May 16, 2020

How AIOps is Modernising the Financial Sector

Unravel Data
Kunal Agarwal, CEO & co-founde...
4 min
Kunal Agarwal, CEO & co-founder, Unravel Data, comments on the effects of DevOps and the move to cloud platforms on the financial sector

As the mat...

Kunal Agarwal, CEO & co-founder, Unravel Data, comments on the effects of DevOps and the move to cloud platforms on the financial sector

As the maturity of cloud platforms has developed an increasing number of sectors have seen the need for migrating their data workloads to the cloud. While the financial sector has traditionally been slow to move their on-premise, legacy workloads to the cloud, many major banks are now finding that cloud migration has direct relevance to their business use cases.

Two of the main areas where banks are beginning to use big data are in fraud detection and compliance application performance failures. For these specific use cases the cloud already has significant advantages over an on-premise environment. However, the increasing adoption of AIOps has compounded these advantages to such an extent that financial institutions leaving their workloads on-premise will soon find themselves outmoded. 

Before looking into how AIOps is restructuring financial data applications however, let us first look at the inherent issues of running them on-premise. The first is speed; typical on-premise applications in finance are slow and subject to frequent crashes. The key issue is that remediating these issues is an intensely time-consuming task for data teams as they need to manually sort through copious data logs to find problematic issues. This process is usually on the time-scale of weeks, and unfortunately results in application down-time. Even once the problem has been addressed, trial-and-error processes to ensure the issue has been resolved add several more weeks until normal operations can be resumed. Another consideration is how difficult it is to monitor issues at the cluster usage level. Frequently, data teams will have little visibility over how computer resources are being used and, as a result, optimising data applications is a constant challenge. Due to this lack of visibility, compute utilisation issues can only be identified when a critical data application fails.

With such a comprehensive host of issues on-premise, the incentive for financial institutions to migrate to the cloud is clear. The primary advantage of hosting these applications in the cloud is the enhanced visibility it provides when well managed. Whether these applications are using Hive, Spark, Workflows, Kafka, etc. the ability to monitor their performance in real time provides data teams with invaluable insights that can be used to create reliable performance. For specific use-cases like fraud detection where the inputs of streaming data are so large, the cloud is even more integral in ensuring teams still have visibility over applications and detailed insights gained. With these insights, applications can be optimised to boost performance and reduce wasteful resource consumption.

This is where AI and automation are a boon to cloud workloads. AIOps promises to enhance or replace a variety of IT operations processes through combining big data with AI or machine learning. For the financial sector specifically, this holds obvious appeal as expensive, challenging, and time-consuming problems in big data deployments can be addressed. With AI capable of independently diagnosing several root cause issues, the burden for data teams is reduced as there is no longer the need to manually sort through data logs. Moreover, with automation also being able to provide notifications for specific failures, there is the option of providing automated fixes in these specific instances.


For financial institutions looking to enjoy these benefits, however, the journey to the cloud can seem confusing. As such, the biggest obstacle is often the planning phase. In this process, organisations need to map out which applications are suitable for the cloud and which should remain on premise. Another objective of this phase is to anticipate how these applications should be configured based on specific instance type recommendation. What these early decisions allow for is accurate cost and consumption forecasting. Importantly, by providing critical, data-driven insights instead of relying on guesswork, the decision making timeline can be accelerated and the cloud migration and realised sooner.

To conclude, undeniably AIOps will be essential for financial institutions moving forward. As such, organisations should look to begin planning their cloud migration early to realise the advantages that AIOps has to offer in their deployments. This will broadly reduce their costs, increase efficiency and allow them to redirect resources to value-on initiatives instead of fire-fighting outmoded on-prem workloads.

For more information on all topics for FinTech, please take a look at the latest edition of FinTech magazine.

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Jun 10, 2021

FIVE things fintechs must do to keep investors onboard

Brandon Rembe, CPO, Envestnet...
4 min
Fintech innovations drew in first-time investors who reshaped the markets. What new advancements will help them continue their rise?

