In this context, we have developed a project based on detecting periodicities in transactional data. This research, which will be published in March during the IEEE Symposia, represents a significant advancement in banking customer segmentation.
Óscar Barba
Co-founder & CTO of Coinscrap Finance
Our team has developed an innovative algorithm based on detecting periodicities in transactional data, a study recently selected for publication at the IEEE Symposia on Applied Computational Intelligence in Trondheim, Norway (March 2025).
Together with my colleagues Martín Molina, Carolina Cano and David Díaz, we have created a system that allows banks to better understand their customers and anticipate their financial needs.
The potential of advanced clustering for banks
According to our clients, one of the main challenges for banks is gaining an in-depth understanding of their users to offer them financial solutions tailored to their real needs. It means, essentially, achieving the perfect match between supply and demand.
Typically, segmentation is based on socioeconomic criteria (such as age or income) or basic financial behaviour rules (such as investments or property ownership). However, with the enrichment of transactional data provided by our AI and the analysis of periodicities, banks can go beyond, grouping their customers into clusters with homogeneous characteristics and needs.
This new approach enables them to identify spending patterns, assess savings capacity, and anticipate future financial behaviour for each user. As a result, banks can fine-tune their marketing strategies, design successful financial products, and strengthen customer relationships through genuinely useful communications.
💡 Did you know that…
… your customers’ savings can be transferred to different savings and investment vehicles, according to the bank’s strategic priorities: savings accounts, investment funds, unit-linked insurance, pension plans, and more.
What are the practical applications of periodicity detection?
The detection of transactional periodicities offers exciting possibilities for the sector: imagine a world where banking does not just react but anticipates needs, supports decisions, and makes life easier. Isn’t that what we all dream of?
Below are some use cases that bring our research to life. Algorithms add a touch of magic to online banking; now, discover the applications that enhance financial health for the population:
Micro-Savings
When someone struggles with financial planning and management, they are likely to leave their current bank as soon as they find a better alternative. Digital tools that guide users can foster lifelong loyalty and attract new customers.
Our technology already enables banks to assist their customers in this process through automated rules, setting realistic financial goals, and celebrating each small achievement with family and friends. Here is what users can do with our module:
• Set savings goals based on their financial situation.
• Receive personalised recommendations and advice.
• Automate savings towards key objectives.
• Celebrate every goal scored by their favourite team by adding a sum to the savings pot.
In this way, everyone benefits: banks strengthen their bond with each person, and individuals achieve their financial goals. By adding a touch of fun and gamification, the user experience becomes unforgettable. Check out B100’s business case and draw your own conclusions.
Smart Savings: Smart Goals and Smart Moments
We know that each user has a different financial reality. That is why our AI engine, COCO, analyses each user’s circumstances and determines how much they can save at any given moment (Smart Savings).
Instead of setting a fixed amount for monthly savings, the system provides a dynamic figure that adjusts according to income and expenses, thus safeguarding the user’s financial health.
Let’s consider a practical example: If your bank detects that one of your expenses is your annual car insurance payment, it can suggest dividing the amount into 12 months and setting aside a portion each month. By setting this Smart Goal, the charge to your account will no longer be a surprise, and you will manage your finances more effectively.
Now, let’s explore how Smart Moments work. This AI functionality allows banks to identify moments when it is possible to maximize contributions to savings products, such as tax refunds or a bonus. Take a look at this image:
User segmentation based on financial behaviour
Or rather, micro-segmentation. Banking marketing teams are taking a huge leap forward by reducing the size of their user clusters. They can now create customer segments based on ultra-precise characteristics —derived from financial habits and key behavioural traits— which are far more valuable than traditional sociodemographic factors.
This is a key strategy enabling leading brands to truly understand their customers and offer services that are 100% tailored to their needs. We see this in users who show a particular interest in online shopping or those who have a high appetite for investment risk.
In the first case, if the bank observes that a user is subscribed to multiple platforms and makes online purchases every month, it could propose a savings strategy that eliminates unused streaming/content consumption services and adjusts the digital piggy bank goals to their actual saving capacity.
For our hypothetical investor, if their bank notices frequent portfolio changes and purchases of above-average risk assets, it could send a push notification suggesting new opportunities, investment recommendations, or alternative products of interest.
AI as a catalyst for banking transformation
Artificial intelligence is redefining the financial sector, enabling banks to offer more intuitive, customer-centric experiences. By detecting essential and non-essential expenses, subscriptions, income, recurring transactions, and more, we are taking the banking industry to the next level.
Periodicity detection in the future of banking
Our periodicity detection algorithm even allows the same user to belong to multiple clusters, so they receive offers based on each data point our AI collects. Every individual habit places the customer in different segments, ensuring all recommendations they receive are relevant.
Identifying key moments in banking transactions
Leveraging key moments throughout the year also makes a difference: understanding seasonal habits allows for more effective strategies. For example, in September, when school expenses impact many users, it is not the right time to display savings banners in online banking.
However, March is the perfect moment to offer solutions that enhance financial security. Recognising these peaks and troughs enables banks to maximise their data insights and encourage customers to save during lower-expenditure months. This fosters brand loyalty and builds lasting relationships between banks and their customers.
This approach ensures that digital platforms are not only easy to use but also extremely valuable, helping people improve their financial habits and reach their savings goals effortlessly with the support of their trusted bank.
This is how banks can increase their profits by helping customers gain smarter and more effective control over their money!
About the Autor
Óscar Barba is co-founder and CTO of Coinscrap Finance. He is an expert Scrum Manager with more than 6 years of experience in the collection and semantic analysis of data in the financial sector, classification of bank transactions, deep learning applied to stock market sentiment analysis systems and the measurement of the carbon footprint associated with transactional data.
With extensive experience in the banking and insurance sector, Óscar is finishing his PhD in Information Technology right now. He is an Engineer and Master in Computer Engineering from the University of Vigo and Master in Electronic Commerce from the University of Salamanca. In addition, Scrum Manager and Project Management Certificate from the CNTG, SOA Architecture and Web Services Certificate from the University of Salamanca. He recently obtained the ITIL Fundamentals certification, a recognition of good practices in IT service management.
