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Examples of Data Science In Finance

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Examples of Data Science In Finance 1

Let’s look at a news headline from Nasdaq:

“The Rise Of Financial Data Scientist”

Key Takeaways:

  • The finance industry is the one that expects the highest ROI for investing in Big Data, after the logistics industry.
  • It is incredibly difficult to find senior financial data scientists, so the large scale banks are recruiting candidates who have acquired specialized skills through Data Science programs and bootcamps.
  • Financial Data Scientists have the unique ability to utilize technology so as to reduce costs and enhance profits, fuelling the demand for them.
  • As stated by a study conducted by EY on the future of finance, 57% of them noted that it is crucial to brush up skills in predictive and prescriptive analytics.

There are many reasons that fuel the demand for data scientists across the globe.

For the second year in a row, the Data Scientists job has been at the top of the list of 50 best jobs, as reported by Glassdoor.

The salary of Data Scientists can go as high as 19Lpa.

That’s huge! Isn’t it?

 

Moreover, Harvard Business Review refers to Data Scientist as “the sexiest job of the 21st century.”

 

Additionally, data scientists are required in all the sectors from manufacturing to finance, healthcare to IT regardless of your geographical location or current domain.

Another reason for choosing a career in Data Science is that it has plenty of sub-roles such as Data Architect, Database Administrator, Data Engineer, Data- and Analytics Manager. And a good thing about these roles is that they are in high demand across the globe.

Applications of Data Science in Finance

There are many financial companies that train machine learning models to use a large amount of data obtained from different sources like customers, rivals, markets, etc, in order to improve ROIs and enhance cost-efficiency and sustainability. It allows companies to forecast significant parameters such as customer retention schemas, stock market moves, etc.

There are a lot of ways in which Data Science is changing the Finance Sector. Financial management is no longer a tedious task for companies, and the credit goes to data science.

From fraud detection to risk analysis to algorithmic trading, data science is changing the way the finance sector functions. Let us read some of the ways in which Data Science is being used in the Finance Industry.

1.    Risk Analysis

The most crucial part of the finance industry is Risk Analysis. It is impossible to do strategic planning and maintain dignity without going through risk analysis. Risk analysis reports can guide customers regarding investment in the market.

Data science has changed the approach to risk analysis resulting in a transformation in the Finance industry. So, you should understand the concepts of statistics, problem-solving, and math. Some of the sources that generate risks are customers, competitors, shareholders, markets, and others. It is required to analyze the huge amounts of data coming from customer interactions, financial transactions, etc, and train the algorithms to optimize their risk score so as to reduce their risks, thereby enhancing cost-effectiveness and sustainability.

For implementing machine algorithms and data science in the finance sector, companies need to prepare themselves by enhancing the analytical skills of the finance team, automating core financial processes, and making strategic technology investments.

2.    Fraud Detection

Fraud is always anticipated where there is a finance-related task. It is the primary responsibility of a finance company to guarantee security to its customers/stakeholders. This is the reason why fraud detection and management is the most crucial challenge for the finance team. This is the point where a skilled and trained data scientist comes into action. As a data scientist, you have to design such a perfect algorithm that can and prevent anomalies in the work process or user behavior. For example, when there are unusual cash withdrawals or financial purchases that are not frequent, there may be some chances of fraud.

There are machine learning algorithms that can analyze unusual patterns in trading data and hence catch investment fraud. There are clustering algorithms to find insurance-related fraud and other frauds.

3.    Consumer Analytics

In the end, consumers are a critical part of the finance sector. By using predictive modeling and consumer data, you can observe consumer behavior. There are machine learning algorithms that allow you to perform customer sentiment analysis to obtain insights from client behavior, their feedback, and their social media activities. The results can be used to enhance profit and improve personalization. There is a massive amount of consumer data to be handled and to accomplish this task you need a trained and experienced data scientist to perform a precise breakdown.

4.    Real-Time Analytics

Real-time analytics has brought about a transformation in financial processes by analyzing huge amounts of data which is obtained from different sources. This lets you quickly identify any changes thereby finding the best possible solution to the problem.

The real-time analysis helps a company to know the state of the market, their risks on investments, and the stakeholders. Eventually, it helps a company in making better decisions.

5.    Algorithmic Trading

Algorithmic trading has a significant impact on real-time analytics. It is important to have the most recent information regarding traditional and non-traditional data so that the finance company can make real-time decisions. Having the fastest methods of analyzing real-time data makes your company be at a competitive edge.

By initiating algorithmic trading strategies, Data Science and AI have brought a revolution in the finance sector. With techniques such as NoSQL, Hadoop, and Spark, and the most precise algorithms, you can change the way your company responds to the market changes.

