The FinTech revolution is truly transforming the way that we manage our money, bringing new online banks, new models for insurance provision, new ways to access loans, and much more. It rests on a number of pillars, but one of the most important is that of big data.
With big data, both new, digital-native fintech startups and traditional banks can gain better insights into their customers’ needs, detect and act to respond to risks and opportunities while they are still on the horizon, trim operations to be more efficient, raise their security levels, and more.
But big data alone isn’t enough; if data is the new oil, as the saying goes, then it needs to be refined before it can be utilized as fuel. Business intelligence (BI) technologies are the data refineries of the modern age, shaping the development of fintechs and determining the direction that financial services will take for the long term.
Here are five business intelligence technologies that fintechs are using now, and could adopt in the near future, that will underpin the new products and interfaces that fintech is offering and help direct their growth.
When fintechs switch to cloud data storage, it has a transformative effect on all subsequent BI processes. Cloud data storage services are scalable and cost-effective, more secure, and more resilient, encompassing a range of cloud data services.
A cloud data warehouse opens up access to a greater range of BI tools, while data lakes break down silos and integrate data for BI crunching, helping fintechs build their data science ecosystem. BI specialists from fintechs would do well to compare their options here, understanding the differences between Snowflake vs Redshift, for example.
Moving data to the cloud means that it can be updated in real time and brought in from more sources, resulting in faster data crunching that allows financial services companies to respond more quickly to applications for loans, insurance, credit, etc. It increases the range of data that fintech companies can draw on in assessing applications, reducing the risk of fraud and enabling financial services providers to learn more about the applicant when considering their request, rather than just relying on the blunt tool of credit score.
BI tools have moved on from spreadsheets and manual analytics to more powerful advanced analytics which use artificial intelligence applications like machine learning (ML), deep learning (DL), and natural language processing (NLP).
With advanced AI-based BI analytics, fintech companies can find new opportunities to expand, such as identifying new markets, investigating their pain points, and developing new products to meet those needs. For example, new fintech banks are offering business bank accounts and credit cards to creators and influencers whose businesses don’t match the expectations of a traditional bank. At the same time, companies can judge exposure to risk more closely and finely for better business decision-making on a higher level.
In addition, AI’s enhanced ability to draw together massive datasets from disparate sources will form the foundation for new partnerships with non-financial players. McKinsey estimates that AI applications can generate up to $1 trillion in additional value each year for the global banking industry.
Blockchain is already transforming a great deal within the financial services sector. It enables real time financial transactions in zero-trust environments, enables the real time tracking of high-risk goods that secure investments, and supports blockchain wallets and cryptocurrencies. But when combined with BI tools, it can do even more.
Fintech companies can secure data on the blockchain so that it can’t be erased or altered unnoticed, making sensitive customer data far more secure. BI insights stored on the blockchain can have a value in their own right, potentially opening up new revenue streams for financial services companies.
Blockchain data can be more easily shared between partners, since there’s far lower risk of it being tampered with along the way, which also helps facilitate information sharing with new partners.
Like advanced analytics, automation and robotic process automation (RPA) both rest on the foundation of artificial intelligence (AI). Automated data preprocessing means that the data is higher quality, more reliable, and ready for use by BI tools in a much shorter space of time, which in turn means that BI insights are more trustworthy and produced far more quickly.
Banks and financial institutions can automate a great number of BI processes including reconciliation, fund appropriation, tracking price movements for stocks, shares, bonds, commodities, and other assets, and more. With the help of automated BI tools, fintech companies can spot suspicious transactions faster to reduce fraud and increase customer trust.
When it’s so much faster and simpler to reach BI insights, fintech companies can allow customers to access their own data in new and meaningful ways. Self-serve customer portals and customizable data visualizations allow customers to view their recent spending, predict future cash flow, compare income and expenses between different months, and carry out other data exploration activities independently.
The proliferation of connected Internet of Things (IoT) devices permit fintech companies to gather real time data from many more sources and viewpoints to feed into BI analytics, making insights richer and more valuable.
For example, IoT devices can track shipping conditions and progress for better logistics financing. Insurance companies are starting to offer lower premiums for health insurance customers with wearable health monitors, car insurance customers with vehicle trackers, and business insurance customers with sensors that measure air quality in the workplace.
BI analytics of IoT data allows insurers to give more personalized and accurate quotes, and to spot gaps in the market for new products. Research found that the global IoT banking and financial services market will grow at a CAGR of 55.3% between 2019 and 2027.
The growing number of BI technologies is having a profound effect on the developing fintech sector. Innovations like advanced analytics, automation, blockchain, IoT devices, and cloud data storage are part of the fabric of the fintech market. Smart eyes are watching this space to see which direction fintech will take as BI tech continues to evolve.
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