April 24, 2024

A Big Bang Moment For FinTech

Sandeep Sahai is the CEO of Clearwater Analytics, an industry-leading SaaS-based platform that automates the entire investment lifecycle.

Every generation or so, a disruptive new technology comes along that changes the way people live and work. In the late 1990s and 2000s, we were introduced to the internet and smartphones, a development that forever altered lives across the globe.

You may recall the “doom and gloom” forecasts surrounding the disruptive force of the internet. Yes, it would provide us with unlimited information on demand, but many felt it would cost millions of jobs and destroy countless industries. Journalists would disappear, as would realtors, bankers and 50 other professions. There were concerns about privacy and cascading economic damage.

Twenty-five years later, precious few people could imagine a world without Google, email and Amazon.

This year, the world was introduced to artificial intelligence (AI) in the form of ChatGPT—a game-changing technology that is having a Big Bang-like effect on nearly every aspect of our lives, causing an explosion of disruption and innovation that will change the world as we know it.

As with the internet, I believe we can expect to hear a chorus of “Oh no” and “We’re finished” emanating from lawmakers, media organizations and consumer groups.

At Clearwater, we say, “Bring it on.” Rather than retreat from generative AI, we see a big green field with endless opportunities for AI capabilities to disrupt and transform the FinTech space.

Many experts estimate generative AI will contribute significant value across the business sector and specific industries. According to a recent report from McKinsey, “Across the 63 use cases we analyzed, generative AI has the potential to generate $2.6 trillion to $4.4 trillion in value across industries.”

The economic potential is immense, leading heavyweights like NVIDIA, Microsoft, Google, Bloomberg and others to pour massive amounts of R&D resources into this technology.

Every day, generative AI applications are springing to life, helping people generate text, images, audio and synthetic data. Large language models (LLMs) like ChatGPT are democratizing what used to be resource-intensive endeavors. The genius of this technology is that it does much of the heavy lifting, removes repetitive tasks and allows everyone access.

Yet even as first adopters integrate generative AI at a rapid pace, FinTechs should know to approach generative AI with the right priorities and modern tech infrastructure in place.

Security First

Generative AI models need to protect everyone’s data since financial services data is highly sensitive and subject to stringent regulations governing data usage. To leverage generative AI effectively, privacy must be a top priority, keeping client data separate from other models by default.

Unlike other industries, FinTech organizations cannot afford to adopt the technology first and address security concerns later. Decision-makers have to take a step back, establish proper controls and build a private generative AI experience that guarantees 100% data privacy.

More importantly, firms should have a modern technology stack with security features that comply with SOC 2 Type II, PCI-DSS, HIPAA, GDPR and more, while developing applications that carefully select and train language models.

Data Accuracy

The bar for data quality and accuracy in financial services is among the highest in the business world. With our average client being able to invest in over 60 different asset classes, the need for current and accurate data cannot be overstated. Unquestionably, generative AI can produce speedy results. When it comes to producing accurate results, however, the conversation becomes quite different.

Since generative AI occasionally produces errors, or “hallucinations,” quality control is central to avoiding inaccurate outputs. In workflows involving financial reporting and compliance, even the slightest inaccuracies can lead to regulatory blowback and financial penalties.

Achieving accuracy is vital not only for building high-performing products but also for establishing the trust necessary for long-term success between financial institutions and their clientele. FinTechs that build a scalable data architecture prioritizing data governance and security procedures are best positioned to harness generative AI for accurate outputs.

Glass Box Transparency

In recent news, lawmakers in Europe approved the EU’s Artificial Intelligence Act (paywall), a draft set of rules for safer and more transparent AI. A last-minute amendment to the AI Act requires generative AI applications to comply with transparency requirements by disclosing whether the content was AI-generated.

These rules are headed in the right direction, transforming the process of data management from a “black box” into a “glass box,” and should bolster confidence in the data among investors and stakeholders.

Firms that use FinTech software designed with transparency will enable users to understand and explain how decisions are made and ease regulators’ concerns about the development and deployment of AI technology. FinTechs that harness their extensive data sources and can explain their data collection methodology will know why the LLMs provide the outputs they do.

Back To The Future

Today’s institutional investors rely on FinTech solutions to curate tailored reports optimized for human analysis, and in their day-to-day work, these investors run additional analyses and projections that take up a lot of their time.

Generative AI is a tool that empowers institutional investors to quickly find all the answers they need to know, even when working with massive amounts of portfolio data, while giving them more time to do higher-value work. We’ve arrived at a time and place where there are no limits to what is possible, recalling a quote from Sir Arthur C. Clarke: “Any sufficiently advanced technology is indistinguishable from magic.”

While the transition won’t happen overnight, FinTechs that move quickly will gain the most from deploying high-value applications. I believe a modern technology platform that processes accurate, timely and comprehensive data at speed and scale provides the right foundation to power generative AI.

Imagine using this data to reap unprecedented gains in your investments. Sounds utopian, but it’s right around the corner. Will it be easy? Absolutely not. Will it be worth the sweat equity? Yes, by orders of magnitude.

At the end of the day, we will see some of the most transformative and disruptive ways of working that were not possible before, making us all better off as a result.


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