6.    Customer Data Management

The finance sector has customers at its core. You need to take care of your customers by knowing their requirements and working on fulfilling those. Customer data is available in both structured and unstructured forms. Structured data can be obtained from official forms such as details form and feedback forms and is easy to analyze and handle. Unstructured data creates chaos as it is in different formats which are obtained from social media posts, online feedbacks, and emails. You require an experienced data scientist to handle this kind of unstructured data by utilizing tools such as Hadoop, Spark, etc.

7.    Personalized Services

A company becomes the favorite of its customers when they get personalized services from your side. The financial sector also does the same, gives some personalized services and proper attention to each of its customers. To give personalized services by using the data generated from customers and analyzing it.

The most common example of personalized services is chatbots.

It is customer satisfaction that can improve the efficiency of your company thereby improving sales.

Conclusion

Besides the applications of Data Science in the Finance sector, other implementations include social media interaction, process automation, improved level of security, and many other tasks. It can be observed that Data Science is bringing revolutionary changes in the finance industry.

To make a career in this domain, you should take up an online training course in order to get certified and career guidance as well. There are some training providers that provide you the choice in mode of learning and learning hours too. They conduct doubt sessions to ensure that you are well prepared and guide you along your career path.

So, get yourself enrolled now!

 

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How fintech companies can facilitate continued growth

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Fintech M&A: the terrible teens?

By Jackson Lee, VP Corporate Development from Colt Data Centre Services

The fintech industry is rapidly growing and, in the first half of 2020, fintechs have secured more than $25 billion in investment globally, despite the huge uncertainty caused by COVID-19. As fintechs and their customer base expand, it is important to recognise that the success of these companies is predicated on the ability to use data effectively in providing a personalised experience to their customers.

To ensure these companies do not become victim of their own success, they must ensure they have the ability to scale up their operations and data storage as quickly and cost-efficiently as possible, especially in these challenging times.

So what must fintech companies do if they are to facilitate this growth without bursting at the seams?

Big fish in a small pond

Fintech companies are growing exponentially, and for many, even the current uncertainty around the pandemic has not decelerated the pace of their growth. However, having started small – with only having access to limited tools at the beginning of their journey, many fintech companies can’t keep up with their own rapid growth. When it comes to data infrastructures, they are facing a real risk of becoming a big fish in a small pond.

In order to achieve widespread innovation, and to keep their advantage over traditional financial institutions, fintech companies need the necessary playground space to experiment in.

When the pandemic and its consequent disruptions started to take hold, most businesses weren’t prepared for the types of challenges that they would have to face. Although the suggestion of investing in data infrastructure might seem counter intuitive at the moment, a lifeline for fintech companies going forward will be flexibility and the ability to scale.

Risky business? 

As the uncertainty around the pandemic continues, fintech companies, like other industries are finding it difficult to commit to long-term business plans. Despite their continued growth, fintech companies continue to be cautious to invest in expanding their operations during an unpredictable economic climate, especially when they are doing well enough as it is.

Even before the pandemic, fintech companies exhibited slower rates of the adoption of digitalisation and advanced IT infrastructures than other industries. It’s clear the future is digital and for fintechs to effectively compete in today’s volatile market, they need to be proactive and invest in the value of data and digital transformation.

One area that fintech companies must be proactive in is their IT infrastructure, especially their data storage and connectivity, in order to allow them to act faster than big, established competitors.

Limitless scalability

Due to the continuous growth of fintech companies, with no sign for it to slow down, these companies will have to continually scale their operations up to manage increased demand. Ordinarily, this would have very high costs as they would have to continually alter their IT infrastructure and solutions.

When it comes to flexibility, data is a crucial aspect for fintechs. In today’s world, companies store masses of data, and its amount is growing fast. This makes the storing of the data a juggling act, and the costs keep growing with it. In periods of economic uncertainty, such as the one we are experiencing now, this constant increase in data can quickly turn into a challenge. Therefore, fintechs must ensure that scalability is at the heart of everything they do. When it comes to scalability, however, the key factor is not just growth or the ability to scale up. A vital, but often overlooked opportunity in scalability lies in scaling down, when needed. For fintechs aiming at this level of scalability, hyperscale is the only way forward.

The answer is hyperscale

Hyperscale data centres provide businesses with a one-stop shop for all their data and capacity requirements. These centres, which are built in a campus-style design, allow companies to build out further data centres quickly within the same location, or if needed, downsize. In an environment of ever-fluctuating demand, hyperscale enables scalability of data and storage swiftly. This presents many benefits. The sheer size of these facilities allows for large-scale cloud adoption, which is more streamlined, flexible and cost-effective than ever before. This will help fintechs to get a better handle on their data and reduce costs as much as possible.

