Grow VC Group | Jouko Ahvenainen | Jun 2018

Data and AI started to come fundamental components for FinTech in 2017. There are several reasons for this development, for example, the development of machine learning and data analytics solutions, growth of FinTech services to have enough data, and new cloud based infrastructures that make it easier to use data. We can expect this development continues and accelerates in 2018.

At the same time, blockchain, distributed finance models and increasing privacy concerns will change data requirements and models. Data is coming a fundamental enabling component in the finance services, and it will give also more power to customers.

Data to enable customers

Everyone today knows data has a lot of value. “We try to collect all possible data, and then we find a model to monetize it, maybe sell to advertisers,” is a common sentence in many business plans. “We help companies monetize their data,” is another typical value promise. “Let’s offer our solutions for free, if we can get the data,” is a ‘sales strategy’.

Is it so simple that you offer software, apps, and services to consumers and companies, utilize their data and create a big business? It really isn’t that simple anymore, because

• so many parties want that data,
• most users are becoming smarter with their data and asking more questions about their data,
• data doesn’t have uniform value,
• authorities create rules about the use of data, and especially
• most data utilization is marginal optimization, not real value to customers.

Finance institutions and credit scoring companies collect data specifically to manage risks, for example, to decide, if a customer is allowed to get a loan. There are several new credit scoring companies, especially in the emerging market, but also in developed countries, that collect much richer data, e.g. social media, mobile and finance apps data. Typically, consumers don’t even exactly know what data is collected and how it is used. Or the consumer learns about the data when hackers steal it, like from credit rating agency Equifax. One could also say that the use of this data is very one-sided. Finance institutions use this to make decisions about customers and product offering for them, but it doesn’t really help customers to find the best deals.

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These above examples are about cases involving companies collecting customer data and wanting to utilize it make better business by optimizing some of their operations like marketing, risk management or product offerings. But the real value for those customers is often very limited. This means those companies can improve their business a few percent, but it is not disruptive or game changing. Google changed the game, it collects a lot of data, but its services have been also much more direct value to users than analytics from many other companies.

Many companies still see that the way to utilize data is to optimize their own operations to generate more revenue or cut costs. They don’t want to empower customers properly to utilize that data in the services that customers could get direct value. For example, finance data should not be used only by a lender to make a loan decision and adjust interest rates, but it should enable a customer to have a better user experience and find the best loan and interest rate.

Data is the black gold, but to get the full value, it cannot only be a one-sided marginal optimization. All parties must be able to utilize it and build totally fresh solutions. If oil companies had used oil only internally to offer transportation services, it wouldn’t have changed the world, created free mobility and huge businesses. Oil became the black gold when people got cars and other vehicles and got freedom to move based on their own needs. The data business must learn to be an enabler, not just a one-sided optimization tool.

Customer control and distributed models

Regulators, authorities and law makers have become more interested in the use of data. One example is EU’s General Data Protection Regulation, GDPR, that gives more power to consumers to know his/her data and control the use of them. Generally, authorities and consumers see it as more acceptable to collect and use data if the consumer can see and control the data, and if consumers also get real value from it.

The question about ownership of certain data is not simple. One can argue that an individual should own all the data that is from her or him. Someone else can argue that if you use a bank account or credit card, the bank or credit card company in question owns the data linked to those accounts. It is a little bit like, if two parties have a phone call, is it both of them or neither of them that own the rights to the call and can for example publish it?

Probably the fundamental question isn’t who owns the data. The question is, who can use it and for which purposes. Now the situation is not in balance. Companies collect all kinds of data from individuals, sell it to other companies, combine it with other data sources, and utilize it for their own business. At the same time, consumers often cannot even have their own copies of this data, don’t know to whom their data is sold, and how it is combined with other data sources. When all the data was in paper form, the situation was probably better for consumers, they at least had their own papers at home.

Finance services and health care are two areas where companies have a lot of data from people. It is often also very sensitive information in nature. There are many companies in those industries, and people often use services from several companies. It is often valuable too for the consumer that companies can share information between them. For example, when you go to a doctor or hospital, it can help in your treatment that they know your medical history, and when you apply for a loan or use wealth management services, your finance history helps to find the right products and make decisions. But it must be consumer’s decision to share this data.

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Consumers should also have their own copy of their data and the ability to use it when it offers value for them. For example, they could go to a new hospital and insurance company with their personal medical history, or apply for a loan or make personal finance planning with their own data.

We have had two parallel, but slightly opposite, developments with the internet. While each individual can generate more activity - for example publish his or her photos, articles and have their own e-commerce site - the data is concentrating more to some central places, such as to big companies, data aggregators, and data processors (for example Equifax or online marketing platforms). Now we can see developments that we could move to more distributed models with data too and individuals could get better control over their data.

This technically is also linked to blockchain development that particularly has an impact on the finance industry. Blockchain basically distributes finance data, transactions and authority around the Internet, to individuals and their nodes. A person can have her or his own bitcoin and cryptocurrency wallet, which is not the account of a bank or finance institution. Now we will see solutions where people can have their own safebox for their finance, health care, and other data.

Lawmakers will probably try to give further rights to consumers to control their own data; in some countries sooner, some later. But new distributed ledger and data models can empower consumers sooner to take control and impact the balance. In finance and data services we can see development that the control and databases will be distributed. It is not anymore a hierarchical centralized model to manage data, but it will be a distributed model with the consumers in control.

Case: Real time data in SME lending

SME lending can be profitable but at the same time a bad business for banks. The reason is that SME loans are seen as a high-risk liability, and have an impact on capital ratios and the price of capital. The 2007 finance crisis also demonstrated, how the packaging of loans contains significant risks and removes transparency from the debt market. Fintech and data analytics can change this.

Decades ago banks and other lenders typically knew their customers better. Now data analytics makes it again possible. For example, the accounting data with other data sources can be used directly for lending decisions, and the data can be also be used to price loans on the secondary market.

The main data sources are 1) 3rd party data providers, and 2) borrowers, especially their online accounting systems. Data makes loans more transparent in the secondary market and helps price them and also attract investors in the loans. It is possible to develop solutions, with true real-time pricing for each loan in the secondary market. It is also decreases risks of the traditional securizitation.

Data oriented SME loans will change the market. SME lending is a significant business opportunity for banks, but also for alternative finance lenders and p2p lending services. Data oriented SME lending framework offers the leading solution to implement lending services that fully utilize available data, offer better value for SME companies, lenders and loan investors. It also improves bank’s opportunities to operate in this market due to capital ratio requirements.

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Summary

Data analytics and AI will change many finance services. They will replace work as they have done already to analyze agreements, make trading and analyze investment opportunities. The significant change is that data and AI enable customers in a new way in the finance services. Data analytics and AI come also to all daily services, especially for the lending business, and daily customer services. Cryptocurrencies, distributed ledger ecosystems and cloud based services will changes implementation, architecture and business models of many finance services, and they will have impact on models to use and utilize data too. As a whole data and AI service development is one of the most important FinTech components in 2018.

Jouko Ahvenainen is a serial-entrepreneur, e.g. co-founder of Grow VC Group, a pioneer in new funding solutions, including equity p2p investments. He participated in changing US finance regulation, getting the Senate and President to allow crowdfunding and has worked with EU finance regulation. Jouko started his work with crowdfunding models in 2008.  Jouko is a founder, partner and board member in several innovative digital finance companies. Jouko is also an advisor for US, European and Asian investing and finance programs. He has especially worked to plan and implement models to get crowd investing and institutional investor models to work together.

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