Revolutionising Financial Services With AI

By Vikas Krishan, Chief Digital Business Officer, Altimetrik

In the whirlwind that is today’s digitally driven era, the Financial Services Industry is constantly seeking ways to enhance its efficiency, reduce costs, and improve customer experiences. Among the vast array of technology at our disposal, artificial intelligence (AI) now stands out as a transformative force, capable of redefining the landscapes of Insurance, Wealth Management, Banking and Capital Markets.

But it is not just about the automation of routine tasks, AI offers unparalleled opportunities, from advanced data analytics to helping firms to streamline their workflows and so outpace the competition.

Data First

When businesses look to use AI, they often miss out a critical foundational step. And that is ensuring the quality of the data that the AI tool will be provided with. AI can only work effectively, if it is provided with accurate data. Failure to take ownership of business data or indeed a failure to adopt a unified approach will prevent a business from experiencing the full benefits and impact of AI.

There remains a fear among many business leaders within the Financial Services Industry that AI could mislead and pose risks to business operations. However, this is where it is crucial that AI is provided with accurate data in the first place, and a culture of accurate data recording across the business is required to ensure this. As such, Financial Services business leaders must recognise that, when executed properly, businesses can harness AI to stimulate boundless growth. But the right business culture needs to be in place alongside the technology to support that culture, which ensures that everyone takes ownership of business data.

As an example of how this works in practice, Altimetrik recently worked with a prominent US Investment Bank to help them transition to a digital business model. In this instance, the Investment Bank had established a common data lake, yet lacked adequate governance, discoverability, and usability of that data, thereby hindering its ability to function as a Single Source of Truth (SSOT). AI-powered solutions have the capability to ingest vast amounts of data to generate insights, make predictions, automate repetitive tasks, and learn from data patterns to enhance decision-making processes. But here, again we must acknowledge that the worth of AI was directly correlated to the quality of the data it receives.

With this in mind, we re-architected the Single Source of Truth (SSOT) for selected banking domains, ensuring that the business’ data was easily discoverable, usable, and of the highest quality to instil trust and facilitate consumption across all departments.

Although the bank had already established capabilities on RedShift, the bank wished to transition to Snowflake for its SSOT, a key aspect outlined in Altimetrik’s brief to streamline the business.

As with all of the engagements we undertake, we follow an incremental rather than a big bang approach. Through breaking the steps down into bite-sized chunks we help the business achieve a holistic, data-driven strategy that places outcomes over technology.

Leading from the front

A cultural shift within the Financial Services Industry is imperative for an agile and streamlined adoption of AI. C-Suite leaders play a crucial role in cultivating a data-driven culture and guaranteeing the triumph of AI initiatives. It is vital for senior leaders to take ownership and spearhead their organisations in constructing the essential data ecosystem for AI. Data must be seen as a strategic asset with a view to its impact on business growth and success.

Because leaders within the Financial Services Industry must address challenges such as regulatory compliance, fraud detection and prevention, as well as customer experience, it is essential that they have a defined AI strategy in place that aligns with business objectives, concentrating on areas where AI can yield the maximum value.

Collaboration across the organisation is essential to articulate a coherent AI strategy aligned with overarching business goals. It involves pinpointing specific use cases where AI can deliver and contribute to the attainment of strategic objectives. Financial organisations need to be business-owned and led. By setting up a comprehensive framework in which the business consistently takes ownership, leadership can establish the foundation for AI success.

Successful AI adoption requires careful attention to data quality, governance, and leadership. To harness the potential of AI, finance sector leaders must recognise that AI’s success hinges on a solid data foundation, with efficient management and governance. Ultimately, it is only when we invest in data quality first that we will unlock the true power of AI.


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