AI in the Banking and Financial Services (BFSI) sector is not a new concept; it dates to the late 20th century when advanced computing power was first utilized for algorithmic trading. However, with the rise of AI’s broader applications, the financial industry is now undergoing a profound transformation, enhancing customer service, managing risks, and offering personalized solutions.
Salesforce Einstein is leading the charge in the BFSI sector by deploying trusted AI solutions for banking, insurance, and wealth management institutions. Leveraging customer data and powered by the Einstein Trust layer, AI helps streamline operations, mitigate risks, and elevate financial services to new levels of efficiency and innovation.
Predictive and Generative AI, with Machine Learning and Natural Language Processing are at the forefront of this revolution. Predictive AI analyzes vast amounts of data like transactional history while Gen AI creates personalized interactions—enabling financial institutions to better manage risks and deliver personalized services at scale. As digital payments rise, customers demand quicker issue resolution, and AI accelerates service delivery, empowering agents to respond faster and boost customer satisfaction. 91% of financial services business leaders believe that generative AI would benefit their organizations. Additionally, AI is transforming how financial institutions handle insurance claims, summarize client meetings, and address banking queries with greater accuracy.
In this blog, we will explore key use cases of AI in the Banking and Financial Services industry.
3 Benefits of AI in Financial Services Industry
Top 5 Use Cases of AI in Banking and Financial Services Industry
AI is revolutionizing industries by transforming the way businesses operate, making processes more efficient, accurate, and customer centric. In the banking and financial services sectors, AI technologies can automate routine tasks, optimize customer interactions, and create smarter, data-driven solutions that drive business growth and improve client satisfaction.
Below are five key use cases of AI in the financial services industry.
1. Streamline Transaction Dispute Resolution
The Challenge: Customer service agents are often overwhelmed with managing multiple disputes calls manually, making the process time-consuming and inefficient. With complaints being lodged across various channels and applications, switching between platforms can further complicate the process.
The Solution: AI analyzes previous transaction data of customers to deliver accurate responses. Generative AI-powered standard prompts automate the process of sending Transaction Dispute Resolution and Dispute Acknowledgement emails. This innovative approach reduces time spent drafting responses, ensuring faster and more accurate resolutions for customers leading to improved efficiency, enhanced customer satisfaction, and a more effective dispute management process.
2. Simplify Client Meeting Preparation
The Challenge: Banking and financial services professionals often waste valuable time reviewing past client conversations and processing emails before preparing for meetings. This routine work hampers productivity and distracts from more strategic, high-value tasks that require their expertise.
The Solution: Einstein AI streamlines meeting preparation by automatically generating concise summaries that capture key points from all previous client interactions. Integrated within Salesforce, AI-driven prompts allow bankers and financial professionals to quickly access these summaries, making it easier to prepare for meetings—whether for Wealth Client Interactions or Business Relationship Plans—saving time and enhancing focus on building stronger client relationships.
3. Effective Claims Management
The Challenge: Claims agents are often overloaded with multiple tasks simultaneously, including managing and processing insurance claims. Juggling these responsibilities can lead to inefficiencies, delays in claim resolution, and an increased risk of errors. This not only impacts agent productivity but also affects customer satisfaction, as clients may experience longer wait times and less personalized service.
The Solution: AI in Financial Services integrates data from various sources, such as claims, claim items, participants, and payments, to provide a comprehensive overview. Leveraging these insights, AI generates concise summaries of customer details, streamlining the claims management process and enabling agents to work more efficiently and accurately.
4. Seamless Complaint Management
The Challenge: Customer complaints come through various channels, such as emails, messages, and call logs, leaving service agents struggling to take effective action due to the lack of direct interaction, which hinders their ability to fully understand the issue and deliver proactive responses.
The Solution: Einstein AI-powered tools in banking and financial services aggregate data from multiple sources, including emails, messages, social media, and other communication channels. Leveraging Natural Language prompts embedded in the dashboard, Generative AI creates concise complaint summaries, simplifying the entire process and significantly reducing response time.
5. Deliver Personalized Interactions
The Challenge: In banking and financial services, data is often scattered across multiple platforms, making it difficult to harness its full potential. This fragmentation leads to a lack of personalized services, which customers increasingly expect.
The Solution: Predictive AI consolidates data from various customer touchpoints, while Generative AI creates concise interaction summaries. With these insights, financial services can craft personalized investment plans for high-value clients. Tailored recommendations also enable banks to streamline business relationship planning, delivering more value-added outcomes and enhancing customer satisfaction.
Conclusion
AI is transforming the banking and financial services industry by enhancing efficiency, personalization, managing claims and complaints, preparing client meetings and managing transactions seamlessly.
Successful AI implementation in the financial sector goes beyond just adopting new technology; it requires a thorough understanding of where AI can add real value. Before diving into AI, it’s essential to assess the specific needs of the industry and identify areas where AI can improve operations, enhance customer experience, and drive better business outcomes. AblyPro’s 3A’s Strategy—Assess, Analyze, Act for AI implementation guides financial services institutions through this transformative journey. Our comprehensive implementation checklist ensures that AI is deployed effectively for maximum impact. Learn more about our AI implementation checklist here.
Ready to elevate your banking/financial services with AI? Let us help you unlock the full potential of AI by creating a tailored roadmap specific to your organization.
Schedule a 1:1 meeting and let’s embark on this transformative journey together.
Author
AVP, AblyPro
Murali is the AVP – Certinia at AblyPro with 12+ years of experience in handling complex Certinia and Salesforce applications, implementations, configurations, and customizations. At AblyPro, he has been the pillar of all the Certinia PSA and ERP project deliverables, ranging from design to implementation, project management, and resource management. With years of practical knowledge and expertise in this industry, Murali supports the sales team in strategizing customer solutions to meet the actual business needs of the clients. Murali is a dynamic and experienced professional with multiple Certinia and Salesforce certifications, helping businesses to technically strive in this ever-changing landscape.
