By Imran Aftab
Imran Aftab is the Co-Founder & CEO of 10Pearls, a global digital transformation company helping businesses innovate, digitalize and scale.
AI Poised to Elevate Fintech – How Can Innovators Lead the Way?
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It’s hard to understate the transformative impact that innovation has had on the financial industry. The rise of challenger banks – also known as neobanks – ushered in a new wave of customer-focused banking services that disrupted the status quo of legacy financial institutions, forcing a new wave of competitive modernizations. In the long term, this disruption saw the industry gain a leading edge in realizing useful digital tools and services.
Now, the frontiers of fintech are set to jump forward once again thanks to the evolution of Artificial Intelligence (AI).
AI is being widely leveraged within specific solutions and across the industry, helping to analyze banking activities across disparate apps or automate incremental savings, among many other use cases.
However, 2024 marks a major milestone in the overall evolution of AI and its capabilities. The latest advances will not only be able to powerfully refine existing use cases but are also poised to usher in entirely new, previously unattainable business models. Furthermore, their impact on QA automation, platform refactoring, business process automation, and more will also be felt.
Fintech already boasts a mature tech infrastructure and a solid foundation, meaning that new AI innovations can be developed and delivered at a very agile pace. This potential for disruption is underscored in the figures, with the global AI in fintech market anticipated to surge to $61.30 billion by 2031.
Entrepreneurs play a crucial role in this story, creating the next generation of fintech solutions and aiding the market growth trajectory. Here are three areas where AI innovations can deliver the most impact.
Fighting Fraud with Automatization and a New Arsenal
Unfortunately, cybercrime and fraud are an ever-present threat across the finance industry. Although solutions such as personal banking apps with facial ID recognition and two-factor authentications have improved security in some areas, cybercriminals’ tactics are also evolving in line with technological advances.
Reports of personal finance fraud in the US are close to record highs thanks to sophisticated phishing scams and replica interfaces that are increasingly difficult for human users to detect.
Meanwhile, the industry has seen a worrying rise in deepfake scams. To illustrate, in February, a Hong Kong banking executive transferred $25.6 million to cybercriminals. The elaborate scam involved the employee attending a video call with several senior staff members who transpired to be deepfake recreations.
AI can help the finance industry gain the upper hand and tackle the latest tactics cybercriminals employ, particularly by leveraging automation. By analyzing transaction patterns from transactions and unstructured sources, automation can identify highly nuanced anomalies that indicate fraudulent activities in real-time.
In theory, this will enable banks to automate much more accurate protection controls, pinpointing fraud without impeding service delivery or frustrating customers.
AI can very effectively further business process automation here. Additionally, as fraudulent apps and deepfake communications are now almost indistinguishable from authentic materials, AI screening tools can be deployed to act as a first line of defense.
In this game of cat and mouse, the financial industry must employ AI innovations as sophisticated as their criminal counterparts to avoid reputational damage, limit financial losses, and protect customers.
Predictive Analytics and Quality Assurance (QA)
AI’s role in predictive analytics has dramatically impacted the industry’s ability to analyze historical data and combine this with current market trends to automate processes and guide decision-making. As a result, the global market for predictive analytics in the fintech sector will hit $23.9 billion by 2025.
However, AI models of the past have come under fire for being too rigid at times. For example, automated credit scoring algorithms may reject customers for specific products or services due to the parameters of the AI model. New generative AI models can analyze a broader range of data sources, such as education and employment history, to provide a more holistic view of an individual’s credit risk.
Aside from just approving a credit application, these models can also personalize loans automatically. AI can look at vast amounts of borrower data and credit risk indicators to evaluate loan applications, determine the best loan terms, and make instant lending choices.
AI will also play an important role in QA testing, particularly in verifying the usefulness of training data. By leveraging generative AI, financial institutions can access better data, improve credit access, and make business services more efficient and agile.
will also play an important role in
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Asset Allocation Improvements While Leaning on Platform Refactoring
Finally, AI is set to help banks and financial institutions reshape their internal processes and generate more income from investment portfolios.
AI provides traders with sophisticated tools to analyze market trends, predict price movements, and execute trades with precision. These algorithms can analyze vast amounts of financial data in real-time, identifying patterns individuals may overlook.
The same is true for portfolio management. AI can optimize asset allocation and minimize risk by analyzing market data, economic indicators, and investor sentiment. 
For multinational financial institutions that manage a vast and complex network of global holdings, AI can generate optimal investment strategies tailored to personal goals. This will lead to better diversification, higher returns, and improved risk-adjusted performance in their portfolios.
For firms that have long-invested solutions in this area, platform refactoring—making changes to an application’s existing codebase while preserving its functionality—can play a key role.
Further, by helping investors avoid high-risk deals, AI is poised to bring about a more stable financial landscape and champion ethical trading.
The Next Frontiers of Fintech
AI will define the future of fintech in 2024 and beyond. From defending against fraud to helping financial institutions better implement business process automation, AI’s integral role in the industry is clear. The technology will drive advances that improve operational efficiency and security and redefine platform refactoring and QA automation, showcasing its essential contribution to the industry.
Explore out Fintech capabilities 
Read article on MSN News
About 10Pearls
Partnering with 10Pearls as a technology partner presents numerous advantages for businesses seeking to harness the transformative potential of artificial intelligence. With expertise in AI, machine learning, and advanced technologies, we offer comprehensive support in ideating, designing, developing, and implementing AI-powered applications customized to the unique needs of each industry and organization.
With 10Pearls as your trusted technology partner, your business can navigate the complexities of AI implementation with confidence, knowing that you have a dedicated team of experts by your side, ready to help you achieve your business goals and drive success.
Empower Your Business With Artificial Intelligence
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