This article is authored in conjunction with iMoney. For further information regarding iMoney’s services, please contact them via their website or drop an email at marketing@imoney.my.

From computer software to the streaming industry, the successful implementation of hyper-personalisation has seen companies reaping big rewards such as Netflix adding 9 million subscribers in the first quarter of this year. 

Customers and consumers today want that personalised “Netflix” experience as part of their daily services; exceptionally relevant product suggestions that are provided in real-time.

The same goes for financial services that we use as part of our daily life to save, invest or apply for a loan. This begs the question, “Why aren’t more key decision-makers in the banking and finance industry integrating it into their operations?”

In this article, we will explain and explore a few of the benefits and challenges that those in the banking and finance industry face when it comes to implementing hyper-personalisation solutions. 

Ultimately, banks must integrate and nurture hyper-personalisation into their architecture as the cost of ignoring can be too big for banks and financial institutions (FI) to ignore.

What is Hyper-personalisation in Banking?

Hyper-personalisation in banking is the utilisation of machine learning (ML) and artificial intelligence (AI) technology to thoroughly understand and create highly customised financial services and products tailored to the needs and preferences of individual customers.

Using customer data, such as demographic information and transaction histories, banks can build detailed profiles of their customers to offer personalised and bespoke banking experiences.

While traditional AI has set the stage for personalisation in banking, Generative AI (GenAI) advances this with more dynamic and intuitive features. It understands customer needs better. It creates more engaging and personalised content. It provides scalable solutions that adapt to changing financial environments. This leads to a more personalised and satisfying banking experience for customers. Read here to find out more on how GenAI is emerging in the Banking and Financial Services industries. 

Building Detailed KYC/customer Personas 

Banks can further hone their customer personas and strengthen their know-your-customer (KYC) standards by using big data combined with ML and AI technology. 

This provides a deeper understanding of their customers, going beyond just the standard demographic data. By pulling from external sources such as social media and utilising past interactions, banks can create customer personas that will help them deliver personalised experiences.

Netflix is a prime example of how using the vast data they have acquired through the years to build a customer persona that allows them to provide personalised recommendations and improve their user retention.

Analysing and Understanding Customer Data 

To fully utilise these personas will require a strong foundation in the bank’s abilities to harness, analyse, and understand big data. With data, banks can pull key insights that help build their customer personas. These insights can be broken down into the following three:

• Descriptive insights – Visualises and explains the behaviour/nuances of customers’ spending patterns, transactions, assets, etc.
• Diagnostic insights – Providing the answers to the ‘hows’ and ‘whys’ of customers to better understand customer behaviours.
• Predictive insights – To help banks foresee a customer’s financial health and to alert them on potential issues such as cash flow, unplanned large payments, or penalties. This allows banks to anticipate their customers’ needs and create customised solutions when needed.

By better understanding the data acquired and the type of available insights, banks and FIs can make better decisions on creating and developing experiences that will resonate with their customers.

Creating Customised/Personalised Banking Experiences

Hyper-personalisation is not just big data. It moves beyond ‘data-driven’ and focuses on better understanding customers’ emotional state and the context behind it, allowing you to respond/nudge the customer suitably. 

The combination of convenience, customer engagement, and emotional engagement can lead to stronger loyalty in customers, which will eventually lead to higher conversions. Plus customers are 80% more likely to purchase from a company that offers such personalised experiences.

With the advent of GenAI, hyper-personalisation in banking has reached new heights. Recent surveys show that 91% of financial services companies are either evaluating or using AI technologies. A significant number focus on GenAI to drive innovation, improve efficiency, and enhance customer experiences. Additionally, 63% of European financial services leaders are optimistic about GenAI’s potential to transform their operations. This advanced technology enhances user engagement and greatly boosts customer retention by offering a more intuitive and personalised banking experience. Here are some compelling use cases showing the transformative impact of GenAI in banking:

• Advanced Automated Customer Interaction: A GenAI-powered chatbot is capable of enhancing customer service by providing accurate, context-aware responses, leading to improved customer satisfaction and retention.
• Real-Time Data Analytics: GenAI analyses real-time transaction data to predict and suggest personalised financial products to customers, such as customised loan options based on their current spending patterns and financial behaviour.
• Customised Product and Service Development: GenAI helps banks develop new financial products tailored to specific customer segments, such as bespoke investment packages for young professionals or retirement plans for seniors.
• Enhanced Fraud Detection and Security: GenAI monitors transactions in real-time, learning and adapting to detect and respond to fraudulent activities specific to each customer’s transaction habits, improving security measures.

How Failing to Utilise Hyper-personalisation Can Be Costly for Banks

While the opportunities for growth and improving the performance of banks and FIs can be limitless with hyper-personalisation, the cost of ignoring or failing to integrate it on time can be devasting. 

Unsatisfactory customer experiences for banks have led to customer defections, with the lack of personalised experiences being a key point. The study by Standard & Poor highlights how customer loyalty will waver without these personalised experiences with responses by consumers who are willing to switch from one bank to another if they provide “better mobile app experiences” (39%) and “better customer experience” (38%).

But beyond losing customers, banks that fail to utilise hyper-personalisation will face significant business impacts. A study by Forrester highlights the major costs that banks faced such as increased costs (62%), slowed business agility (60%), poor customer experience (56%), and lost operational resilience (54%).

