. ○ Generative tools create hyper-personalized messaging and offer recommendations. ○ AI segments audiences for cross-sell campaigns and streamlines onboarding. For example, a large national bank reported that personalizing content on its mobile phone apps helped increase engagement rates by 25%. AI Use Cases in Banking A ROADMAP TO SMARTER DECISIONS AND STRONGER OUTCOMES By Sriram Tirunellayi, Director of Applied AI, Abrigo 2. Prospecting and Onboarding AI can reduce friction in early-stage customer interactions for banking services. ○ Automate document verification and identity validation. ○ Prepopulate onboarding forms and streamline KYC workflows. ○ Use chatbots for initial data collection and customer guidance. Costs to verify investment bank clients are down 40% where AI is being deployed across the workflow, according to a large national bank. 3. Credit Risk Underwriting and Review AI enhances accuracy and speed in credit decisions, helping lenders make good decisions quickly. ○ Predictive models analyze cash flow, credit scores, and risk thresholds. ○ Generative AI assists in drafting credit memos and narrative summaries for loan reviews. ○ Real-time data integration supports more holistic, dynamic underwriting. A bank in Texas reduced its commercial loan process for certain loans from two weeks to three to five days using Abrigo’s loan origination for smaller commercial loans, which automates decisioning and features AI-powered loan scoring. And Abrigo’s Loan Review Assistant allows credit risk review staff to evaluate credit quality and document insights in minutes rather than days. 4. Operations Financial institutions can improve back-office efficiency with AI automation. ○ AI routes payments, classifies documents, and extracts insights. ○ Automated financial spreading saves hours of manual entry. ○ Collections strategies are optimized through borrower-level pattern recognition. NVIDIA’s latest survey of financial institutions’ use of AI found that more than 60% of respondents credited AI with helping reduce annual costs by 5% or more. Colorado Banker 16
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