With this level of scalability, companies can operate like an elastic band, expanding or retracting when necessary and at a moment’s notice. For example, imagine this year’s Christmas. With the uncertainty of the pandemic and constantly changing restrictions, people’s online activity will be even higher than in previous years. Fintechs will have to scale up their operations to cope with the high demand of online services. Meanwhile, when demand goes down in January, it might be beneficial to scale down and reduce costs until demand increases again.

Hyperscale will also help fintech companies to future-proof their operations, which has become a key consideration as the economy looks to recover from the pandemic. By having the level of flexibility that hyperscale provides, businesses will always have the ability to lean or expand. Being able to adjust quickly within the hyperscale environment, with no added costs, makes fintechs more resilient and flexible to disruptions.

While cutting costs will continue to be a priority in today’s business environment, it is important that fintech companies look beyond this and focus on innovation and technology. The issues that the pandemic unearthed already existed and needed to be addressed by businesses. Therefore, they need to take the current situation as an opportunity to reconsider and improve their business models. Flexibility, scalability and cost efficiency must be top priorities in this new era. Hyperscale can provide this trinity of success.

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2021 Predictions: Operational Resilience Takes Center Stage

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Managing Operational Resilience And Safeguarding Data Are Core To Sustainable Digital Financial Services

Breaking down barriers between Risk and Business Continuity

By Brian Molk, Fusion Risk Management

What a year! Simply put, the global shocks of 2020 were unmatched by any time in recent history. Not only did the COVID-19 pandemic reach a scale and longevity that rippled through the way organizations operate, communicate, and safeguard against future disruptions, we simultaneously experienced civil unrest, wildfires, hurricanes and more. This unprecedented time exposed weaknesses in organizations and demonstrated that historically siloed approaches to resiliency put organizations in grave danger. No one had a plan robust enough for 2020. Those that emerged from this year stronger were those that took an agile, collaborative, and, above all, data-led approach to resilience.

Driven by these changes, the industry will see several trends in 2021:  operational resilience that blurs the lines between multiple disciplines, real-time decision-making based on data instead of plans,  industry collaboration and product suites,  a new executive buyer, often in the C-suite, and  regulators taking greater interest in resilience across critical industries.

Operational Resilience Goes Multi-Disciplinary

2020 prompted volatile and unpredictable market conditions. The pandemic not only demonstrated the interdependence of multiple areas of risk, but showed organizations that they must be hyper vigilant about all disciplines simultaneously and holistically. Organizations recognized they had resources and processes siloed, and that communication and coordination cross-organization is necessary to prove resilience to leadership, regulators and stakeholders. This demonstrated that solution areas (business continuity, risk management, disaster recovery, and more) with their specific expertise and training each have a role to play – and a strength to bring – in an operational resilience strategy.

As organizations recognize the importance of multiple-discipline focus, the barriers between these practices will break down and come together under operational resilience. Operational resilience will become the overarching school of thought in the industry. As a result, products and services will evolve to serve this need.

Data Instead of Plans

If 2020 demonstrated one thing, it’s that organizations simply cannot plan for everything – and instead must be ready to resolve problems as they arise. However, those that emerged most successful from disruption were those with good data at their fingertips, ensuring that leaders can make informed decisions quickly.

Gone are the days in which meticulous planning and tabletop exercises were the best approaches to resilience. In 2021, organizations will recognize the value of identifying their data and dependencies, maintaining them in software and leaning on the technology to simulate the multitude of outcomes possible. When unplanned events do arise, organizations will depend on technology to play out the plans, understand where they will fail and propose the right changes proactively.

Brian Molk

Brian Molk

Industry Collaboration and Product Suites

Industry collaboration is already underway and will continue into next year. As resilience continues to become a highly visible and critical business operation, the industry will realize the benefit of products that span disciplines to better deliver on organizations’ needs. As organizations break down silos between business continuity, incident and crisis management, disaster recovery and various risk disciplines to become one broader resilience practice, industry players will consolidate their respective offerings and increasingly integrate product suites for greater collaboration – and ultimately, greater resilience.

C-Suite Involvement in Risk and Resilience

In 2021, we will see resilience become a priority at every level of an organization – especially with executive leadership. Prior to this year, many companies viewed resilience as an esoteric activity focused on placating leadership and regulators. They relied on a few employees to own all resilience programs, not intimately involving themselves or their operating executives with the details. 2020 took resilience out of the back room and placed it firmly into the boardroom.

