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How HPC and AI are Transforming the Finance Industry

7 mins read

Qinthara Fasya | 22 September 2021

Sinisa Nikolic

Director and Segment leader of HPC & AI at Lenovo ISG, APAC

As a result of the pandemic, financial institutions, like many other organizations, have definitely expedited a number of digitalization initiatives. Tech solutions have helped to sustain operations and keep things moving, whether it is to assist their employees or to guarantee they can continue to serve consumers. For example, customer interaction in Singapore’s mobile banking apps increased by 17 percent last year.

However, beyond temporary solutions to ensure business continuity, solutions such as artificial intelligence and high-performance computing (HPC) enable financial institutions to further streamline and automate processes, improve data management and utilization, and ultimately enjoy efficiencies and build resilience to weather future storms. DigitalCFO Asia spoke with Sinisa Nikolic, Director and Segment leader of HPC & AI at Lenovo ISG, APAC, on how tech such as Artificial Intelligence and High Performance Computing can support financial institutions beyond COVID-19.

Technology Trends demonstrated by Financial Institutions

While traditional systems have worked well in the past, rapidly evolving industry needs mean that financial services must adapt their processes accordingly or risk falling behind. Promisingly, the industry has witnessed a continued and aggressive focus on digitalisation and the adoption of new and emerging technologies to enjoy operational efficiencies, enhance speed-to-market, and deliver superior customer experiences. As online and mobile banking continue to increase in usage, we’ve seen banks reduce spending on physical branches, choosing instead to invest in tech solutions such as self-service digital channels. 

More players in the finance industry, including “traditional banks” are now moving away from outdated, legacy systems to data-driven technologies such as cloud, artificial intelligence (AI) and machine learning. Financial institutions have increasingly recognised that data is the new currency and by leveraging hybrid infrastructure environments that are easily accessible, scalable, and secure, they are able to better store, manage, and utilise their data – building resilience and driving innovation. 

Apart from meeting customer needs, tech has also been influencing the way people in the financial services sector work. To maintain operations and keep things moving, businesses have embraced tech solutions like Virtual Desktop Infrastructure (VDI) that provide both flexibility and security – which is extremely critical for those working in this sector. In Singapore, incumbents like DBS and UOB have even implemented flexible work arrangements that are set to continue beyond COVID-19. This transition to hybrid models of work has no doubt been underpinned by tech and we’ve seen greater demand for IT services like VDI and software-defined infrastructure (SDI).

It is clear that the use of technology is the way forward for banks, but financial institutions face some barriers to growth and sustained tech innovation. One of the biggest obstacles standing in their way is this dependence on legacy systems. As a largely traditional industry more conscious of risks, banking and finance is not known to be as agile as other sectors; since implementing new tech often requires experimentation and brings with it uncertainty. However, with the pandemic as a catalyst, many banks have started exploring partnerships with fintech companies to drive new ways of doing digital business. Once seen as fierce competitors filling the void created by ‘staid’ banks, these fintech partnerships have encouraged agility, supporting banks as they deploy new and innovative technology focused on products and services.

Meanwhile, technologies such as blockchain are a catalyst of change, shining a light on the conventional economic value offered by the banking industry. Blockchain is shaking up the foundations of traditional business models with peer-to-peer lending, smart contracts, digital payments, and eliminating intermediaries to speed up underlying processes. With its still unrealised potential, blockchain is expected to save as much as US$20 billion annually by 2022 with the replacement of legacy systems and infrastructure. 

The financial services sector is one of the most regulated industries in the world; these new regulatory requirements and data protection laws are putting additional strains on already-stretched resources. Adding to that, an increase in online activity, digital transactions and processes have naturally resulted in exponential growth in the volume of data being generated. As banks and other institutions contend with storing, managing, and securing all this information, they must also be able to flexibly address rising complexity and adhere to ever-developing industry rules. Without the right technology in place to provide support, be it emerging tech like AI and robotics, or heavy-duty servers and cloud environments, financial firms will find it challenging to be agile and respond to their changing data needs and demands.  

In addition to these concerns, financial services have to consider the amount of investment required to implement new systems or overhaul their existing infrastructure. Recognising the need to balance costs and manage their expenses, subscription-based consumption models like our Lenovo TruScale allow customers to use and pay for data centre hardware and services without having to purchase the equipment. Our priority is not just to help customers address the current challenges they face, but to also encourage a long-term and strategic approach by supporting them in preparing for their future needs and growth.

