How big data transforms FinTech in the Nordics

Technological advancements have shaken up the financial service industry. The way in which banks used to operate was plenty of bureaucracy and tons of time wasted in queues. Today, we are seeing a swift shift towards a more digitized approach.

The digital transformation of financial institutions translates to a swift process of compliance, almost instant lending procedures and less red tape for both both business and consumer alike. But what it also means is that one can track the behavior, preferences and needs of individual customers better. And, even more importantly, monitor and analyze lifestyles, spending habits and big purchases. The analysis then helps identify the likelihood of, e.g. loan repayment. Needless to say, digitally identifying and preventing defaults outperforms many times risk profiling by traditional credit institutions.

The shift is quite visible in the Nordics…

The fintech market in the Nordics has grown exponentially over the last three years. That’s no coincidence: Scandinavia has the reputation of a hub for innovative solutions in the digital market. The strong fundamentals of the ecosystem lie in the liberal internal market, dominated by innovation-friendly customers. An additional contributing factor is the great synergy between government policy, regulations and entrepreneurial spirit. Back in 2015, Fintech startups collected more funding than any other vertical in the Nordics. Even local favorites like SaaS and e-Sports lose footing for the first time ever, according to “The Nordic Web”.  

What does this transformation mean for businesses?

Access to predictive analytics (hence better decision making) allows fintech startups to leapfrog and challenge big players. Not only does that lead to an exponential growth of modern financial service providers – it also provides huge upsides for the end user.

• Better risk management

  Typically, bankers give out loans considering past repayment history, whereas now more metrics can be included in the equation- allowing for better accuracy. Traditional banks usually take on a lot of bad debts because of customers unable to pay their loans. Тhe fintech industry relies heavily on algorithms (think NeuroChain) for accurate predictions and assessment of risk. By accounting for several metrics simultaneously (spending habits, big purchases and lifestyle) the industry is empowered to make better calls. Symbuka is an example for a company using a “score record engine”, which allows a multifaceted decision tree.

• Tailored Customer Segmentation

  As every modern and digitally focused field of business, in the Fintech industry there is strong customer segmentation. In this regard, fintech companies can easily categorize spending habits depending on age, gender and social class. Which means they can tailor their services and alternate banking products to meet the demand and needs of each customer segment. As people seek for more personalized approach, especially when it comes to their finances, being able to identify valuable customers and giving them unique treatment is a great marketing strategy and a long- term asset. Lunar Way, another mobile banking app born in Scandinavia, is on a mission to attract younger adults between the age of 18 to 25. According to their founder Ken Villum, the traditional banks have lost touch with this segment, whereas modern financial services might have something to bring to the table for them.

• Improved Fraud Detection

  Fraud detection is a key element of the industry and worth mentioning. With the rise of online banking and transactions, everyone is more probable to becoming a victim of fraud than ever. However, being able to track the usual financial habits of users and identifying anomalies is very easy for financial service providers. The go-to approach is to leverage machine learning capabilities based on statistical modelling. The financial institution can quickly contact the account owner in case of any unusual activity – and sort out the issue. BehavioSec (Sweden) is a great example for a company helping other enterprises reduce account fraud and data theft, offering what they call Behavioral Biometrics.

What does big data mean for the average consumer?

B2C businesses fundamentally exist to improve customer service. The added value for consumers is therefore pivotal for their existence and long-term success. So how does big data improve CX?

• Speeding up the process

  As mentioned before, big data is extremely useful when it comes to optimizing the processes, especially concerning evaluating borrowers. They were forced to sometimes wait for days, even weeks on end prior to receiving a decision from the lender. Today, you are approved or declined within hours, sometimes minutes. Moreover, all the red tape once needed for compliance is now obsolete, making credits much more accessible and quickly attainable. According to a recent study by Deloitte, in 2016 more than more than 57% of Scandinavian citizens used mobile banking, compared to only 44% in Europe. Big contributor for these results is Atom Bank, mobile banking app developed in the Nordics.

• Customer orientation

  Fintech startups grow more and more customer oriented. It is what differentiates them from the standard bank in the eyes of the ordinary consumer; and it is their biggest advantage in the industry. What enables customer focus and a tailored approach for them is the data they extract and analyze. Personalization might not seem as important at a first glance, however customer studies disagree. Accenture claims 46% of consumers will be more interested in taking a loan if there was personal guidance. Customers understand the trade-off and are willing to provide their data to companies if this will return better customer experience. A recent success story of Swish brings together 6 large banks to co- develop a payment system. Nowadays, 3.7 million Swedes use it, which is close to 40% of the population.