Ignoring or failing to use hyper-personalisation can be detrimental to your growth and profitability. At the same time, it’s also important to understand why banks and FIs are failing so that leaders can avoid making the same mistakes.

Reasons Why Most Banks Fail to Utilise Hyper-personalisation

The banking industry is particularly suited to adopt hyper-personalisation given its large customer bases and high amount of data per customer. However, banks and FIs are not fully harnessing what hyper-personalisation has to offer due to a myriad of reasons. 

Legacy Technology and Systems

The World Retail Banking Report 2022 pointed out the fact that legacy technology and systems remain the biggest hurdle for banks and FIs. 95% of its surveyed executives believe their outdated legacy systems and technological capabilities make it hard to fully optimise their data for customer-centric growth strategies.

Legacy technology and systems have made it difficult for banks to access the potential goldmine of customer data, which has seen banks needing the ability to fully harness data analytics or behavioural science to increase the utility of their products. 

Strict Data Regulations and Compliances

In addition to facing legacy technology issues, banks also face strict regulations in the form of stringent customer protection and data privacy and security regulations, which also act as perceived constraints towards the adoption of hyper-personalisation. 

Given that hyper-personalisation relies on huge amounts of data collection, there are raising concerns among users regarding their privacy and how it is protected. Add to that privacy regulations such as the GDPR and CCPA, banks and FIs have to ensure that they are collecting and using data in a compliant manner.

Taking the Initiative to Integrate Hyper-personalisation

So, how do banks overcome these costly challenges and start taking advantage of hyper-personalisation?

It all starts with investing and setting up a comprehensive data infrastructure. With the right technology, banks can ensure that the right personalised data is captured and is shareable across all other systems.

From investing in the right platform and building up a data-centric vision to integrating hyper-personalisation, there are numerous ways that banks and FIs can approach this. 

Hyper-personalisation in JurisTech’s Digital Onboarding Platform

A survey conducted by Gladly showed that 59% of customers value personalisation when it comes to their onboarding/customer service experience over speed. For banks and FIs, a hyper-personalised digital onboarding platform is a necessity to keep up with the growing needs and demands of its customers.

JurisTech’s digital onboarding platform tackles these demands through two major approaches:

1. Personalised Application Journeys:
   1. Tailor intuitive application journeys for various financial products, such as car loans, personal loans, auto-financing, and mortgages.
   2. Incorporates pre-approval steps, virtual viewing options, and personalised product recommendations to enhance customer experience.
2. AI-Powered Capabilities:
   1. Reduces costs by improving customer conversion rates and lowering acquisition costs through enhanced sales processes.
   2. Increases revenue by providing AI-driven product recommendations, cross-selling, and upselling opportunities.
   3. Offers valuable insights into customer behaviour, enabling predictive analytics for churn prediction and Loan-to-Value (LTV) assessment. 

Implementation of JurisTech’s digital onboarding platform has led to proven results within the financial industries with corporations and financial institutions being able to improve client experiences and simplify corporate processes, such as fast and precise customer onboarding with straight-through processing, enhanced security measures for you and your customers’  peace of mind, ease of use with low-code/no-code technology, and fast scalability through compatibility with all standard APIs. 

Hyper-personalisation in JurisTech’s Debt Collection System

Basic personalisation is not enough in the modern collection space. Ensuring that banks and FIs can clear accounts in a scalable manner and not impact customer retention will require a personalised experience at every step of the journey.

As such, JurisTech’s debt collection system offers personalised collection strategies with the following capabilities:

1. Profiles customers into different segments based on criteria such as product type, risk value, geographic location, and days past due (DPD).
2. Creates personalised collection strategies for each segment to maximise effectiveness and increase collection rates.  

In addition, JurisTech’s debt collection system takes full advantage of AI-driven predictive analytics and offers the following benefits:

1. Predicts self-curing accounts and potential non-performing loans (NPL) customers using behavioural scoring and AI analytics, improving revenue forecasting accuracy.
2. Maximises revenue collection through the Whiz strategy manager, which simplifies strategy management and allows experimentation with different approaches.

Attract, Keep and Expand Customer Loyalty With Hyper-personalisation

As part of the digital transformation movement, banks and FIs will need to commit to adopting and integrating hyper-personalisation in their key services, which can act as a key differentiator for success. 

By utilising solutions and platforms such as JurisTech’s debt collection system and digital onboarding platform, they will take another step towards taking full advantage of what hyper-personalisation has to offer and maximising growth and profitability.

About JurisTech

JurisTech is a leading fintech company, specialising in enterprise-class software solutions for banks, financial institutions, telecommunications, and automobile companies globally.

We power economies by reimagining financial services with cutting-edge software solutions, which includes artificial intelligence (AI), auto-decisioning, digital customer onboarding, loan origination, credit scoring, loan documentation, litigation, and debt collection.

Our solutions have enabled businesses across a broad array of industries to undergo digital transformation, providing enhanced customer experiences and, most importantly, achieving their business goals.

About iMoney.my

iMoney.my (Intelligent Money) is an award-winning financial intelligence centre that helps simplify personal financial decision-making for Malaysians. Since we started in 2012, our purpose has remained to help people reach their goals through good money decisions.

From tools to jargon-free advice, we make it easy for our users to find the right financial products, apply for them online, and learn about financial tips and tools through insightful articles and financial tools.