The New Blueprint for the Fintech Industry: Artificial Intelligence and Machine Learning

There is no doubt that artificial intelligence (AI) and machine learning (ML) are becoming a hot topic within the fintech industry. At almost every seminar and conference, we are hearing about the rise of these emerging technologies and the potential they have to disrupt businesses.

It’s clear that AI and ML are a blueprint within which the fintech industry is operating. However, what is apparent is that no matter how much fintechs bang the drum of the impact of AI on enterprises, it still remains underutilized by many companies due to their inability to visualize, integrate and adopt these new technologies.

That’s not to say that there isn’t an understanding of its importance for enabling strategic priorities. Indeed, three out of four executives believe that if they don’t scale AI in the next five years, they risk going out of business completely.

Nonetheless, there remains a gap between "hype" and "practical implementation". Not many companies have successfully industrialized AI, while others are pursuing discrete proof of concept products - where the power of AI and machine learning is disconnected from business outcomes or strategic imperatives. Many companies do not sufficiently tap into the full potential of emerging technologies, consequently limiting their business impact.

With its expansive historical and structured data, fintech is a fertile ground for artificial intelligence and machine learning technologies to generate bespoke products and solutions, to help businesses increase profitability and save costs.  So, why are companies generally slow to adopt, implement, and scale emerging technologies in their short, mid-term and long-term strategies?

Embracing the benefits of Artificial Intelligence and Machine Learning

Many companies are slow to adopt AI and machine learning due to a lack of technical know-how – from both an integration point of view, and a limited understanding of its value to their business.

It is essential that companies work with the right people to commission AI and ML products and solutions that have tangible business benefits and impact at the customer level.

These technologies can play a vital role in operations across a business. Companies can identify opportunities where cost savings can be made, while simultaneously increasing efficiencies, making it easier for the CFO to embrace their role as a key contributor to the growth of the company.

By using a combination of AI and ML technologies, businesses can identify opportunities that companies are missing to accelerate their day-to-day activities and processes. These technologies enable customers to make smarter decisions and operate more effectively. Meanwhile, emerging technologies will increase growth opportunities to aid business development across the globe, helping companies to thrive in an international environment.

According to recent research, executives weren’t struggling to scale AI because of budgetary constraints, but rather the operational challenges of integrating these technologies into their current business processes. The inability to set up a supportive organizational structure, the absence of foundational data capabilities, and the lack of employee adoption are barriers to harnessing AI and ML within an organization.

It is precisely these aspects that differentiate companies that have successfully scaled AI and ML, versus their counterparts pursuing siloed proof of concepts. Not only should company bosses move towards adopting AI and ML as part of their go-to-market business strategies, but they should also actively work towards integrating and encouraging the adoption of these technologies into their day-to-day operations.

Unlocking data insights

The beauty of AI and ML lies in its ability to unlock data insights not previously accessible by traditional manual processes. It is also business size agnostic, i.e. the scaling success rate or the return on investment for using AI and ML is not determined by a company’s size. Instead, it’s more important to focus on implementing the right AI and ML capabilities and mindset in your organization’s company culture. Whether you’re a start-up, scale-up, or a large corporation, AI and ML can be used to fuel your company’s growth strategy.

The business advantages of strategically scaling emerging technologies are vast; these companies achieve nearly twice the success rate and triple the return on their AI investments rather than those companies pursuing siloed projects.

For businesses to harness the benefits of AI and machine learning, there needs to be a move away from an overhyped theoretical narrative towards practical implementation. These technologies should no longer be seen as a clip-on solution; they are integral – now in the present moment – to every business model. It is important to formulate a plan and integration strategy of how your business will use artificial intelligence and machine learning, to both mitigate the risks of cybercrime and fraud, while embracing the opportunity of tangible business impact.

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