Kiandra Insights
Finance technology trends
The finance sector is constantly under pressure as consumers demand more autonomy and faster service. In response, financial institutions are finding new ways to use technology to improve efficiency and meet these needs.
But with so many options available, it can be difficult to know which solutions are right for your business. To help you make the best choices for your organisation, we've compiled a list of the top FinTech trends for 2023.
Hyper personalisation of services and offers for bank customers
One of the growing FinTech industry trends is becoming more of an imperative than an option. Hyper personalisation means custom-made digital banking experiences for each customer. Backed by Artificial Intelligence (AI) and behavioural science, this trend is characterised by collecting data on an individual’s shopping habits, location, transaction history, and more. This data could later be used by the bank to make future offers based on the customers’ evolving needs.
Composable applications
Composable applications are having a profound and immediate impact on the FinTech industry because they enable fast adaptation to changing business conditions. Composable applications allow organisations to develop applications that can be rebuilt and redeployed according to their needs. The ideal finance function technology portfolio is modular, allowing finance team users to acquire, assemble and configure different application capabilities in personalised ways that facilitate their work. According to Gartner, through 2024, 50% of financial application leaders will incorporate a composable financial management system approach.
AI and ML for risk management and securing financial data
Artificial intelligence (AI) and machine learning (ML) have made their way to the FinTech industry and will continue to play a huge role in reshaping businesses. AI and ML can be used by organisations to improve their customer experience with the use of bots and virtual assistants. At the same time, they can be used to automate mundane tasks like cash flow management.
Machine learning works on a lot of data to generate useful insights and can help in risk management, marketing, decision-making, and customer retention. Security is also an area that ML and AI can help improve. For example, both can work to keep user data safe by identifying potential breaches or suspicious activity well in advance.
Decision intelligence
Understanding how an organisation makes decisions requires breaking down the decision-making process and aligning each component with a standardised framework. These components are, in turn, aligned with a set of technologies and techniques to support modular automation and continuous improvements. According to Gartner, by 2023, more than 33% of large organisations will have analysts practising decision intelligence, including decision modelling.
Using data-based predictive analytics is very important for companies to make informed business decisions. It can help them understand their customers better and market their products accordingly.
If you have been considering a new digital offering for your customers or an internal process contact us today to talk about the first steps to providing a solution for your organisation.
.svg){kind=icon}
More insights
The role of the Product Owner in successful software delivery
At Kiandra, we work closely with Product Owners to bridge the gap between their organisation’s needs and our delivery team’s technical expertise. This collaboration is crucial for keeping the project aligned to business goals, managing scope effectively, and ensuring value is delivered.
If you want trustworthy AI, don’t start with the tech
“How do we make sure our AI systems behave responsibly, not just accurately?” We get this question a lot. Usually after something has already gone a bit sideways. Here is the short answer: You build responsibility into AI from the very beginning. Guided by our B-Corp principles, we see responsible AI as a balance of purpose and effectiveness.
Lovable app review: AI prototyping and product ideation tools for clients
When working with clients in the earliest stages of a project, speed matters. The faster we can turn ideas into something visual, the sooner we can test assumptions, get feedback, and align on a direction. That’s where product ideation tools like Lovable come in.
Let’s discuss your next project
Whether you’re curious about custom software or have a specific problem to solve – we’re here to answer your questions. Fill in the following form, and we’ll be in touch soon.
.svg)
