Consumers today expect their banking service provider to meet them where they are. Both retail and enterprise customers are growing increasingly comfortable with all things digital, making the legacy banking system seem woefully inadequate.

In addition to sustainability challenges, the banking and financial services industry has been upended by new entrants. Embedded finance offerings and novel platform-based models popularised by new-age financial players are making customers accustomed to the hyper-personalised experience. In their banking interactions at both physical and digital touchpoints, customers now expect minimal friction and seamless experience

AI can play a key role in helping traditional financial institutions to drastically improve their customer insights and deliver superior, hyper-personal experiences. Relying on such exponential technologies can equip incumbents with the kind of ecosystem capabilities, data, and insights on their customer’s individual financial situations. This can help guide personalisation strategies to improve customer engagement. Technology infuses the vital element of scale into personalised experiences.

Many financial institutions are striving to become virtual enterprises. Here, advanced data science and emerging technologies such as process mining, neural networks, and swarm intelligence together help fast-track innovation. As these enterprises rely heavily on information and discovery, the way they leverage their data will be crucial to creating highly relevant personas and empathy maps that strongly link back to the customer. Another effective way to personalise is by designing for trust wherein the customer determines how their data is to be accessed and used and is at liberty to opt out as they see fit.

Converting data to actionable insights

Data and AI together can help accelerate productivity and innovation. There are several AI use cases for financial institutions that enable personalised experiences using data. These include:

Reduction in risk of identity fraud by verifying and authenticating customer documents submitted as part of the digital know-your-customer (KYC) process.

Summarisation of call-centre interactions, documents, financial reports, analyst articles, emails, news, media trends to capture the most meaningful and relevant information.

Development of conversational knowledge based on reviews, knowledge base, product descriptions and more.

Content creation of personas, user stories, synthetic data, images, personalised UI, marketing communications, etc.

Personalised wealth management and payment journeys enabled through super-wallet apps.

With generative AI, the capabilities of traditional AI and analytics go up several notches. For instance, it can elevate the entire digital experience for customers. We saw this at a large global payments company, which used generative AI to extract actionable insights based on the millions of complaints they had been receiving. They replaced their laborious, ineffectual manual approach for complaint analysis with a generative AI model that cut the effort to less than 15 minutes, dramatically down from the previous 3-week period. Besides, they could now categorise in greater detail with over 90 per cent accuracy, extract keywords, recognise intentions, and more to help improve the quality of service rendered to individual customers.

Here, the true power of generative AI comes to the fore as it drives business value by enabling new business models, speeding up the time to market, and one-to-one experiences at scale. It can unlock business and human potential at scale when properly tailored to suit the business needs of financial institutions.

Looking ahead

The benefits of AI are clear. A large global bank could better the accuracy of its conversational AI by 25 per cent in addition to substantially improving testing and classification. We expect financial institutions across the board to become AI-centric and characterised by their use of generative AI technologies, digital and software innovation, as well as design-led and AI-first workflows.

Today’s foundation models, generative AI, and advanced analytics signify AI’s remarkable progress over the past decade, allowing for scalability and customer obsession like never before in the financial services domain. As financial institutions continue to sharpen their focus on superior customer engagement as a key differentiator, they must increasingly rely on AI to shape their offerings and future-proof their businesses.

The writer is Managing Partner, IBM Consulting India & South Asia

Related Topics
comment COMMENT NOW