Regulatory technology holds significant promise for easing the regulatory burden at banks — but there’s a flawed sense of optimism about how quickly those benefits can be achieved.

To date, the market hype around regtech has lulled many executives into the belief that they can easily solve any compliance challenge with the latest technology. But the reality is that many financial institutions are struggling to make use of these technologies, even when they are enthusiastic about them.

As we head into the rest of 2018, I would argue that we are on the cusp of regtech’s “Great Awakening” — where the banking industry shakes off lingering myths about the technology.

Advanced technologies like artificial intelligence may one day help banks meet their regulatory demands much more cheaply — although it's unclear how soon that day will come. Adobe Stock

Perhaps the most jarring of these myths is the hope that immense cost savings are just around the corner. We need to dispel the notion that a regtech solution can yield a bank immediate cost savings of 30% on day one of its implementation. Regtech’s successes are hard fought. No one can sit down over the weekend, do some programming, and then churn out the work of 800 employees come Monday.

So what do the short-term realities look like, if banks must wait patiently for the huge payouts their investments will eventually yield? Let’s take a look at some of the market’s emerging technologies and the myths surrounding them.

For starters, there’s a myth that robotic process automation, which is technology that mimics the actions that human workers make on a computer, is a silver bullet that will take corporate costs down by 20% overnight.

In reality, the industry’s understanding of this technology is transforming. Since it can be deployed as a rules-based system that mimics human behavior to automate parts of repeatable processes, it is, therefore, seen as a strong technology to complement the human workforce rather than as a replacement. If a financial adviser, for example, can allocate more of their time to clients because a robot is managing more repetitive portfolio-based tasks, this could help improve customer satisfaction and retention rates considerably.

But that won’t happen immediately — in fact, the landscape may need another five years to mature.

When it comes to cognitive computing — more colloquially referred to as artificial intelligence, with computers going beyond mere actions to mimic human judgment — there is a myth that the technology is smart enough in its current state to eliminate huge tranches of the workforce and save on overhead costs right now.

The truth is that these cerebral-like technologies are not all-knowing from the start. While it’s true that they include self-learning systems that have the ability to grow exponentially smarter over time, they are not currently capable of being complete human stand-ins. Instead, they can intelligently complete front-end analyses — that is, they can analyze huge data sets and identify the most significant data — so that bank executives can spend more time on analysis, drawing conclusions, assessing risks and directing business strategy.

While increased efficiency and intelligent analysis are the most tangible near-term benefits, applying cognitive technologies can also yield a form of cost savings down the line by providing improved responses to emerging business risks, which can potentially lead to fewer regulatory fines.

Finally, consider the case of cloud computing, which takes computing out of bank’s data centers into shared data processing farms of vastly greater scale. This technology has historically been viewed skeptically by bank executives, who fear it raises too many red flags. There are concerns that using cloud computing might spur unauthorized access to sensitive data and give bad actors more entry points into a bank’s systems.

But, increasingly, there are institutions that are beginning to investigate and evaluate the benefits of being on a cloud platform as well as the risks, because of the compelling economics.

The short-term reality is that cloud computing is critical for many of the regtech solutions that banks want to deploy. Cloud computing is particularly important when it comes to AI, which requires massive databases and dizzying computing demands to enable robots to learn. AI solutions are often prohibitively expensive without the cloud.

For banks, implementing regtech can at times feel akin to piecing together a complex puzzle without the picture that shows the final result. But it’s important for executives to remember that the transformational value can be very significant, even if it does not immediately translate to dollars saved.

Dilip Krishna

Dilip Krishna

Dilip Krishna is a managing director with the risk and compliance consulting practice at Deloitte.

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