Generative AI (GenAI) is currently experiencing a surge in popularity, with many organizations across various industries seeking ways to harness its potential value.
According to McKinsey’s projections, GenAI could contribute a remarkable $2.6 to $4.4 trillion to the global economy. Banking emerges as the industry with the most significant potential impact on revenue percentage, as highlighted in their report.
This presents numerous opportunities for enhancing efficiency and productivity in credit customer journeys. Accenture’s recent risk study indicates that 95% of executives believe GenAI will necessitate a modernization of their organization’s technology architecture.
Currently, organizations are exploring GenAI’s potential through targeted process adjustments and incremental technical improvements. However, to fully leverage GenAI in credit customer journeys, organizations must identify transformative use cases that align closely with their business objectives. These use cases may include:
Precision customer targeting strategies
Chatbots for sales and marketing: GenAI can streamline lending processes by providing 24/7 support, personalized assistance, and prompt responses to customer inquiries, making them more efficient and customer-friendly.
Natural language processing (NLP) for data analysis: By combining NLP models with GenAI, organizations can analyze unstructured data like customer feedback, news articles, and social media to gain insights into public sentiment and emerging market trends, informing their targeting strategies.
Customer acquisition and onboarding
Risk assessment: GenAI can automate lending processes by analyzing borrowers’ credit reports, income statements, tax returns, transaction history, and other financial data.
Data generation for training: GenAI can help generate synthetic data for training machine learning models, particularly in scenarios where real data is sensitive and subject to privacy regulations.
Robust fraud prevention
Fraud detection and prevention: GenAI can identify patterns of fraudulent activities in real time, analyze large datasets to detect unusual transaction patterns, or provide natural language descriptions of potential fraud alerts for fraud analysts.
Enhanced security: GenAI can enhance security in internet and mobile banking through biometric authentication, voice recognition, and facial recognition.
Enhanced customer operations
Virtual assistants: GenAI-driven chatbots can offer quick and accurate responses to frequently asked questions, assisting customers with account inquiries, transaction history, and basic banking tasks.
Automated document generation: GenAI can automate the generation of paperwork such as contracts, statements, and reports, reducing errors and saving time.
Personalized customer management
Personalized collector scripts: GenAI can create personalized scripts for collectors, increasing productivity by optimizing their time usage and enhancing customer experience through personalized communication.
Personalized repayment plans: GenAI can provide personalized recommendations for refinancing or settlement options based on a borrower’s financial history and payment behavior.
