Key Takeaways:
Financial software development is the creation of systems and processes for the financial and banking industry.
Recently, AI and ML are playing a major role in shaping the way customers engage with banks and other financial institutions.
These two forces are shaping the future of the financial services market
Table of contents
What is Financial Software Development?
Financial software development is the process of developing, optimizing, and implementing software programs in the finance and banking industry. Accelerating AI technology has made it possible for development companies to offer cutting-edge solutions to their clients in the financial world.
As the need of financial companies for digital-first products is here to stay, so is the need for experienced providers of custom-build software solutions, capable to address this demand. The right technology partner can cover nearly every area of the financial realm.
System Modernization
For example, rearchitecting monolith applications into a modern microservices-based solution that can scale to millions of transactions and users.
Applications Integration
Integration of all applications across the organization, building a comprehensive integration strategy based on using enterprise integration platforms and API management technologies.
Data, Advanced Analytics and AI
Optimizing the way financial companies gather, store and process data is the first step toward the data-driven enterprise. Once all data flows are streamlined companies can add advanced analytics and business intelligence solutions to uncover the hidden gems in their data.
Custom Application Development
Working with a custom software development partner, ensures that your specific business goals are fully aligned with your technology capabilities. Custom fintech software drives accurate decision-making and stable growth of the customer base of the client.
Financial software development has advanced significantly in recent years, especially after the Covid-battered global economy emerged from state-wide lockdowns. In that context, financial services companies have shifted their focus from working with clients on-site to migrating their services fully digital and available 24/7.
The Role of AI and ML in Financial Software
Artificial intelligence and machine learning are two powerful components in the process of creating and maintaining financial software. AI and ML algorithms are used to collect and analyze big volumes of data, assess trends, make predictions, and offer solutions.
Further, they can extract and organize insightful conclusions presented in a relatively easy to understand way. Financial operations such as banking and credit offerings, have benefited greatly from the use of AI and ML in the process of working with data. In addition, most operations in the finance and banking sector like asset management or personal financing, could be significantly enhanced by implementing AI and ML.
AI-Powered Financial Software Applications
Financial software applications underpinned by AI/ML include:
Data-driven decision making;
Fraud detection;
Customer experience personalization;
Automated customer service;
Data management.
Data-driven Decision Making
Timely decisions are among the most important components in financial software operations. While humans have a hard time trying to accurately analyze piles of data, AI-powered software could easily scan vast amount of information and predict trends.
Moreover, AI is useful for carefully and thoroughly identifying patterns, as well as anomalies, and pulling insights from the data it gathers.
Banking will undergo a change thanks to artificial intelligence as attention would move from scale of assets to scale of data. Rather than creating mass-market items for broad audiences, banks would now strive to provide their consumers with customized experiences. Being more customer-focused will offer significant retention advantages, as opposed to maintaining them through high switching costs. The most significant change would be that banks would no longer just rely on human inventiveness to improve their services. Performance would instead result from the interaction between talent and technology.
Examples of using AI in finance include budget tracking, investment management assistance, deposits, lending, automated operations and more.
Fraud Detection
Fraud detection is an integral part of every well-functioning financial software solution To this end, AI and ML could effectively deal with detecting and preventing fraud attempts to ensure safe and secure transactions.
AI could easily analyze transaction data and information and uncover inconsistencies in payment documents, user location, or even used devices. AI and ML could be trained to spot any kind of unusual activity along the workflow.
To mitigate the risk of fraud, AI could apply predictive analytics or other solutions to check every step in the transaction process and find traces of manipulation.
Customer Experience Personalization
Customer experience, as with any other field, is highly important in the finance and banking industry. Financial services companies continuously aim to improve user experience, as they seek ways to provide better engagement and have more satisfied customers. AI is readily available to give their efforts a boost.
What AI does, in this situation, is to try and understand customer journey problems and come up with effective and scalable solutions. In particular, AI can track and analyze every click or comment. On a deeper level, it could also evaluate users’ information and present a behavioral profile.
Further, as users keep interacting with the software program, they provide more traces about behavioral patterns which are collected and assessed by the AI in the backend. In turn, artificial intelligence is able to offer tailored solutions to regular customers.
Customer Service
AI could considerably enhance the way traditional customer service operations work. More precisely, solving customer issues could be quicker and more efficient without the intervention of a customer service agent.
Automated AI-powered software could deploy advanced chatbots that could be available to customers 24/7. Furthermore, chatbots could not only solve customer issues, but also collect experiences and complaints reported by users in order to improve existing customer service operations.
In addition, automated chatbots could easily replace humans, which would remove hassles and waiting time on the customer’s end.
Data Management
As financial services companies work with huge data volumes, data management powered by AI and ML could make workflows more convenient and paperless. Artificial intelligence could easily handle complex data from a wide range of sources in a matter of seconds.
Text analysis, data analytics, and predictive analytics are powerful tools that could yield deep insights, which could later be used to improve decision-making processes.
Benefits of AI and ML in Financial Software Development
Artificial intelligence and machine learning are two strong components of a growing number of financial software applications. Some of the benefits they offer in the field of finance include:
Automating repetitive tasks
Cost optimization
Elevated security
Less room for errors
Mitigated risks
Advanced data analytics
Summary
AI and ML-powered financial software development promises to bring a wave of benefits that could offer your business a competitive advantage. As part of the BFSI (banking, financial services and insurance) industry, you need to be assured that you are staying ahead of the curve when it comes to platform functionalities, automated processes, and smooth customer experience.
To help you do just that, Scalefocus is ready to empower you with the latest cutting-edge AI and ML tools. They have the potential to accelerate your services, bring more revenue, and engage a large base of customers.
At Scalefocus we make it our business to know the finance sector in and out and help organizations with their technology-related challenges. Our comprehensive portfolio of services is designed to help banking, financial services and insurance (BFSI) companies to evolve into digital product powerhouses.
With the help of our Remote Delivery Center framework we support the custom software development needs of our clients who can easily extend their operations offshore or onshore.