By Mark Katz, Client Strategy and Technology Officer for Financial Services, Hitachi Vantara
Efficiency is all over the news lately. The new administration is pushing to “radically improve government efficiency,” and industry giants tech like Meta and Tesla have announced layoffs and even gone as far as to encourage staff to drop from meetings in the name of efficiency.
The world’s top financial services firms are running the numbers too, and investment in AI is promising. Citigroup’s CEO just reiterated her commitment to the company’s $1 billion efficiency push, and JPMorgan Chase has been forthcoming about its technology goal: Innovation with cost control.
To many people, the word efficiency means cutting spending on things that are not important. But efficiency also sometimes is used to signal a desire for or move to less regulatory oversight.
Being ruthless about spending on the right things and making your business operations and IT environments more efficient are great ways to make your business more sustainable. That’s true regardless of which way the frequently shifting regulatory winds are blowing at any moment.
In today’s environment, here are some steps financial services firms and other businesses can take to improve efficiency while simultaneously adapting their organizations and infrastructure for the age of AI.
1. Understand and address the efficiency challenges of AI and data
AI can provide great new efficiencies, but it’s exceedingly expensive and power-hungry, so it can be an enemy as much as an ally. Breaking the mold for established IT models, AI calls for a new approach to data centers and data management. Yet, new Hitachi Vantara research indicates that while 36% of banking, financial services and insurance (BFSI) sector IT leaders acknowledge the importance of data quality, the data itself is only available when needed only 25% of the time and other factors for AI implementation are being prioritized. Among these challenges and opportunities, it’s critical to note that rushing ahead with AI without focusing on ROI, accuracy, sustainability and efficiency, IT leaders risk sabotaging the long-term potential of AI.
To enjoy the efficiencies and other business benefits of AI while ensuring your IT operations are efficient and sustainable, invest in data centers that monitor and optimize energy use by dynamically powering up and down server workloads and IT electronics. Data centers themselves are optimized by the amount of kilowatts per rack and per row, so choosing server models that operate within that construct can help you significantly with efficiency.
Finding the data you need when you need it is more challenging than ever given the large and growing amount data – especially unstructured data – in your enterprise. Get a handle on your data and ensure people will be able to find it later by tagging your data at the capture point, rather than trying to catalog or locate the data later. If you wait, data will be lost in the sprawl.
Keep only the data you need. Less data means less equipment, power and cooling – and greater efficiency. You’ll also do less searching and be able to feed your AI models faster.
Store data in the most appropriate and cost-efficient place to avoid unnecessary energy usage and storage costs. Look beyond price per gig or price per CPU second and consider total infrastructure consumption, including heat and power. Hard drives are far more power hungry than solid state drives, for instance. So even if a solid state drive costs a bit more, it may be worth it if it consumes a lot less power, generates a lot less heat and requires a lot less cooling.
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2. When applying AI tools, offer incentives for greater operational efficiency
Taking on a new client requires significant evaluation and paperwork for financial services firms today. But AI promises to make that a much more unbiased and lighter weight approach. AI also holds great potential to increase the efficiency of fixed income and foreign exchange trading floors, which are generally not as operationally buttoned up as equities, for example.
Some of the world’s leading financial services firms – including Citigroup and JPMorgan – are already using AI to accelerate the speed at which their developers create code. That’s significant considering that Citigroup alone has 30,000 developers. Software development skills are in high demand, and banks want to use their developers’ valuable time in the most efficient and value-added way. Yet there’s a tremendous amount of housekeeping involved with coding that doesn’t really add business value. AI and new coding languages that abstract some of that low-level work can free up coders to be more productive and focus their efforts on business logic.
Analyze how and where AI will work best for you. Start with one or two use cases and build from there. Map out your goals and how you’ll reach them. Work with an expert partner to guide the way. The last few years, during which many AI projects failed to move into production, have highlighted the importance of doing the proper analysis and work to ensure AI return on investment (ROI).
As you seek to gain new efficiencies with AI or any new technology or approach, build efficiency incentives into your bonus pools. For example, for every $X that an operations or other team member saves on electricity to come in under budget, you might offer $2 in the bonus pool.
3. Remember the financial services business model is inherently tied to trust
There are many great ways to improve business efficiency. But you can carry efficiency too far.
As you work to become more efficient, keep in mind that the business model of financial services is built on trust. Clients bank on the fact they can trust you with their money and their data. Losing their trust creates an existential risk for your brand reputation and your business.
Most BFSI industry IT leaders seem to understand the risk. Eighty-four percent told us if they lost their data through a mistake or attack, the results would be catastrophic to their business.
Make sure you know where your non-public personal information (NPI) and private personal information (PII) data exists, and be sure you have the proper safeguards in place to protect it.
4. Stay vigilant – regulatory predilections are cyclical, but efficiency, sustainability and trust are timeless
History has shown that the appetite for regulation – or deregulation – is cyclical.
But accuracy, efficiency, sustainability and trust never go out of style.
To be clear, when we talk about sustainability, we’re talking about more than just meeting compliance goals or protecting the planet. Making your business more sustainable is also about maintaining trust while making your operations more efficient, innovative and competitive.
This is a lot to consider, but the steps to balance efficiency with accuracy, sustainability and trust are simple. Make sure your data infrastructure operates efficiently and positions you to achieve AI ROI. Tag your data at the source so you can find data when you need it and reach your goals faster. Store your data efficiently, so you don’t needlessly waste budget on extra energy costs. And as you work to drive other efficiencies within your IT operations and your business at large, always remember to protect NPI and PII data your customers entrust you with.
Read More: In A Digital Age, Banks Must Not Leave Cash Out In The Cold
[To share your insights with us, please write to psen@itechseries.com ]
