FinTechHyper-Personalisation: Reshaping Banking Dynamics

April 12, 20240


In the era of digital advancement, the saying ‘data is the new oil’ holds particular significance in the banking industry as well. However, the effectiveness of utilizing vast amounts of data to drive sustainable business outcomes increasingly articulates on hyper-personalization. This approach, leveraging data analysis and digital tools, tailors services to align with each customer’s distinct characteristics, leading to more meaningful interactions.

Unlike traditional customer segmentation, hyper-personalization delves into individual behaviours, preferences, and requirements, representing a significant shift in customer engagement from mere banking transactions to promoting financial well-being. This redefines the banking experience for the digital age.

Worldwide, the banks are elevating their standards in hyper-personalization by providing personalized financial guidance and resources to their customers. This strategy not only assists customers in making informed financial choices but also solidifies the bank’s position as a trusted advisor.

In India, the banking sector is undergoing a notable transformation, primarily driven by fintech firms evolving hyper-personalization in their services. The implementation of the Account Aggregator framework in India offers banks an opportunity to leverage analytics across diverse data sources, including internal and external data such as credit bureau information, while ensuring utmost respect for customer privacy. By obtaining explicit consent from customers for data collection, banks can ensure transparency and foster trust while delivering highly tailored experiences that cater to individual preferences and needs.

Integrating hyper-personalization with digital initiatives like Aadhaar and UPI could significantly advance financial inclusion and empowerment in India. This collaboration has the potential to offer customized financial services to different population segments, effectively addressing existing gaps in the financial system.


Hyper-personalization represents the recent evolution in digital banking, and major banks globally are already accepting it. This approach utilizes data analytics and artificial intelligence (hereinafter referred to as “AI”) to provide individualized banking experiences tailored to each customer. It entails comprehending the specific requirements and preferences of each customer and utilizing this knowledge to provide them with the most suitable products and services, delivered at the optimal time and through preferred channels.


1. Demand for Immediate Service: In the age of platforms like Netflix, Spotify, and Amazon, consumers have grown accustomed to receiving personalized recommendations without actively searching them. These expectations now extend to everyday activities, particularly in banking transactions. Instant credit scoring and approval, personalized payment options adjusted in real-time based on individual profiles and behaviours, have become essential for customer retention and to elevate their banking and payment experiences.

2. Integration of Client-Centric Algorithms: Consumers have become accustomed to accessing tailored services and products that align with their habits and expectations. Whether it is in music apps or online shopping, algorithms and machine learning have eliminated the need for clients to initiate searches from scratch. Instead, they are frequently presented with pre-customized products and services that cater to their typical needs. Recognizing this shift, banks now realize the importance of offering not just products or services, but establishing genuine relationships where customer effort is minimized.

3. Open Banking: When customers are willing to share their data with banks and grant them control over it, which is the case for many as it promises improved services, Open Banking emerges as a prime enabler of hyper-personalization. According to research conducted, challenger banks, whose business model heavily relies on Open Banking and the extensive availability of customer data, boast the highest level of customer loyalty.

4. APIs Revolution: Application Programming Interface (hereinafter referred to as “APIs”) drive hyper-personalization in banking by integrating various data sources, providing insights into customer behaviours and preferences in real-time. They enable personalized services, collaboration with fintech, and third-party apps for tailored financial advice and improved user interfaces. Moreover, APIs automate personalized marketing and enhance customer support with AI tools. Essentially, APIs empower banks to swiftly adapt, delivering customized experiences to meet each customer’s needs.

5. Establishing Brand Differentiation: Banks are currently contending with a new type of competition, often specializing in a single product or service. These competitors excel in customer experience, leveraging their focused offerings to enhance brand image and success. To navigate this shifting landscape, banks must carve out their niche. Hyper-personalizing services can be instrumental in this regard, elevating customer satisfaction to unprecedented levels and fostering client advocacy, thereby strengthening the bank’s position in the evolving ecosystem.


 Banks aiming for hyper-personalization in their product offerings must navigate three critical milestones:

1. Know Your Customer (KYC) Enhancement: Banks need to re-examine their approach to gathering client information, leveraging various data sources including basic account details, account activity, contact information, marketing preferences, third-party data, demographics, and web-browsing history. By integrating insights from social media, past interactions, transactions, and payments data, banks can create a comprehensive customer profile.

2. Three Levels of Customer Insights:

3. Descriptive Insights: Focus on understanding “what,” “where,” and “when” of consumer behaviour to engage clients at fortunate moments, such as offering mortgage or car loans when they are most likely to make such purchases.

4. Diagnostic Insights: Utilize analytics to delve into the “how” and “why” of customer behaviour, employing Machine Learning (hereinafter referred to as “ML”) and AI models to pinpoint root causes and improve decision-making.

