By Michael Chalmers, CEO, Mesh-AI
Artificial Intelligence (AI) has never been more popular. This year has seen interest in the technology hit new heights, as businesses and consumers alike figure out how to make the most of the latest AI developments in both their working and personal lives.
The financial services world is no exception. Senior leaders and technical gurus within the sector are starting to become very aware that AI has the potential to revolutionise their entire industry, offering data-driven solutions that can be used to not only address specific problems or ‘headaches’, but also create new opportunities for business growth. It can be the key to unlocking new business profitability and staying ahead of the competition.
However, bringing AI successfully into a business doesn’t happen with the simple ‘flick of a switch’. Considerations and decisions must be made. It requires careful forethought and planning. Financial services teams must determine which AI capabilities they actually need to improve their business, alongside what they feel is feasible to implement now rather than later.
These teams don’t need to make these business-critical decisions alone. To figure out the future, financial institutions can collaborate with transformation consultancies that can help businesses understand where AI can unleash business growth and accelerate certain outcomes. These consultancies can assist businesses in comprehending the practical applications of AI, identifying opportunities for growth, and devising strategies to implement AI solutions effectively.
Improving decision-making and reducing costs
Whilst the economic climate remains tough, the financial services industry could benefit hugely from AI and Machine Learning (ML). These technologies can help financial services institutions navigate uncertain times through greater operational effectiveness – achieved by optimising processes, improving decision-making and reducing costs.
One way of doing this is through using AI to quickly analyse data that would otherwise typically take humans a large amount of time. This not only helps financial institutions recognise trends for informed strategic decisions but also allows employees to focus on more value-added activities, driving revenue and addressing cost-of-living concerns. For example, AI can automate Know Your Customer (KYC) checks by cross-referencing image, audio, and video datasets to ensure organisations are dealing with genuine customers.
AI and data analytics can also help financial institutions to foresee and adjust to disruptions more effectively, minimising the impact by enhancing operational resilience. For instance, AI-driven scenario analysis and stress testing can help financial institutions identify potential vulnerabilities and develop contingency plans ahead of time.
Simplifying the art of following the rules
In the financial services industry, regulatory reporting is a key requirement in safeguarding consumers and ensuring transparency within financial institutions. As regulatory compliance practices across the sector continuously evolve and strict implementation timelines put pressure on financial institutions, it is crucial financial services institutions keep up in order to avoid the risks associated with running legacy approaches.
By embracing data-driven AI, financial institutions can streamline the regulatory reporting process, improving accuracy and ensuring compliance with changing regulations. This is because data collection processes can be automated via AI, which significantly improves the time taken make key decisions and meet regulatory compliance obligations.
Truly knowing your customer
The use of AI and ML in the financial services industry is transforming the way these institutions engage with their customers, allowing them to better understand who their customer base is and what they could offer them to keep them happy.
Truly understanding your customer in no easy feat. Especially in an industry where this understanding can involve a lot of data. Gaining what would stereotypically be referred to as a ‘360 degree view of a customer’ in the financial services industry involves consolidating various different data aspects including transaction history, demographics, online behaviour and interactions with customer support. AI and ML can help with this, empowering financial services teams to discover hidden customer behaviour patterns and preferences which otherwise may go unnoticed with traditional analysis methods. These teams will then find themselves with a much-improved understanding of their customer base, allowing them to enhance personalisation, marketing and customer service standards as necessary.
By understanding the customer’s needs, financial goals and preferences at a deeper level, firms can tailor their products and services, leading to higher customer satisfaction and increased loyalty. For example, AI can be used to recommend suitable investment products, credit cards, or loan options based on the customer’s financial profile.
Data, AI and ML have the potential to revolutionise the financial services industry, leading to more efficient, customer-centric, and resilient financial institutions. At a time of increased uncertainty across the financial ecosystem, it is in the best interest of financial services leaders to get ahead of the curve, while simultaneously benefitting customers and shareholders.
