Financial services were one of the first sectors to understand the promise of the Big Data revolution, and the wave of new technology that has come with it – including Artificial Intelligence (AI). AI is a powerful tool that is already widely deployed in financial services. It has great potential for a positive impact if companies deploy it with sufficient diligence, prudence, and care.

AI is on its way to becoming mainstream in Financial Services within the short term. FinTech companies are more widely leveraging AI to create new products and services while Incumbents mainly use it to enhance existing ones. A larger share of FinTechs is pursuing a more product-oriented approach to implementing AI, by selling AI-enabled offerings as a service.

In contrast, Incumbents tend to focus more on leveraging AI capabilities to foster process innovation within existing product portfolios. There is a trend towards AI mass adoption, with half of all AI Leaders having simultaneously implemented AI in several key areas such as generating new revenue potential, process automation, risk management, customer service, and client acquisition. All AI Leaders expect to be mass adopters within two years, solidifying the hypothesis that there are significant economies of scale in the application of AI in Financial Services.

While FinTechs currently place more emphasis on the strategic importance of AI to their business, the majority of both Incumbents and FinTechs expect AI to become a significant business driver within two years.

AI has the potential to super-charge financial services and transforms the way services are delivered to customers. It could allow more informed and tailored products & services, internal process efficiencies, enhanced cybersecurity and reduced risk.

Approached properly this can provide significant benefits for the firm, its customers and wider society. Disruptive technology is a fact of life and it is not the strongest businesses that survive but the most adaptable to change.

While innovation in finance is not a new concept, the focus on technological innovations and its pace have increased significantly. Fintech solutions that make use of Big Data analytics, Artificial Intelligence, and Blockchain technologies are currently introduced at an unprecedented rate. These new technologies are changing the nature of the financial industry, therefore creating opportunities for Fintech startups to offer more inclusive access to financial services.

The advantages notwithstanding, Fintech solutions leave the door open for many challenges such as underestimation of creditworthiness, market volatility, cyber-attacks, fraud and money laundering which represent central points of interest for regulators and supervisory bodies.

Artificial intelligence (AI) is in the process of transforming a variety of models in the global financial services industry. AI is changing how financial institutions generate and utilize insights from data, which in turn propels new forms of business model innovation, reshapes competitive environments and workforces, engenders new risk dynamics and poses novel challenges to firms and policy-makers alike.

There are many benefits of using AI in financial services. It can enhance efficiency and productivity through automation; reduce human biases and errors caused by psychological or emotional factors; and improve the quality and conciseness of management information by spotting either anomalies or longer-term trends that cannot be easily picked up by current reporting methods. 

AI is transforming the Financial Services industry and we can expect widespread adoption to continue. As the technologies give way to new revenue streams and transform business functions, it’s increasingly important for organizations to focus on the long-term implications of AI adoption. Artificial intelligence is leading the next wave of applications and services for the financial services industry.

One way banks are using artificial intelligence is to improve customer service and engagement. Many have rolled out chatbots for real-time customer service and information purposes, leveraging their customer’s presence on the major chat platforms. Others have developed full virtual assistants, similar to Apple’s Siri or Amazon’s Alexa — to help customers find products or conduct financial transactions.

However, if organizations do not exercise enough prudence and care in AI applications, they face potential pitfalls. These include bias in input data, process and outcome when profiling customers & scoring credit, and due diligence risk in the supply chain. Users of AI analytics must have a thorough understanding of the data that has been used to train, test, retrain, upgrade and use their AI systems. This is critical when analytics are provided by third parties or when proprietary analytics are built on third-party data and platforms. There are also concerns over the appropriateness of using big data in customer profiling and credit scoring.

Many banks are also using AI to automate their own internal activities, such as filling out forms, filing records and receipts, and assessing risks.

Financial Services is also a popular sector for a large number of AI startups. In many cases, start-ups are aiming to disrupt the traditional businesses of large banks. In other cases, they are looking to provide advanced new services to the banks to allow them to improve their product offerings.

Several major themes have emerged among AI startups in the financial services sector: fraud detection, advisory services, personal financial management and trading assistance and execution.

Always keen to develop and exploit a new competitive edge, in recent years the financial sector has put the latest technology to work driving operational changes, increasing rates of fraud detection, improving customer services and developing new products.

The wave of technological change that has swept across the financial sector, and society at large, since the arrival of the internet, has changed things forever – and not just in good ways.

While online banking and technology-driven disruption have brought about improvements in accessibility and customer service, hacking and cybercrime have become common problems. Combating these issues requires enormous amounts of resources – and incurs costs that are inevitably passed on to consumers.

Thankfully, where technology brings new problems, it also offers new solutions.

Another challenge facing the financial services industry is the wave of disruptive start-ups that have emerged, and keep emerging. These newcomers are often carving themselves a slice of the customer base by leveraging data-driven technology in an agile way. Customers take a chance when moving their business away from traditional service providers, gambling that a less established innovator will raise the bar when it comes to customer service, convenience or value.

These disruptors include banks that operate primarily through smartphone apps and websites rather than high street branches – reducing overheads, which means they can pass on savings to the customer through lower fees. Adopting data-driven business models means more efficient decisions can be made when it comes to offering loans and investments.

For the customer, it means services such as verifying transactions are not fraudulent, reviewing recent transactions, making instant purchases and transferring money to friends or family are at their fingertips, 24 hours a day. The growth in popularity of these services means that last year, 38% of personal loans were made by businesses classified as “fintech start-ups” rather than traditional banks and lenders.

AI is also changing how organizations interact with regulators. As the sophistication of algorithms and the volume of data rises, the uses of AI in finance are expanding, and so are pertaining risks. With these additional and unknown challenges, there are also implications for user trust. As the industry continues to transform, regulation will be integral to managing the risks, appropriately regulating the use of AI and instilling trust in consumers.

While regulation may increase costs and ultimately delay product development, it also provides a pathway to user trust. In particular for new entrants, regulation provides reassurance for users and investors as they do not have an established brand name. Fully understanding how business models, regulatory practices and talent needs have shifted as a result of the adoption and application of AI is essential to gain insights into the current Financial Services ecosystem.

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