New investors flocked to the stock market during the COVID-19 pandemic. Thirty-eight percent of investors said they had never had a brokerage or similar account before opening one in 2020.

Low or no-fee trading options have helped accelerate the trend – nearly half of new investors said they accessed their account primarily through a mobile app. As FinTechs, how do we create the trust needed to keep new investors in the market and create a fruitful customer experience for them?

The financial industry does a disservice to individual investors if we merely offer tools that focus on making money quickly, an approach that usually backfires. Instead, the surge of interest presents an enormous opportunity for those who want to help more consumers use financial technology to educate them on responsible spending, saving, and investing in order to achieve financial wellness current fintech tools have welcomed individual investors in the door.

Now, it’s time to focus on education and improving their experience going forward. There are several ways those of us in fintech can step up to shape the future of retail investing so that it works better for everyone, starting with the following areas.

Equal access to financial wellness education

Financial health should be available to everyone — but today, not everyone has the educational resources to achieve it. One study shows that only 3.9% of students from low-income schools were required to take a personal finance class. What they aren’t learning in school or from family members, fintech companies can provide on their platforms.

The companies should move from solely offering financial services to a more responsible model of education, advice, and prescriptive choices to help consumers develop better habits and make wiser financial decisions. Not only can they empower consumers and bridge historical wealth divides, but they can also stimulate growth by opening up new consumer segments.

More personalisation

Just as we’ve come to expect that our fitness routines are tailored to our individual bodies, we’re also ready for finance tools that go beyond one-size-fits-all solutions. But only six percent of financial institutions say they’re using the kind of technology that allows them to deliver a deeply personalized experience. Fintech tools need to reflect that financial success looks different for each of us.

For one consumer, it may mean providing guidance on how to pay off student loans early; for another, it may mean prescriptive actions that enable them to stick to a budget for the first time; for a third, it could look like prioritizing environmental, social and governance (ESG) investments, so that her portfolio aligns with her political beliefs.

Now, we are seeing financial technology beginning to meet the demands of personalized finance in a substantial and meaningful way.

The rise of AI-Powered Advice

Big-picture advice and predictive guidance used to be a feature of high-end financial advisory firms — a perk only available to those who could afford it. But thanks to rapid advancements in data analytics and artificial intelligence (AI), that kind of holistic advice is now more accessible than ever. AI-driven robo-advisors can parse many different streams of financial information, delivering customized answers to key questions: Is it time to buy a home, or is it smarter to keep renting? Can I afford to take out another student loan?

Intelligent connectivity powered by AI can anticipate consumers’ needs and next steps, making proactive suggestions that guide them along the path to financial wellbeing. Fintech companies can also help consumers identify when their financial picture becomes too complex for a robo-advisor, and help them find a human financial advisor to meet their needs. 

Focus on financial mental health

New investors are quickly finding that the market can be overwhelming. That’s not surprising, financial anxiety is common and studies show that financial stress can have an impact on mental health for some.

It’s not enough for fintech companies to give retail investors access; they also must provide the guidance and support that help consumers manage their financial well-being. Educational tools can ensure that consumers are well informed about their options.

Predictive analytics can anticipate consumers’ questions, serving them key information and insights before they ask. Features that emphasize a comprehensive notion of financial well-being, rather than short-term wins and losses, can also help ensure that consumers are keeping their eyes on the bigger picture.

Gamification for good

The surge of gamification apps has done an impressive job making investing as engaging as playing a video game or joining a social media platform.

Much of the current use of gamification emphasizes short-term thinking, but there’s also an opportunity to help consumers think more broadly about their overall financial picture. One example is peer benchmarking, a feature that enables help consumers to see how their financial habits compare to those of friends and fellow consumers.

Gamification can also be used to incentivize making smaller, smarter choices — for example, rewarding saving over making an impulse buy.

The future of fintech is about more than just broadening access to the markets. It’s about making sure more individuals have access to the tools that can help improve their financial well-being—in the ways that suit their own circumstances and needs. The potential to act within their own set of individual priorities, with their long-term financial wellness in mind is much more empowering to a consumer than simply relying on short-term, high-risk investments.

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