The C-suite will be increasingly committed to knowing whether their organization is ready to tackle and recover from disruptions. This means a resilience program needs to span all the appropriate departments and disciplines, speak the language of business instead of practitioners and answer the highest-level questions of readiness in a single executive experience.

Operational Resilience in Every Critical Industry

Undoubtedly, operational resilience will begin to take center stage in all critical industries. Over the past several years, the Bank of England, the Fed, and the European Central Bank among others have begun a push for regulation not only in financial resilience but in the resilience of operations for financial services. These bodies recognized the critical impact that their industry has on the wellbeing of individuals, businesses, and the economy as a whole – and are taking seriously their role in making a more resilient economy.

Other critical industries, including energy, power, agriculture and others (possibly based on the 16 critical industries defined by the department of homeland security) are similarly positioned. We expect to see regulators taking a greater interest in the organizations in these spaces, to ensure our national and global systems are resilient enough to recover from future events.

2020 was a challenging year, and many people are likely relieved it’s over. But don’t rest on your laurels. Whether it’s climate change, political unrest or even pandemics, the world is more interdependent and more exposed than ever. Ensure your organization has learned the lessons of 2020 and is first to take advantage of these trends in 2021, before it’s too late.

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Five Workplace Culture Trends of 2021

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Five Workplace Culture Trends of 2021 2

5 January 2021 – 2020 – a year like no other – is responsible for driving organisational change, especially workplace culture, which has witnessed considerable upheaval over the past 10 months. Workplace culture expert, O.C. Tanner Europe, foresees that the pandemic and its fallout will accelerate further changes on a scale never before witnessed. Here are its top five workplace culture trends of 2021:

  1. 2021 will see a big focus on organisational culture – COVID has altered priorities. Perhaps for the first time, the importance of a thriving workplace culture has been driven home, with leaders realising that culture isn’t just about the physical perks such as the table tennis table and massage chair, but is about connecting people to purpose, accomplishment and each other.  After months of remote working, furlough and general workplace flux which has caused mass anxiety and financial strain, many organisational cultures need healing and fixing. Leaders will need to find ways to bring people back together, even if it means doing this remotely , and some leaders may even need to strip everything back and re-build a more positive, connected and purpose-driven culture from the ground-up.
  2. How we work has changed for good – Research by the O.C. Tanner Institute found 77 per cent of employees say their workplace culture will never return to pre-Covid-19 normal. Remote working will continue well into 2021 and as employees have proven that remote working can be as efficient and productive as being in the office, many organisations will allow employees to work remotely permanently. On top of this,  with many organisations having had to adapt to virtual working, many normal work processes have changed for good. Companies have already adopted new recruiting and hiring processes, including virtual interviews and even the benefits that appeal to employees right now are shifting. Rather than unlimited holidays, paid parental leave has become important. There’s also a renewed focus on mental and emotional wellbeing.
  3. A greater emphasis on diversity and inclusion (D&I) – Organisations can no longer remain silent on social issues. Employees expect their companies to be vocal on issues of injustice and inequity and this includes a greater emphasis on D&I. And instead of focusing on how to avoid exclusion which is an approach initially driven by legal experts to avoid litigation, the key is to concentrate on inclusivity. This means companies should look past categories such as race, gender, or sexual orientation and nurture each person as an individual. With just 44 per cent of employees saying their company’s diversity and inclusion approach feels sincere, there is a huge opportunity for organisations to improve their efforts.
  4. Generation Z needs to be connected to purpose – Employees in this generation are entering the workplace and more than any previous generation, they are highly connected to social issues and want to make a difference in their jobs. This generation isn’t about climbing the corporate ladder but want to feel that they belong and that their company has an inspiring and relatable purpose. In order to attract and engage Gen Z employees, companies must connect their work to purpose, practice modern leadership and focus on wellbeing.
  5. Real digital transformation is happening – Covid-19 has forced true digital transformation that companies may have had on their ‘to do’ lists for years. Technology has been used to connect us together and keep us working during times of social distancing and remote working, and technological innovation is not stopping any time soon. Mobile tools are more important than ever, as well as strong data security and robust internet capabilities. We will continue to see more technological developments this year, with a focus on bringing people together despite many employees still working apart.

Robert Ordever, Managing Director of O.C. Tanner Europe says, “Leaders and HR professionals need to be prepared for the challenges ahead as they tackle the fallout from the pandemic. There must be a concerted effort to heal broken and damaged workplace cultures while building on the positive developments as a result of COVID-19. Inclusive, connected and purpose-driven workplaces must be prioritised and it’s time to drive technological advancements to bring people together. 2021 needs to be a year of deliberate and positive transformation.”

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