Delivering hyper-personalisation in banking with new technologies

According to a 2022 State of the Connected Customer Salesforce survey, 73% of customers said that they expected companies to understand their unique needs and expectations.

In the banking scene, customers nowadays expect banks to know and anticipate their needs, engage them based on life events, life stages, and lifestyle, as well as provide a frictionless path to transactions and services.

New technologies and innovative techniques have emerged to help financial institutions leverage data and analyticsto offer hyper-personalisation by understanding their customers’ digital preferences and footprint.

This is even more pertinent today as Australia’s financial landscape faces challenges from rising interest rates and customers transitioning from fixed-term mortgages. Banks and financial institutions must proactively identify and support customers at risk of financial hardship and build long-term relationships, loyalty, and a stable, satisfied customer base.

Hyper-personalisation, advanced artificial intelligence (AI) algorithms, and robotic process automation (RPA) are crucial for addressing the customer’s evolving needs and financial distress.

The Reserve Bank of Australia (RBA) has been raising interest rates to tame inflation and maintain economic stability. As of May 2023 the cash rate sits at 3.85%, the eleventh interest hike within 12 months. This increase is leading to heavy financial pressure on households with variable-rate mortgages, amid added stress from the rising cost-of-living.

On top of that, the RBA predicts that up to 800,000 fixed home loan contracts will end in 2023, and borrowers with expiring fixed-rate loans face large increases in their repayments.

Banks can play a proactive and pivotal role in preventing widespread hardship and offer their customers a lifeline in this environment. By using AI-driven analytics and real-time data, they can identify at-risk customers early and offer targeted support. Through analysing customer data, AI algorithms can identify patterns indicating potential hardship, such as repayment struggles or income declines, enabling banks to provide tailored support like revised repayment plans or financial counselling.

Financial guidance

As personalisation becomes the norm, customers increasingly expect assistance in managing their finances, particularly during periods of financial uncertainty.

For instance, with Covid-19 causing widespread financial distress, one of the top three banks in the United Kingdom, in partnership with Publicis Sapient, increased its focus on supporting customers in financial difficulty and providing them with the necessary tools to navigate through these challenging times.

By combining customer data available within the bank with data gathered from credit bureaus, the bank was able to proactively identify customers who might require assistance and offer them guidance and support. Warning signs included patterns such as a continuous decline in credit scores, consistent usage of the limit of revolving accounts (credit cards and overdraft accounts) and missed payments on accounts held both inside and outside the bank.

For these identified customers, as they logged into digital channels, signposts were displayed in relevant locations to guide them towards a journey specifically designed to aid those experiencing financial distress. Within this journey, customers received personalised treatment strategies and payment plans tailored to their specific circumstances.

Additionally, the bank offered bespoke credit coaching personalised to the extent of charting out the steps customers should take to improve their credit profile.

The case described above had a significant impact on customers’ lives, with close to a million customers taking part. The bank provided treatment plans for around 10,000 customers each month via online channels.

Meeting regulations

Integrating AI and automation into customer service channels streamlines identification and assistance for customers. Furthermore, these innovations will help banks adhere to regulatory requirements emphasising responsible lending practices and proactive hardship support.

By investing in hyper-personalisation, AI and automation, banks demonstrate commitment to these standards and improve credit risk management and customer base stability.

Reskilling staff

And finally, the implementation of these technologies also redefines the role of bank employees. Staff will need to undergo reskilling to harness the potential of AI and RPA. Equipping employees with necessary knowledge and skills will allow them to provide high-quality, empathetic customer support while AI manages data analysis.

Tales Lopes is Managing Partner of Publicis Sapient’s Financial Services practice in Australia

This article was first published by Consultancy.com.au