Published on October 29, 2023, 8:35 pm
The adoption of artificial intelligence (AI) in the banking industry is on the rise, according to a recent Gartner report titled “Emerging Tech Impact Radar: Artificial Intelligence in Banking.” The report reveals that 67% of surveyed banking institutions are currently leveraging AI in their operations. This technology has proved to be beneficial in various use cases within the industry.
One of the key advantages of AI adoption in banking is its ability to enhance automation efforts and drive efficiency. By automating certain processes, banks can streamline operations and reduce manual workloads. This not only saves time but also increases accuracy and reduces the risk of errors. Additionally, AI-powered automation can help improve customer service by providing quicker responses to queries and resolving issues promptly.
Another area where AI brings significant value is data analytics. By utilizing AI algorithms, banks can gather and analyze vast amounts of data to make data-driven decisions. This enables them to gain valuable insights into customer behavior, preferences, and patterns, allowing for personalized services and targeted product offerings. Furthermore, AI helps reduce operating costs by optimizing resource allocation based on real-time data analysis.
In November 2022, OpenAI launched ChatGPT, a language model that sparked immense interest across various industries and users worldwide. In banking, ChatGPT has shown potential for enabling human-like virtual assistants and improving customer service experiences. However, financial institutions are left wondering what lies ahead on the journey towards democratization of AI.
Jan Cenkr, the Group Chief Information Officer (CIO) of Home Credit, acknowledges that technological advancements have transformed financial services over the years. With big data and AI capabilities, financial institutions now have enhanced data modeling scoring techniques that allow them to leverage personalized information for developing better products for customers. Cenkr also emphasizes how automation can optimize field collection processes for call centers by introducing higher-quality human-like chatbots or voice bots.
When it comes to specific use cases for AI and big data in financial services, Cenkr highlights a few areas. Data collection for call center activities can be optimized through the application of big data and AI techniques. This enables field collectors to plan their transportation routes more efficiently, resulting in better productivity and reduced costs.
Another valuable use case is leveraging customer behavior data for targeted product offerings. By analyzing customer behavior, banks can expand their product portfolios and introduce new offerings that cater to customers’ specific needs. This not only benefits the bank by diversifying its revenue streams but also enhances the customer experience by introducing them to previously undiscovered products.
In terms of digital adoption, Cenkr points out that legislation plays a crucial role. While Europe has established solid data protection regulations, Asian markets are rapidly catching up. The Philippines stands out as one of the most advanced countries when it comes to digital adoption among emerging markets. It is essential for companies operating across different regions to understand and adapt to varying consumer habits and preferences.
When adopting emerging technologies like AI, Cenkr advises maintaining good cybersecurity practices and safeguarding sensitive data, especially when dealing with big data or AI models that aggregate vast amounts of information into one place. He suggests focusing on one or two digital transformation initiatives at a time instead of attempting too many at once. This allows organizations to test ideas incrementally and identify what works best for their specific context.
Cenkr acknowledges that regulations can sometimes impede the adoption of emerging technologies but believes it is necessary to engage in productive dialogues with governments and regulatory bodies. These discussions help in explaining the benefits of AI and enabling trials to find balanced legislation that yields mutual benefits.
As for the growing influence of ChatGPT and large language models (LLMs), Cenkr mentions how Home Credit has used chatbots and voice bots in their call centers over the years. Technology has advanced so much that it becomes challenging to distinguish between human agents and these bots. This trend will continue evolving, and new innovations will surely be developed to further improve customer interactions.
The role of the CIO has significantly evolved in recent years. Initially perceived as operating in isolation, IT teams are now integral parts of all business discussions, from product development and strategy to marketing. Technological advancements have made it essential for CIOs to align IT with business objectives and help companies achieve their goals by leveraging emerging technologies effectively.
For CIOs and other executives looking to drive digital adoption in Asia’s emerging markets, Cenkr advises focusing on perseverance and taking small steps forward. Trying to digitalize everything simultaneously can lead to failure. Therefore, it is crucial to prioritize areas of focus and implement digital transformation initiatives gradually.
In conclusion, AI adoption in the banking industry is increasing rapidly, bringing numerous benefits such as enhanced automation, improved customer service, reduced operating costs, data-driven decision-making, and personalization. Companies like Home Credit are leveraging AI technologies like ChatGPT to improve call center operations and provide more human-like customer experiences. However, it is crucial for financial institutions to navigate regulatory environments effectively while driving digital adoption. The role of the CIO has evolved