Big Data in Financial Services: Analyze-As-You-Go

In recent years the “Big Data” term has gone viral, more than any other IT science in the 2000s. Not only the spread of the terminology but also the use of it, as every company seems to want to jump on the innovation train. Whether we call it big data, data science, industry 4.0 or any other seductive lingo, we are talking about the same thing: DATA.

For the time being, there is no specific definition for it, but businesses can test their data against the 5 Vs, if they have them all then they are sitting on big data.  

The 5 Vs are: volume, velocity, variety, veracity and value. However, some businesses are stuck with only the old 3 Vs: volume, variety and velocity. Unfortunately, this set of tests are considered less lucrative as a big investment can be allocated on detailed analytics but may bring no value, therefore, it is pointless to start it at all. And that explains how fast the science has been evolving in very short time.

Big data is not the answer for every business equation. However, not all types of data can be stored or used as big data, for instance:

A financial services provider is storing on a daily basis the content of customers’ bank transfer descriptions. This data can’t be called big data, it is personal data which can’t be shared or analyzed by any party. The same provider is storing their users’ IDs as they get registered, this neither can be called big data. This is corporate internal data and should be stored in a dedicated Data Warehouse server. On the other hand, spending transactions can be undeniably considered as consumer behavior and that is big data. Once this data is analyzed, firms can provide more personalized services for users and consequently optimize pricing strategies, therefore increasing customer retention rates, gain competitive advantage etc…

Financial services firms must be fully digitalized to get valuable insights from big data. But the financial services industry is no closer to topping the Digitalization Index as reported by Morgan Stanley research as it was in late 2016. In fact, only 35% of financial services firms are digitalised due to IT legacy systems and outdated business processes. Firms need to unlock more opportunities by utilising big data and integrating it into their everyday operations such as:

Business Operations & Strategy

In a report by PwC’s published in 2018, only 38% of U.S. consumers say the employees they interact with understand their needs; 46% of consumers outside the U.S. say the same. To tackle this business issue, analytics-based technologies produced from big data can promote a customer-centric culture to enhance customer experience and increase operational efficiencies. By leveraging big data, firms can also build self-service platforms to attract more wealth management investors, aligning them with their demands and also cutting fees to the lowest. It will be a good practice to connect departments’ old collected data and integrate it with the new acquired one to get the most of data integrity.

Risk Management

Credit scoring platforms are a vital service that serves hundreds of millions of customers across the globe. But now it must be brought to a second level to provide a 360-degree view on the customers’ financial circumstances. By introducing non-traditional metrics, customers will have fairer access to financial products. Moreover, the outcomes produced from big data can be used to build a data model to identify patterns to catch stock market cheaters and alert risk workers to investigate these cases. Proactive Chief Risk Officers will regularly utilize big data to ensure the company is aligned with their strict standards.

Information Technology

The use of big data in financial services’ IT systems has become imperative in recent years due to high numbers of cybercrime. In order to detect fraud and prevent it from occurring, firms must have a more advanced level of security. Building predictive analytics will empower IT workers to anticipate cyber-attacks before they hack their systems. IT engineers acting strategically can support other departments, feeding them big-data-as-a-service, ranging from: automate reconciliation processes for finance department, real-time reports for marketing department to enhance their targeted marketing campaigns and building parallel big data models for back-testing new services before their launch. IT workers are the jolly players in the big data game, they have the ability to continually support their colleagues across departments to transform dark data into strategic data.

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Businesses must not have red-numbers in their balance sheets to start exploring analytics from big data. Even established firms with healthy statements are frequently analyzing their data. In fact, they are the firms that gain: market expansion, competitive advantage and boost profits.

If firms can empower big data to answer business questions, then the same big data can provide them also many unquestioned answers. In fact, the benefits of big data unquestioned answers won’t be limited only to the financial services firms and their stakeholders but will exceed further to other parties, here are some of them:

1)   Unquestioned answer: Customer Segmentation

Analytics can provide insights on different consumer behaviour based on age, income and demographics. Therefore, firms are enabled to align customer products with their customized needs consequently will increase customer retention rates. Beneficiaries: Consumers – Financial Services Providers

2) Unquestioned answer: Pricing Strategy

Along with other benefits, large-scale analytics can offer consumers better prices. For instance: consumers can get competitive prices on their car insurance policies based on their prudent speed patterns. Financial services firms are able to use big data to spot overpriced housing and advise their customers to evaluate different offers, re-directing them to a more suitable lender. Beneficiaries: Consumers – Competition Regulators

3) Unquestioned answer: Financial Inclusion

As mentioned by the European Banking Authority in their survey published in 2018, respondents expressed the positive impact of big data for more financial inclusion. A considerable portion of citizens don’t have access to financial services such as: credit scoring, housing financing…etc.

But by involving big data, those citizens could use wearable devices to improve their health conditions, therefore will have access to more competitive and cheaper insurance packages. Having the first financial product will help them to be integrated into the financial ecosystem. Beneficiaries: Consumers – Financial Services Providers – Governmental Bodies

4) Unquestioned answer: Data Governance

Good practices using big data from financial services will increase consumers’ trust with their suppliers. Firms will benefit if they share their big data techniques and explain how they are using the data ethically to improve their provided services and better meet consumer demands. As consumers are attracted to personalized products, they will knowingly share more data to get more personalization. Beneficiaries: all above mentioned beneficiaries

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Big data guidelines are everywhere but that does not mean all data scientists will get the same outputs as each company has different volume of data and it depends on how deep the analytics is performed. Not all big data will provide sophisticated insights with value. Therefore, industry leaders must ensure investing in their own data will be profitable and is aligned to their business capabilities, people skills and corporate vision.

Today’s financial services firms that are seeking to compete by leveraging big data analytics, their winning data strategies will be structured like this:

  • Management: Data Migration, Data Selection, Data Storage, Data Testing
  • Analytics: Data Structuring, Data Analysis, Machine Learning, Data Visualization
  • Outcomes: Success Metrics, Business Decisions, Monetization, Market Leadership

Data is a tangible asset that never depreciates, using valuable insights from it is a future-proof strategy. As competition is a moving target, therefore, businesses must analyze as they go.

About the Author

Hassan Mohamed is a London-based analyst specializing in financial operations and credit management in EU markets. His articles have been featured in international publications such as British Computer Society, Investing.com, Medium.com, Al-Quds Al-Arabi and Wall Street Italia covering topics as economics, fintechs and IT.


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Comments

  1. I like how you gave tips about big data, this is quite hard to understand and I like how you easily explained it. I like how you included the inclusivity of the product and it is not full of jargon. Financial services need to be inclusive so that every consumer can access the product and it can be of relevant use to consumer’s lives.