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Does your FinTech business need data analytics outsourcing?

The proverbial saying “Data is everything” applies not only to the Financial Services and FinTech industries but also to all other sectors. The real power lies in the ability to convert raw data into meaningful and actionable insights.

Data has become increasingly valuable to businesses of all sizes, whether it’s using internet cookies to create customized online experiences or analyzing banking activities to provide budgeting advice. Fintech firms, in particular, are exploring new ways to use big data to challenge established financial institutions by prioritizing the needs of the customer. But what are the key applications of big data in finance, and how can businesses personalize consumer experiences?

Ever since the transition to digital, FinTech has been using data analytics reports to effectively address consumer churn, prevent accidents, and detect and prevent financial fraud and errors. In addition, FinTech has expanded its reach by using big data and quality assurance services, incorporating cutting-edge technologies like the Internet of Things (IoT), Blockchain, Artificial Intelligence/Machine Learning (AI/ML), and intelligent data discovery. These are the primary reasons why SMBs and enterprises prefer to outsource data analytics.

Therefore, let us examine the potential of big data in the fintech industry and provide some advice on how to execute effective customer-focused marketing campaigns

What Makes Big Data BIG?

The idea of collecting data to enhance consumer experiences is not a recent development. Businesses, ranging from local grocery stores to large-scale financial institutions, have been leveraging fragments of data for years to gain a deeper understanding of their clientele. However, the concept of “big data” provides companies with an abundance of consumer information that has the potential to revolutionize the financial industry.

The Role of Big Data in FinTech

The FinTech industry is projected to attain a valuation of $28,529.29 billion by 2025, with a Compound Annual Growth Rate (CAGR) of 6%. The proliferation of mobile devices has led to a surge in FinTech product and service adoption among clients. Furthermore, with each interaction and usage habit being logged over time, the quantity of data generated per second by users has grown exponentially.

However, this presents both opportunities and challenges for most FinTech firms.

If your FinTech company is unable to harness this vast amount of data to enhance client experiences, it may be setting itself up for failure. Nevertheless, quality assurance services such as advanced data analytics and intelligent data discovery skills can work wonders for your FinTech venture.

How big data helps fintech companies to serve their customers better

Financial technology and big data intersect in several areas, creating a symbiotic relationship that benefits both service providers and customers.

Big Data Processing

  • Real-time data processing simplifies the task of monitoring users’ activity in online and mobile applications for later analysis.
  • Data mining techniques allow for a deeper exploration of vast amounts of unstructured data stored in data lakes, enabling the extraction of relevant insights.
  • Customizable dashboards that display data visualizations provide a clear and concise view of the most critical aspects of key business processes.
  • Stream computing systems gather data streams from applications and IoT networks, analyze them in real time, and provide clean, usable data sets.

Data Analytics

  • Advanced risk analysis algorithms use artificial intelligence and machine learning approaches to improve accuracy.
  • Data-driven decision-making employs big data analysis and AI/ML algorithms to suggest the best course of action in complex scenarios.
  • The use of intelligent decision-making and automation in business processes reduces service delays and enhances the customer experience.
  • Marketing teams can monitor brand image in social networks and detect concerns early on by utilizing continuous social analytics, resulting in a high CSAT (customer satisfaction) score.

Data security

  • Big data is instrumental in creating highly detailed customer profiles that are utilized to ensure the safety and security of users’ identities and personal information, which is especially critical for financial institutions.
  • Quality assurance services such as artificial intelligence (AI) and big data are increasingly being used to identify suspicious activity and prevent fraud and sophisticated hacking attempts.

In the present day, data management practices and techniques such as extensive data collection and 360-degree data analysis are essential components of every financial institution and fintech company. Artificial intelligence and big data play a vital role in enabling these companies to collect, process, and analyze large amounts of data in real time, resulting in improved decision-making, enhanced customer experiences, and better security.

If you’re looking to leverage AI and big data to strengthen your financial company idea, Transform Hub can assist you in unlocking the full potential of this revolutionary technology.