5. Predictive Insights: Anticipate future customer needs and preferences by understanding from descriptive and diagnostic insights, ensuring personalized offerings that cater to individual or group preferences.

Through these milestones, banks can navigate the road to hyper-personalization, enhancing customer satisfaction and establishing themselves as trusted financial partners.


i. Real-time Customer Engagement: Hyper-personalization enables banks to interact with customers in real-time, offering solutions tailored to their specific needs and preferences, effectively segmenting their client base to allocate value appropriately.

ii. Enhanced Service and Product Transparency: By leveraging insights derived from data and analytics, banks can improve the transparency of their services and products, ensuring clients have a clear understanding of what is being offered.

iii. Reduced Churn Rate and Increased Client Attraction: Personalized approaches can lead to a decrease in customer churn rates and an increase in attracting new clients, as tailored offerings are more likely to meet individual needs and preferences, fostering stronger relationships with the customers.

iv. Encouraging Profitable Customer Behaviours: Hyper-personalization encourages customers to engage in behaviours that contribute to profitable relationships for the bank, such as increasing account balances and deposits, thereby improving overall financial health.

v. Enhanced Efficiency and Cost Reduction: By streamlining processes and leveraging digital technologies, hyper-personalization can increase operational efficiency and reduce costs associated with manual transaction handling and paperwork.

vi. Identification of Non-Profitable Relationships: Data-driven insights allow banks to identify and evaluate relationships and products that are not financially viable, enabling them to optimize their strategies by discontinuing unprofitable offerings or partnerships.

vii. Revenue Growth and Enhanced Brand Image: Ultimately, hyper-personalization can lead to increased revenue through improved customer satisfaction, retention, and acquisition. Additionally, delivering personalized experiences can enhance the bank’s brand image, positioning it as innovative and customer-centric in the eyes of consumers.


 In order to balance hyper-personalization and privacy, businesses should adopt the following key principles:

1. Transparent Data Collection: Clearly communicate data practices to customers.

2. Consent: Obtain explicit consent for data collection and personalization efforts.

3. Robust Security Measures: Implement strong data security protocols.

4. Anonymization Techniques: Protect privacy while deriving insights from data.

5. Compliance with Regulations: Adhere to relevant data protection laws such as Digital Personal Data Protection Act, 2023.

In India, where privacy awareness is growing exponentially, businesses must ensure transparency, customer control, data minimization, and responsible AI use. Leveraging zero-party and first-party data, contextual personalization, and privacy-enhancing technologies can help achieve personalized yet privacy compliant experiences.

India has been one of the leading countries in Digital Payments. India’s UPI has been adopted by several other countries as well. The Government is working extensively for creating a digitally safe cyberspace with both cyber security and data protection measures.

The Deputy Governor of the Reserve Bank of India, at a Conference for Financial Institution on 23rd November, 2023 had given his views on “Changing paradigms in the financial landscape.”

He highlighted how banking is moving towards a highly personalized approach and might no longer operate as a standalone service. In the future, banking services could be seamlessly integrated into various consumer products and services. This concept, known as embedded finance, would mean that financial tools are incorporated directly into the offerings of non-financial companies. For instance, while booking an apartment through a builder’s app, the process of securing a home loan could be integrated within the same platform. By simply entering your KYC details, the system could automatically evaluate your loan eligibility by accessing your financial and other relevant data through services like account aggregators or Digi Locker. This could streamline the loan process, making it possible to receive a loan within minutes.

The adoption of advanced technologies would also enable banks to tailor pricing dynamically, based on real-time data on customer behaviour, market supply and demand, operational margins, and competitive factors. This high level of personalization in banking services will become increasingly feasible as digital footprints expand and financial institutions, along with their tech partners, enhance their use of AI and machine learning to analyze this data effectively.


In the dynamic landscape of banking, hyper-personalization emerges as a transformative force, reshaping customer interactions and expectations. Leveraging data analytics and digital tools, banks are moving beyond traditional segmentation to offer tailored experiences that cater to individual needs and preferences.

This evolution is not without its challenges, particularly concerning data privacy. To strike a balance between hyper-personalization and privacy, banks must prioritize transparency, consent, robust security measures, anonymization techniques, and compliance with regulations.

To navigate the changing landscape of banking successfully, it is essential for banks to embrace hyper-personalization. This means recognizing its significance in reshaping customer experiences and investing in data analytics and digital technologies to offer tailored services. Alongside this, prioritizing data privacy is paramount.

Banks must ensure transparency, seek explicit consent, fortify security measures, and comply with regulations to safeguard customer data and maintain trust. Collaboration with fintech firms and third-party providers can further enhance hyper-personalization while maintaining data privacy standards.

– Team AMLEGALS assisted by Prishita Saraiwala

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