From your experience, can you provide examples or case studies where AI has led to increased productivity or more efficient work schedules in financial organizations?

At Zennify, we use our in-house LLM called Arti – our internal ChatGPT to help with content creation and internal content discovery. This has increased productivity for our marketing team when creating assets like blog posts, and we’ve optimized our onboarding process by making it easier for new team members to find information. We’re excited to bring these use cases to our customers and have done so with our AI advisory and experimentation solutions.

We are seeing significant productivity gains in back-office operations, specifically for use cases that currently require repetitive labor-intensive tasks with complex compliance-driven workflows. Examples of this include business loan documentation and financial wealth advisory plans. FIs are utilizing AI and data-rich large language models to reduce the amount of work and time it takes to generate documentation and streamline the process workflows.

Digital agility in banks: best practices from customer deployments

Digital agility is a vital aspect of staying competitive in the finance sector. Could you share some best practices or success stories from customer deployments that highlight the importance of digital agility in banks?

One of our clients in the agtech lending space went through a digital transformation journey to impact their lending process. They leveraged Zennify’s expertise in the ecosystem and saw a 2000% increase in revenue, improvements in the customer & employee experience, and ROI on their tech investments.

They shared with us the following best practices: Getting internal commitment from stakeholders, be open to asking for help, and start with a clean slate.

Could you share your personal vision for the future of AI in the financial sector and how it might reshape the industry in the coming years?

I haven’t mentioned ethical AI implementation, which I believe is crucial in the sustainable future of AI in the industry. There will be a growing focus on ethical AI implementation, and recognizing bias considerations to ensure transparency, accountability, and fairness in the algorithms and decision-making process. I also believe that AI will augment human decision-making capabilities. Good data foundations lead to useful AI outputs that provide comprehensive data analysis and insights – enabling quicker, more informed decision-making in investments, risk management, and customer service. Overall, the future of AI in the financial sector will revolutionize how financial services are delivered, making them more personalized, efficient, secure, and accessible. It will transform the industry into a more customer-centric, technologically advanced, and inclusive landscape.

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