Hire FinTech Software Developers in Basingstoke. 

Microservices have a considerable role to play in the successful evolution of the fintech industry. In fact, without them, the potential of the industry to disrupt the existing financial services players would have been constrained.

Microservices give fintechs the flexibility to develop innovative, groundbreaking banking technology and agility to adapt to changing circumstances and competitive forces.

Built on a one code basis, monolithic systems are developed as a single unit, and over time customised technology is added and integrated into the system to meet the changing needs of the company as and when they arise. Critical pieces of the technology platform are tightly coupled and highly interdependent, so it is difficult to change without affecting the entire architecture. Many traditional large financial services companies operate on monolithic systems, which means they cannot respond quickly to customer behaviour, preferences, and choices. 

Microservices offer a completely different technology proposition. They are independent applications developed, deployed, and maintained separately to deliver on specific business requirements. These microservices help solve common, complex issues like speed and scalability while also supporting continuous testing and continuous delivery.

From Robo-advisers to regulatory technology (Regtech), AI/ML-driven systems are enabling companies to put big data to effective use in monitoring customer behaviour and detecting anomalies and opportunities they can factor into their services and product offerings.

Whereas banks have traditionally relied on the scale of assets, the financial services players of the future, namely Fintech companies, will depend on the scale of data. Instead of treating customers as the masses, fintech companies will differentiate themselves by providing a highly personalised, customised service to their clients. All of this will be made possible by combining the best of technology and human skills in what Deloitte calls augmented performance versus dependence on human ingenuity.

The areas where AI/ML is becoming particularly prevalent is in the detection of fraud, banking chatbots, algorithmic trading, regulations and policy.

AI/ML is helping banks enormously in their anti-money laundering and terrorism financing efforts. The use of the technology is turning the tide on the huge, and mostly ineffective, investments they have been making into compliance departments to meet increasingly demanding regulatory requirements. The incorporation of AI/ML is expected to improve the return on investment in compliance departments and slow the annual growth in compliance expenses.

However, they warn that there may be potential pitfalls if organisations don’t manage the incorporation of AI/ML into their processes. These include bias in input data, process, and outcome when profiling customers and scoring credit, as well as due diligence risk in the supply chain, they note.

Decentralised Finance (DeFi) is experiencing exponential growth in recent years, highlighting how well-positioned this emerging technology is becoming to revolutionise the finance industry forever.

DeFi is finding favour because it operates outside the centralised regulatory financial structures, cuts out intermediaries and effectively democratises finance for the vast proportion of people who are currently not well serviced by the existing financial incumbents. As its name suggests, DeFi’s common goal is to decentralise financial services. It does so by removing bank, payment and investment intermediaries and replacing these with services that operate within the blockchain network.

Blockchain is a robust alternative base for this disruptive emerging financial ecosystem because it offers transparency and security, removing the reliance on doing business with trusted financial services companies, as in the past. Instead, transactions are facilitated by smart contracts and tokens, which effectively become the digital middlemen and allow individuals to transfer anything of value transparently.

Such has been the demand that, according to Ivan on Tech, the DeFi market has grown by almost 1,000% this year, from about $680 million at the beginning of 2020 to some $6.7 billion by August. Growth is picking up exponentially on a month-by-month basis, with the total value locked into the system almost doubling from $3.5 billion to $6.68 billion in July alone.

With cyber-security cited as one of the biggest challenges businesses will confront during the years ahead, predictive analytics is expected to play a central role in strengthening cybersecurity measures and preventing fraud.

Predictive analytics uses big data, algorithms, and machine learning to assess the likelihood of things happening in the future based on past behaviour. It’s a relatively new branch of data science. Still, it favours a wide range of applications – particularly in the fintech industry where technology facilitates cost-effective, efficient, and scalable outcomes.

In addition to combating fraud, predictive analytics prove valuable in improving customer experiences, identifying employees who are most likely to add value to organisations, and improving operational processes with the foresight offered by the analytics’s forward-looking nature.

When it comes to the customer, predictive analytics enables companies to monitor and measure customer behaviour both in their interactions with the company and across digital and social platforms. They can measure, for instance, average spend, purchasing patterns, loyalty, and customer feedback, and use this data to model customer behaviour and use the insights generated to enhance customer experiences, marketing strategies, and brand awareness.

Operational processes benefit from the ability of predictive analytics to engage in capacity modelling, process optimization and vendor risk management, according to a paper published by Protiviti, titled Innovation in Predictive Analytics. Making use of this technology enables managers to detect problems before they happen. Predictive analytics also plays a valuable role in the internal audit functions in a business, where surveillance tools can enhance the effectiveness of identifying causes for concern.