Applications and Use Cases of (Big) Data Analytics in FinTech

Big data analytics has numerous applications in online banks, FinTech startups, and existing financial institutions beyond simply transforming data into useful information. In the FinTech industry, there are various ways in which big data analytics can be used in conjunction with modern technology to benefit your FinTech company. Here are some examples:

1. Big data in insurance

Insurance companies have been using statistical and demographic data for a long time to price their insurance policies. However, this data is no longer sufficient to create accurate policies, resulting in financial losses for the companies. Modern insurance companies are utilizing big data to create low-risk insurance packages.

For instance, many vehicle insurance companies are analyzing risk and modifying policy offerings based on data related to road accidents and other factors. This enables them to offer personalized insurance packages that reflect the risk profile of each customer.

2. Big data analytics in digital payments

Various financial technology (FinTech) companies have harnessed the power of big data and machine learning to bolster their fraud detection and security measures. The current trend in online payments is the amalgamation of payment processing and sales, whereby consumers can obtain loans in mere seconds. To evaluate risk and determine the amount of credit available to customers, machine learning algorithms and big data are integrated into the online method. This has resulted in several FinTech firms observing a boost in their conversion rates.

As part of their quality assurance services, a few financial payment firms cater to the needs of young professionals by providing them with the necessary tools to effectively and securely manage their finances, invest, and save.

3. Big data technology in real estate

The field of real estate necessitates the continuous monitoring of market fluctuations, the use of adaptable pricing strategies, and the dissemination of comprehensive property details to maximize sales and increase profits. To achieve this goal, it is imperative to gather data from multiple sources and meticulously analyze it to tailor bespoke solutions for targeted clients. This can be further augmented by leveraging the power of big data analytics to minimize the risk of customers failing to make timely payments.

4. Big data in lending

Microfinance institutions and other lending organizations have the option to utilize AI models and big data analytics to facilitate the provision of credit loans to a wider range of individuals. This approach affords two distinct benefits. Firstly, your FinTech enterprise can promote financial inclusivity among the target demographic. Secondly, the adoption of such loans can augment the overall revenue of your FinTech company.

Additionally, the availability of quick loans stimulates economic activity and fosters the growth of other businesses.

5. Predictive data analytics in wealth management

Predictive data analytics can play a vital role in wealth management by bridging the gap between corporate expectations and client demands. By leveraging valuable customer information, you can develop more comprehensive client profiles, leading to better customer retention rates. This allows for the creation of personalized offerings for different demographics, ranging from student loans to retirement plans.

Moreover, predictive data analytics, as part of quality assurance services, facilitates customer segmentation, the delivery of customer-centric goods and services, and operational optimization. This is precisely why organizations of all sizes have embraced data analytics services to enhance their overall client experience.

Now that we have established the significance of data analytics insights for your FinTech enterprise, it is crucial to consider outsourcing data management services. This can assist your business in optimizing its data analytics capabilities and leveraging the insights gained for sustained growth and success.

Big Data in Fintech is The "New Big Thing"

The value of analyzing client data in the financial services industry cannot be overstated. To stay competitive in the ever-evolving field of FinTech, only outsourcing big data analytics solutions can keep companies ahead of the curve.

A growing number of business owners are outsourcing their analytics needs to acquire the data and insights they require while focusing on other essential aspects of their organizations. Having experts handle the time-consuming task of statistical analysis and idea generation is both cost-effective and efficient.

Real-world use cases demonstrate how incorporating data analytics into customer service solutions can help improve FinTech products.

How Can Netlink Help You with FinTech Data Analytics Solutions?

As extensive data analytics outsourcing in FinTech continues to gain popularity, it is likely to become a crucial element for major companies and businesses. By utilizing big data, your FinTech company can offer clients seamless service across all channels, leading to improved efficiency and customer satisfaction. Netlink has spent several years developing data management and quality assurance services and solutions that have been successful.

We can offer customized data analytics services to meet the needs of your FinTech company, including analytical consultancy and data visualization.