Emerging Technologies Driving Change
AI and blockchain are unique and rising technologies. Both have their own unique implications for finance.
Artificial Intelligence (AI)
Artificial intelligence and machine learning are finance analysis juggernauts. They might take the form of analyzing consumer spending and earning data in a mobile budgeting application, or they might analyze changes in investment value to make market predictions. No matter what the application, machine learning tools are making it possible for any consumer to gain serious insights into the market and their finances.
AI can also be used to detect fraud. For example, an AI trained on the typical spending data could detect abnormalities in the data, like unusual purchases. This can be used to determine if a purchase could be fraudulent.
Another useful application of AI is through recommendation engines. For example, someone looking for the best loan on a digital lending marketplace might benefit from personalized recommendations based on the size of the loan they need and their credit score.
Blockchain
With decentralized blockchains, payment systems can become faster, more secure, and simpler. Without intermediaries to get on the way, traders can exchange payments peer to peer. In addition to exchanging money, blockchains can enable tamper proof financial documents and contracts. This greatly increases security for all parties.
Revolutionizing Trading and Investment Platforms
AI’s advancements have led to a rise in algorithmic trading and robo-advisors in the finance industry. These systems automatically manage investment portfolios across diverse assets in a way that is most likely to grow savings over time. Robo-advisor platforms can also execute a few other tasks, like rebalancing — adjusting your portfolio to maintain a desired amount of allocation and risk — and tax-loss harvesting, where some assets can be sold at a loss to minimize tax liability.
In the past, advanced algorithms and automation tools weren’t techniques used for personal finance. Instead, they were limited to wealthy investors who could afford the bleeding edge. However, AI has made those features accessible to a much wider audience of investors, meaning that just about anyone can start optimizing their investment portfolios with these tools. These features have become so democratized that demand has increased for mobile application development to provide them for larger pools of investors.
Challenges Integrating AI into Trading and Investment
AI is a powerful tool for a wider pool of investors, but there are a number of challenges to consider when integrating AI tools into these kinds of applications. For one, AI needs a lot of training data to work appropriately. Getting that training data comes with privacy and legal difficulties. You might be able to find public data that fits your needs, but it’s also possible that you might need to train an AI with your own data. This can require extensive research projects and surveys by experienced data scientists to accomplish effectively.
However, if you are starting a launch with a minimum viable product, you may be able to collect data from your own users to enhance the quality of the product over time. It’s worth noting though that this can result in some privacy concerns if you’re not careful. Government regulations restrict what kind of data you can collect from customers without their explicit consent. You’ll need to take that into account when launching your product and gathering financial trend information from your users.
Risk Management and Regulatory Compliance
Finance businesses have several options to consider when looking to build their next software product. Both options come with their own set of risks and regulatory concerns. One of the simplest options is to pick an out-of-the-box solution. If other firms have used the same solution, it’s usually easy to know what to expect out of it when it comes to regulatory compliance. However, it may be much more difficult to integrate an innovative and original solution into the original design. It also can be challenging to update it later on to fit your needs over time.
Instead, when looking for a product with unique features, longstanding support, and tailored to your brand, custom software development is the path to go. It helps you address complex regulatory requirements in a way that you can definitively control. It also allows you more freedom to conduct data analytics on customer experiences, add new and unique features, and present the experience to customers in a way that matches your brand identity.
Reducing Risk with Custom Software Development
The best place to start when looking to reduce risk is to make a plan. If you’re going to make your own product from scratch with a software development company, they’ll help you form a comprehensive plan that identifies possible risks as soon as possible. A plan like this can also help prevent scope creep and ensure that costs don’t overrun.
Excellent software development companies utilize agile methodologies which enable more flexible and iterative project completion processes. This allows you to help steer the ship over time as the project is built. Development teams will aim to create a minimum viable product (MVP) for you and beta testers to review to give feedback on and to understand what the final product might look like. Regular testing, backups, and recovery plans are also essential for mitigating the risks of building custom fintech applications.
Communication is another major area of risk when custom finance applications are being built. Great development teams have a single point of contact and discuss with clients to decide how they will communicate and how often. Regular project updates and transparent reporting are essential to your success.
Future Trends in Financial Technology
The future of the finance industry is exciting thanks to new technologies, but it’s also a double-edged sword. Quantum computers offer benefits for risk management, portfolio optimization, encryption, and high-frequency trading. However, on the other hand, quantum computers could potentially break all existing encryption systems fairly quickly, presenting a disaster for data security.
Open banking is another technology that can affect the future of the finance industry. This technology enables banks to share information via APIs to third-party applications. This allows for things like personal finance applications with real-time data from user banks, giving them a much better picture of their account values all in one place. This democratizes financial services technologies, increases competition, but also presents some serious security risks. If these APIs become compromised, it could expose critical user data or provide a gateway to fraud.
Over time, government regulations will start to catch up with the fast-paced innovation of the financial sector. That’s why it’s important to focus on building applications in such a way that it’s easy to pivot when necessary. You never know when the legal landscape is going to change, so custom software development strategies can make the difference between success and failure for fintech startups.
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