Hyper-personalization is fast becoming a core component of the financial services industry, It has risen rapidly in prominence thanks to the emergence of machine learning and AI technologies, allowing banks to tailor their offering specifically to customers and their exact requests. Indeed, harnessed correctly, hyper-personalization can enable financial services providers to interact with their customers
The banking landscape today across the entire globe bears very little resemblance to what it looked like even a few years ago.
Indeed, it is fair to say it never stands still – and continues to change, constantly.
The common denominator behind this change is, of course, technology. The rise of online banking, digital-only banks, sophisticated smartphone apps and the ongoing closure of high street bank, building society and credit union branches, means the recent changes in banking have been seismic.
Customer behaviour is also changing, which is affecting how they engage with their financial providers. In addition to using technology, they are increasingly expecting a highly individual service, such as personalized spending advice or customized financial products, and are also increasingly expecting to see a focus on financial wellness, including the provision of tools for budgeting, savings goals, and financial literacy.
However, there is a new technology kid on the block which is helping financial providers to answer the question of how to improve customer engagement in banking – artificial intelligence (AI). Indeed, AI is already making changes that are likely to be equally as significant in the long-term as the online-driven revolution we have already seen.
Customer expectations in banking
The expectations of customers continue to change, leading to a change in digital banking customer engagement for financial providers.
One of the chief patterns is they no longer expect a one-size-fits-all, anonymous approach from their bank, building society or credit union – even though, arguably, the rise in online banking and the disappearance of high street branches would seemingly make this the likely outcome.
The new buzzword in financial services is “personalization” or “hyper-personalization”.
Research from McKinsey states that over 70% of consumers expect personalization and will get annoyed when it doesn’t manifest. Another piece of research, this time by Twilo, is clear in its conclusion that 56% of 5,000 consumers surveyed said they a personalized experience would motivate them to become repeat buyers – a seven per cent increase compared to 2022. Accenture states that three quarters of consumers will not purchase from a supplier without personalization.
Customers also expect an increased focus on cybersecurity and data protection – which is today essential for maintaining customer trust in a digital-first world. As an example of this, biometric authentication, such as fingerprint or face ID, and two-factor authentication are becoming standard.
They also expect seamless integration across multiple platforms – not just banking ones. Financial services are increasingly being integrated into non-banking platforms, such as payments in e-commerce apps, changing how customers interact with their banking services.
How AI can be used to increase customer engagement in banking
The use of AI platforms for banking can significantly enhance customer engagement strategies by offering the following personalized, efficient, and innovative services.
1. Personalized customer experiences
- Customer insights: AI can analyze customer data to understand behavior, preferences, and financial habits, enabling banks to offer tailored products and services.
- Targeted marketing: Machine learning algorithms can segment customers based on their needs and suggest relevant financial products such as loans, credit cards, or investment options.
2. Enhanced customer support
- Chatbots and virtual assistants: AI-powered chatbots can provide 24/7 assistance, answering FAQs, helping with transactions, and guiding customers through complex processes like loan applications.
- Voice recognition: Voice-enabled assistants can make banking more accessible by enabling hands-free operations and providing immediate responses.
3. Proactive financial guidance
- Budgeting tools: AI can monitor spending patterns and offer budgeting tips or alerts when customers approach their spending limits.
- Investment advice: Robo-advisors use AI to analyze market trends and provide tailored investment strategies, making financial planning more accessible.
4. Fraud detection and security
- Real-time alerts: AI algorithms can detect unusual transaction patterns and notify customers instantly, enhancing trust and engagement.
- Secure transactions: Biometric authentication systems (e.g., facial recognition or fingerprint scanning) powered by AI can ensure safe and seamless banking.
5. Streamlined operations
- Loan processing: AI can automate credit assessments, speeding up loan approvals while ensuring compliance with regulations.
- Account management: Predictive analytics can anticipate customer needs, such as suggesting overdraft protection when funds are low.
6. Customer retention strategies
- Predictive analytics: AI can identify at-risk customers and recommend actions to improve satisfaction, such as offering incentives or personalized follow-ups.
- Feedback analysis: Sentiment analysis of customer feedback can help banks identify and address issues proactively.
7. Engagement through gamification
AI can support gamified experiences, such as challenges or rewards programs for achieving financial goals, encouraging customers to interact with the bank’s platform.
8. Omnichannel experience
AI ensures consistent and seamless interactions across various platforms, including mobile apps, websites, and in-branch services, allowing customers to pick up where they left off regardless of the channel.
What is the future of AI in banking?
The future of AI in banking is transformative, with advancements poised to redefine customer experiences, operational efficiency, and financial product innovation.
We will continue to see a major emphasis on hyper-personalized banking, such as that offered by Fintilect. AI will create deeply customized financial solutions tailored to individual customer behaviours, life events, and preferences, while real-time insights will allow banks to proactively suggest products or services that align with customers’ changing needs.
We will also see increasing automation of core banking processes. AI-driven automation will streamline processes like loan approvals, KYC (Know Your Customer), fraud detection, and compliance monitoring. Additionally, in conjunction with blockchain, AI will facilitate automated, self-executing contracts for secure and efficient transactions.
We will also see an increase in the amount of AI-powered financial advisors. AI will enhance investment management with more sophisticated robo-advisors offering real-time market insights and personalized portfolio strategies, while predictive AI will help customers make better financial decisions by analyzing their habits and suggesting adjustments.
Financial inclusion will also continue rising in prominence. AI will enable underserved populations to access banking services through simplified interfaces, voice commands, and regional language support, while predictive analytics will assess creditworthiness for those without traditional credit histories, broadening access to products such as loans.
Enhanced data analytics and decision making will also feature highly on the agendas of financial providers. AI will consolidate and analyze multi-channel data to provide banks with a comprehensive understanding of their customers, while forecasting market trends, enabling banks to make informed strategic decisions.
Conclusion
As we have seen, the banking landscape continues to evolve, with AI and hyper-personalization arguably the most “current” trend to monitor.
Certainly, it is being increasingly seen as a must-have for the banking sector and for consumers alike, providing both with multiple benefits.
Banks, building societies and credit unions are increasingly turning to AI – and those that are not should at least be starting to learn about the mammoth changes that are likely to come in over the next few years, if not sooner.
For more information on Fintilect and its hyper-personalized digital banking platform, please contact us.
