…At Coinscrap Finance we are in charge of unraveling the complex code behind the data, precisely linking transactions to their companies of origin. This advance offers a whole range of possibilities for innovation, and that is where banks and fintech companies can generate new business and impact a younger audience, who are comfortable with technology.
Why dedicate resources to the arduous task of tracing transactions back to the merchants of origin? Because it allows us to open wide the door to the use of financial products through AI in banking. With the valuable insights obtained, it is possible to discover patterns and establish probabilities that allow entities to improve their services and increase customer satisfaction.
For example, AI-based analytics can predict trends, which in turn leads to the development of hyper-personalized financial products and services. The synergy between transaction tracking and subsequent AI applications paves the way for a new era of innovation and efficiency in the financial sector.
Juan Carlos López
Co-founder & CPO of Coinscrap Finance
The unstoppable use of AI in finance: Don’t be left behind
Our AI engine, COCO collects and normalizes banking transaction data. Using advanced algorithms to clear the information, it is able to eliminate anomalies and ensure the consistency of it. At that time, it analyzes this data to identify patterns in user behavior, such as spending habits, savings trends, and investment capacity.
Through machine learning and predictive modeling techniques, AI can forecast future financial behavior and assess risks. This allows banking entities to segment consumers into different groups, according to their habits. Thanks to this information, the system can generate personalized recommendations for each user, launching the right messages at the right time.
Recommendations may include customized savings products, adapted investment options, and advice for debt management at every moment of banking customers’ lives. Additionally, the system can send alerts about savings opportunities or unusual expenses whenever they arise. It’s about knowing the user better than the competition and offering them a unique service.
Artificial intelligence applications in banking
Obtaining financial insights
The AI engine is capable of launching personalized recommendations based on the consumption habits of each customer. For example, suggesting products and services tailored to their individual needs after detecting predictive moments (relevant events in their life, such as the birth of a baby). On the other hand, it is very useful for controlling fraud due to its ability to detect risk indicators.
Personal finance manager
It revolutionizes the way users control their personal finances through PFM and Smart Savings modules. The first one allows them to have a complete view of all their accounts, offering greater control, advice, warnings and the possibility of making budgets. The second one analyzes the personal circumstances of each user to facilitate savings, suggesting contributions and detecting strategic moments for investment.
Improved safety in operations
With the use of AI, some user consumption habits can be identified and, in the event of any anomaly or suspicious transaction, action can be taken automatically. For example, if you live in one city and your bank card registers activity in another, it is possible to cross-reference data from geolocation systems and notify the operation to request verification. Thus, crimes such as identity theft are prevented.
Delay in payment reduction
Through notifications in digital banking applications, it is possible to inform customers about the transactions that will be carried out, such as the payment of a bill in a couple of days or the car insurance in a few weeks. The AI analyzes spending patterns and warns the user that they could run out of money to make those payments. In this way, personalized treatment is offered, better financial management is promoted and the risk of running out of liquidity to meet future obligations is reduced.
Credit management
With the use of data such as age, income, expenses, average balance or debt level, among others, Artificial Intelligence serves to optimize decision-making when granting, or not, banking products such as credits or any other risky operation. This process allows banks to reduce time and resources, as well as offer safer loans for both parties.
Personalization of customer service
Enriched data is a tool with which banks can show valuable information to their users: from geolocating businesses to track the location of each transaction to identifying each merchant with its logo, including the recognition of receipts and policies. AI decodes complex information to provide a clear view of income and expenses, ensuring hyper-personalization of financial services.
You have already witnessed that Financial Products Through AI play (and will continue to play) a crucial role in the ongoing enhancement of the banking offering. By enabling more agile adaptation to changing customer needs, it transforms market complexity into clear and accessible opportunities for banks. Artificial intelligence, acting as the compass, guides the way toward a new era of technological developments.
About the Autor
Juan Carlos López Díaz is Chief Product Officer and co-founder of Coinscrap Finance. In 2016, together with David Conde and Óscar Barba, he created Txstockdata and Coinscrap Finance. After the tremendous success achieved, the business pivoted towards B2B, in partnership with EVO Banco and its “Smart Piggy Bank.” As a developer, he has over 8 years of experience leading major projects.
Along with his team, he is capable of creating the best tools for the financial world. From the product department, Juan Carlos has delivered projects for major companies in the sector: Evo Banco, Santander, Caser, Mapfre, and Bankia. He holds a degree in Electrical Engineering from the Central University of Venezuela and an iOS App Development certification from U.N.E.D and U.C.A.M.
