One of the biggest challenges faced by fintechs, financial institutions, and businesses providing embedded financial services today is offering customers a seamless experience – without compromising security. Personalized financial services are at the heart of solving this tension.
72% of customers rate personalization as highly important in financial services. Companies that excel at personalization can increase revenues by 5-15% through more relevant offers, reduced churn, and higher customer lifetime value. And with AI-driven personalization delivering up to a 200% increase in conversions in financial services, the business case is clear.
This article – drawing on insights from Viktorija Mažūnė, Customer Experience Director at ConnectPay – explores what personalization in financial services means in practice, how to balance it with security, and what the smartest approaches look like for fintechs and platforms today.
What is personalization in financial services?
Personalization in financial services means using data analytics and AI to tailor financial products, communications, and experiences to individual customers – rather than offering the same generic service to everyone.
Personalized financial services can range from relatively simple adjustments (proactive notifications about relevant offers, communication in a customer’s preferred channel) to deeply customised financial products (investment strategies adapted to individual income and risk tolerance, personalised financial planning for tax efficiency, or credit products based on real-time behavioural data).
Personalized banking services use transaction history, account behaviour, and customer data to provide proactive recommendations – suggesting a savings product when spending patterns show surplus income, or flagging potential cash flow issues before they become problems. This is in contrast to traditional banking, where customers receive the same product menu regardless of their individual circumstances.
The underlying technology is data. With the help of AI, customer data can yield actionable insights that allow businesses to make tailored offers at the right moment. Receiving a generic newsletter is one thing. Getting an offer that is actually valuable because it matches one’s specific needs – that is quite another.
Balancing security and convenience through personalization
Striking the perfect balance between security and convenience is not always easy. Security features generally come with trade-offs, but the inconveniences associated with robust security measures can be significantly reduced by a focus on personalization. The key thing is that customers want to feel heard and understood – not processed.
As Viktorija Mažūnė, Customer Experience Director at ConnectPay, explains:
“What I’ve learned over the years is that people want to be in the loop. Even when you can’t help them directly, just explaining why something is being done meets with a positive reaction – every single time. And this is especially true of complaints regarding functionalities implemented to boost security. When I tell people that the one extra step they’re now required to take is intended to protect them, suddenly it’s all smiles. Their loyalty, rather than returning to baseline, actually goes up as a result.”
This insight captures something important: personalization in financial services is not just about product recommendations. It is about communication, transparency, and making customers feel the service was designed with them in mind.
Personalization as a customer-centric approach
Personalization should be understood not only as tailoring services to individual customers, but as adopting a customer-centric approach more generally. Consider two investment platforms during onboarding – both requiring the same personal data from users. In one case, the process feels like an interrogation where any misstep could result in denial. In the other, the interface is intuitive, the tone is helpful and friendly, and the process feels organic.
The difference is personalized finance in its broadest sense: designing every touchpoint – not just the product offer – around the customer’s experience. The goal here is not to serve any one individual differently, but to ensure that everyone feels the service was made for them.
Multi-channel communication in personalized banking services
Channel selection is a practical dimension of personalization in financial services that is often overlooked. As Viktorija puts it:
“No one likes to be bothered when there’s no pressing need. Bombarding people with endless messages and notifications can easily wear them out. But what about switching the channel of communication from time to time? Personally, I like to give my customers a call when a significant event is impending. Maybe their account is soon to be closed due to prolonged inactivity. Or maybe their data is set to be deleted within a matter of days. In such cases, people really appreciate hearing a human voice on the line, just making a friendly inquiry. This shows you care and respect their time enough not to pester them with calls about some discount they already know about.”
Personalized banking services use data to determine not just what to communicate, but when and through which channel – making engagement feel relevant rather than intrusive.
The role of AI in personalized financial services
AI is the enabler that makes personalized financial services scalable. In the early stages of a business, personalization comes naturally – a small team knows their customers and can respond to individual needs. As customer bases grow, maintaining that level of attention becomes operationally impossible without technology.
AI algorithms allow financial institutions to treat customers as individuals at scale – analysing transaction patterns, predicting financial needs, and delivering relevant interventions at precisely the right moment. This includes real-time financial insights, automated alerts based on individual behaviour, and personalized financial planning that adapts to a customer’s evolving circumstances.
Are banks safe with AI? Yes – when implemented correctly. AI enhances fraud detection by identifying anomalous transaction patterns, often more accurately and faster than manual processes. The risk lies not in AI itself but in how customer data is handled. Transparent data policies, strong encryption, and compliance with GDPR and applicable regulations are essential foundations for any AI-driven personalized banking service.
Challenges of personalization in financial services
Despite its benefits, personalization in financial services faces genuine obstacles:
- Data silos – customer data is often fragmented across systems, making it difficult to build a complete picture of individual customer behaviour
- Legacy technology – older banking infrastructure struggles to extract actionable insights from unstructured data, limiting personalization capability
- Regulatory constraints – strict data regulations make some customers cautious about sharing data, requiring transparent consent processes
- Vendor lock-in – dependence on specific technology providers can limit access to third-party data needed for richer personalization
Personalized finance built on open banking principles – where customers explicitly consent to data sharing and retain full control over that consent – addresses many of these challenges by creating a secure, transparent foundation for data-driven personalization.
Personalization without breaking the bank
As customers have come to expect seamlessness as the default for all online platforms, they are increasingly seeking personalized experiences too. The good news is that personalization does not always require massive investment. Even a handful of relatively simple adjustments – smarter communication timing, proactive account alerts, a friendlier onboarding tone – can have a significant effect on customer satisfaction and loyalty.
ConnectPay builds personalization into its embedded finance infrastructure by design – offering platforms the data visibility, real-time transaction access, and communication tools needed to deliver personalized banking services without building the capability from scratch.
FAQs: Personalized financial services
What is personalization in financial services?
Personalization in financial services means using customer data, AI, and behavioural analytics to tailor financial products, offers, and communications to individual customers. Rather than a one-size-fits-all approach, personalized financial services deliver experiences based on each customer’s actual situation, preferences, and behaviour – improving satisfaction, loyalty, and conversion rates.
Why does personalization matter in financial services?
72% of customers rate personalization as highly important. Companies that excel at personalized financial services can increase revenues by 5-15% and see up to 200% improvements in conversion rates through AI-driven personalization. Beyond commercial outcomes, personalized banking services reduce financial anxiety and build the trust that underpins long-term customer loyalty.
How do fintechs use AI for personalized financial services?
Fintechs use AI to analyse transaction data, predict customer needs, and deliver personalized recommendations at scale – including proactive alerts based on spending patterns, tailored savings or investment products, real-time credit assessments, and personalized communication timing and channel selection.
What is the $3,000 rule in banking?
The $3,000 rule is a US Bank Secrecy Act requirement obliging financial institutions to collect and retain records on fund transfers of $3,000 or more. It is a record-keeping obligation rather than a reporting requirement, designed to support AML investigations. European jurisdictions have equivalent but distinct thresholds under their own AML frameworks.