Artificial Intelligence & High-Performance Computing

With HPC and AI helping financial services derive insights and make better use of their data, businesses can enhance customer experience and increase competitiveness. For example, hyper-personalisation is a growing trend among banks especially as Generation Z grows into a larger customer segment. This segment expects individualised services instead of one-size-fits-all products. Banks must incorporate more personalisation into their offerings to appeal to and secure loyalty from this group of customers. Be it basing recommendations on past purchases of financial plans, considering customer behaviour, risk profiles, or future life stages and goals, by analysing customer data with AI, financial institutions can help customers plan and design their own suite of banking products (for e.g., investment portfolios, credit cards, or insurance plans) that best suit their circumstances and meets their needs.    

Let’s not forget that always-on fraud detection is a requirement for day-to-day business in the financial services world. Advanced technology can play an integral role in monitoring and detection. By deploying algorithms and machine learning, AI solutions can improve security and prevention – be it by verifying identities of customers or discovering and stopping unusual and potentially fraudulent transfers from being completed. Insurance companies can also rely on AI systems to spot suspicious requests for compensation based on comparisons against historical patterns of prior legitimate claims. With countless transactions flowing online at any one time, these algorithms are crucial to minimising fraud and ensuring payments are protected, all without compromising on speed or efficiency. It’s no wonder why global credit card companies are already leveraging machine-learning solutions that run on HPC systems. With the ability to process millions of transactions each hour while applying a million different rules of examination, companies can almost instantaneously spot and halt fraudulent transactions with no disruptions or delays.

The Ashika Group is one of India’s leading financial services providers that has successfully transformed by swapping its legacy data centre infrastructure for a hyperconverged solution from Lenovo and Nutanix. Offering a suite of products across currency trading to investment banking, Ashika Group’s IT infrastructure supports the entire operation, making reliability an utmost priority. With its traditional systems resulting in unplanned downtime and disruptions, The Ashika Group turned to a solution that gives it flexibility and scalability, without compromising on compute power. By replacing 30 individual servers and storage devices with only 3 nodes, the business significantly reduced physical footprint, and has enjoyed easier maintenance and management. Since implementation, they no longer face unplanned downtime and also benefit from faster rebooting of applications – empowering the business to provide better service to their clients. 

In-Solutions Global Ltd, a leading payment service provider has embraced super-scalable hyperconverged infrastructure to support growing demand for digital payments. With the rise of cashless transactions and e-commerce, the company needed a flexible solution to address varying transaction volumes. With the Lenovo ThinkAgile HX series, response time has been improved and transaction success rates have increased. But more importantly, adjusting capacity is simple and can be done without incurring any downtime. This allows In-Solutions Global to conveniently allocate resources accordingly and puts it in a good position to meet rising demand as the business continues to grow.

Will AI reduce finance operations positions in the future?

The only certainty in life is that ‘things change’ and while it’s likely that certain roles will be reduced, this can lead to the creation of new, higher-value positions. AI’s job is to augment and complement the human workforce, not to make humans obsolete. Many banks are already experimenting with various use cases of AI in their operations. When deployed effectively, the use of automated robots or chatbots for example, takes care of basic and routine tasks, freeing people to drive innovation, be creative, and spend their time on more complex interactions. Even critical functions like regulatory compliance can benefit – with machine-learning bots automatically extracting and aggregating data from various sources, quickly reconciling numbers, and generating the necessary documents for auditing processes. By replacing labour-intensive and manual workflows with reliable, cost-efficient, and fast robotic operations, banks can increasingly move to the Edge, bringing banking services even closer to the customers themselves.   

While the use of AI can alleviate bottlenecks and improve efficiency, there are other aspects that only humans are capable of. For example, customer loyalty is still largely based on trust and relationships, and human employees provide emotional connection and empathy that technology cannot. Without emotional intelligence and contextual ability, AI has its own limitations. As such, we will continue to work closely hand in hand – with AI supporting and speeding up processes, and humans providing the context and analysis.  

COVID-19 has acted as a catalyst, causing firms to re-evaluate their existing infrastructure, such as server capacity and data storage. However, as we look forward to recovery and long-term success, it is obvious that those that move beyond surface-level implementations and instead adopt end-to-end digitalization skills will have a larger competitive edge in the future.

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