AI and ML continue to transform business models in the global financial services industry, the latest evolution of a development which has been gaining momentum over the past few years and is continuing to accelerate exponentially.
This article examines these trends and how organisations can harness AI and ML to transform the customer and employee experience, reduce costs, and improve efficiencies.
Banks and insurance providers have already incorporated a variety of data science services into their workflows, focused on driving better insights from data. Transforming their data into efficiency-boosting intelligence enables businesses to evolve from transactional to relational interactions with their customers, innovating new business models and responding to a fiercely competitive market for financial services.
Moreover, data-driven financial software development allows organisations to make the best use of human effort by reducing or removing repetitive manual processing via automation.
This shift has also exposed new risk dynamics and challenges to both firms and regulatory bodies alike.
AI and ML, which have been used in the past to improve existing products and services through intelligent automation, have now been seized on by insurance service providers, financial organisations, and fintechs to create new value propositions driven by enhanced capabilities. These opportunities span across multiple functions and include the following benefits:
In other customer-facing industries, a recent imperative has been to achieve a single and unified view of the customer to enable the personalisation of products and services to specific customer demands.
Most financial services companies focus on keeping margins level during a time of cheap customer borrowing by establishing new products. During the pandemic, most organisations, regardless of industry, saw customers’ expectations increase significantly alongside a willingness to shop around.
Longstanding financial service providers have seen new and aggressive entrants targeting these more demanding customers with many products which couple the financial service with convenient and flexible solutions. Hyperscalers and other large and well-funded organisations are poised to enter the market.
These companies are now responding strongly to these challenges, using all means, including next-gen AI and ML solutions, to improve their service offerings and deliver efficiencies wherever feasible.
As with any innovation, AI and ML come with some hurdles and impediments. With the rationale of AI and ML predicated on the input data, the rules and algorithmic processing and access to high-quality data is paramount. This is of even higher importance for organisations in which the input assumptions could have a catastrophically negative effect on the business in case of machine error.
Let’s look closely at some potential challenges associated with AI implementation:
Technology cannot replace the human touch. No amount of intelligence, hundreds of thousands of lines of code, and complex algorithmic constructions can trump the human element. AI and ML could be the continuation of a beautiful friendship between humans and machines.
If you are looking for innovative ways to automate your workflows, streamline operations, and deliver personalised user experiences, partner with ELEKS. With more than 30 years of experience providing data-driven solutions for clients in the finance sector.
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