Introduction
According to a global survey conducted by McKinsey in 2021, 56% of financial institutions have embraced artificial intelligence (AI) in various operational aspects. This survey has shown a profound evolution within the industry, where AI is increasingly recognized as a catalyst for innovation and efficiency.
The rapidly evolving financial services sector has embarked on the Artificial Intelligence (AI) era within the digital evolution, a progression initiated by the internet’s inception and spanning various stages of digitalization. AI’s emergence is disrupting the conventional dynamics of the industry, loosening the ties that bound traditional financial institutions’ components, thereby paving the way for increased innovations and novel operational frameworks.
Evolution of AI in the Banking & Finance Sector
Artificial intelligence (AI) is fundamentally transforming the banking industry by enhancing the quality of products and services offered. It’s not just improving data management and enhancing customer experiences; it’s also simplifying and expediting traditional processes, making them more efficient.
In today’s financial landscape, data has become the most valuable asset for banking institutions. They increasingly recognize the potential of AI and other technologies to offer innovative solutions at lower costs. Banks understand that success no longer solely hinges on asset size but on their ability to harness technology to leverage their data effectively.
Consequently, the performance of banking, financial services, and insurance (BFSI) companies is now measured by their proficiency in utilizing technology to unleash the power of their data. This enables them to develop innovative and personalized products and services that meet the evolving needs of their customers.
“In banking services, various sectors are capitalizing on the potential of this disruptive technology. Below, we outline notable use cases where AI has proven most influential within the BFSI industry.”
Application of AI in the Banking & Finance Sector
AI-powered Chatbots
AI-driven chatbots, integrated with Natural Language Processing (NLP), engage customers around the clock, enriching online interactions. Beyond providing standard responses to customer inquiries regarding account details, these chatbots now assist in account openings and routing complaints to the relevant customer service departments, among other functionalities.
AI-powered Fraud Detection System
In the past, banks relied on conventional rule-based Anti-Money Laundering (AML) transaction monitoring and name screening systems, which frequently generated false positives. However, due to the increasing prevalence of fraud-related crimes and evolving fraud patterns, banks are now enhancing their systems with advanced AI components. These improvements enable the identification of previously unnoticed transactional patterns, data irregularities, and suspicious connections between individuals and entities.
Customer Relationship Management
CRM is important for the banking sector, as it strives to offer personalized services 24/7. This includes features like facial recognition and voice commands for logging into financial apps, catering to individual preferences, and enhancing user experience.
Moreover, banks are harnessing the power of Artificial Intelligence to analyze customer behavior and automate segmentation. This facilitates targeted marketing efforts and fosters improved customer interaction and experience.
Predictive Analytics Integration
The emergence of Machine Learning (ML) and AI has ushered in a new era of precise forecasting and prediction. Through the application of Data Analytics and AI, industries are now able to predict revenue, forecast stock prices, monitor risks, and manage cases more effectively. The vast increase in available data has significantly enhanced the accuracy of these models, leading to a reduction in the need for human intervention over time. Top of Form As regulatory scrutiny on risk management intensifies, financial institutions must develop more robust models and solutions. The adoption of AI in credit risk management is becoming increasingly popular, particularly in the Fintech and Digital Banking sectors.
AI is employed to assess the creditworthiness of borrowers by analyzing data to predict the likelihood of default. This enhances the accuracy of credit decisions, shifting the market towards data-driven lending rather than relying solely on expert judgment. Consequently, there is a greater ability to identify high-risk customers for rejection while minimizing the rejection of creditworthy applicants. This approach also leads to reduced credit losses for financial institutions.
Conclusion
In essence, AI adoption has changed the financial services industry by reshaping the traditional way massively. From customer relationship management to risk assessment and predictive analysis, the age of banking and finance will take new heights with AI-based solutions. Banks will be enabled to further provide services tailored only for the customer, improve their operational efficiency, and assist with better decision-making using machine learning and natural language processing technology.
At Ciklum, we believe strongly in the transformative power of AI and dedicate ourselves to changing the frontiers of financial services with our experience in Experience Engineering. We merge innovative technology with a people-first approach to problem-solving so that we can deliver the best and beyond to our clients. Partner with us to see how Experience Engineering will shake your AI ventures up to be much more intuitive, engaging, and effective. Let's work on this transformation journey together, using AI and Experience Engineering to drive your enterprise to success.
