Hiroshi Nakaso: Big data - its impacts on economies, finance and
central banking
Speech by Mr Hiroshi Nakaso, Deputy Governor of the Bank of Japan, at the Fourth FinTech
Forum, Tokyo, 1 November 2017.
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Introduction: Data and Power
It is a great pleasure to welcome you all today to the fourth meeting of the FinTech Forum. Today
I would like to talk about big data and its utilization.
The importance of data itself is not new to all of us. History tells us that many kings, lords, and
governments, put their first priority on collecting data to understand their lands' geographies,
populations, and taxable capacities. Furthermore, they made efforts to utilize the collected data. It
has been the source of their political and economic power to collect high quality data and utilize it
efficiently.
Today, in light of the development of the Internet, smartphones, and SNS, the amount of data
flowing into our society has been rapidly increasing. On the other hand, new technologies such
as artificial intelligence (AI) enable us to process large volumes of data in a swift manner. Against
the background of these rapid increases in the volume of data, and significant improvements in
processing capacity, big data draws significant attention as a potential game-changer in our
economy and society.
To describe how data utilization has evolved over years, I would like to use the example of maps.
Over the years, many people have attempted to make maps as accurate as possible, which
have provided us with remarkable benefits. Even today we enjoy the benefits of using
geographical data, such as "Google Maps." However, what is different from the past is that we
are no longer users of data only. Our access logs to these services themselves constitute a new
set of big data, and potentially have their own value to be utilized. In today's society, data is a kind
of resource, and power belongs to those who are able to collect and efficiently utilize such big
data. It is analogous to the economic power of countries with large amounts of petroleum
resources, which was increased after they enhanced their processing capacity and sales
channels.
I. Economic and Financial Developments and Data Utilization
History of data utilization
The world economy has also developed along with the evolution of data utilization. In this sense,
one of the largest breakthroughs in economic history was the birth of money.
When people exchanged goods, or bartered, the values of these goods were measured only in
relative terms on a bilateral basis. However, the birth of money enabled them to use a common
measure of value, and turned the value of each good into a datum, called a "price." Such price
data also served as a foundation for the pricing mechanism to adjust the demand and supply of
goods.
Moreover, money made it much easier for people to trade with each other. Under the bartering
system, each participant had to find a counterpart with a mutual demand for trading. However,
money's intrinsic function of representing value, i.e. its price, has enabled people to trade without
necessarily finding such a coincidence. Since money contains data about prices, it also made it
easier to store wealth by keeping it in the form of money. This feature has also enabled us to do
"inter-temporal trading", such as obtaining money by selling a fish yesterday and using it for the
purchase of fruits tomorrow.
Data Utilization Today
As those episodes suggest, data utilization and the development of the economy have been
strongly connected with each other. Today it is not an exaggeration to say that every economic
activity is inseparable from collecting and processing data. For instance, demand forecasts, and
production planning and inventory management by firms, consist of large amounts of data
processing.
Above all, the financial industry is one of the most data-oriented businesses. For example, the
operations taking place on the back of our daily payments and settlements via credit cards, debit
cards, or deposit accounts, can be regarded as data processing. Banks provide financial
intermediation services through making complicated decisions and assessments on borrowers,
interest rates, and assets for investments, by collecting and analyzing various types of data.
Insurance companies design insurance policies and set their fees at appropriate levels by also
collecting and analyzing data. These insurance schemes allow society to efficiently redistribute
risks among various entities, and enhance its resiliency against future uncertainty. As such, the
financial and insurance industries have indeed promoted economic growth in modern and
postmodern society.
II. IT Revolution and the Potential of Big Data
The emergence of big data
Unlike tangible assets, information and data never depreciate. Data also has an interesting
feature; that is, the marginal benefit of data may even increase as more data is collected and
accumulated. In the past, collecting, storing, and processing, large amounts of data had been
difficult in many cases due to technological constraints. Today however, the IT revolution has
been changing the situation unprecedentedly and enabling efficient collection, storage, and
processing, of gigantic amounts of data.
This drastic change can be easily seen in the quantity of data. As the Internet, smartphones, and
SNS, are expanding, the amount of data flowing in our economy is also increasing very rapidly.
This is the emergence of big data.
Moreover, in accordance with the IT revolution, more tactical and sophisticated methodologies for
collecting data have become available. For example, unlike the past when doing paper-based
surveys was the main instrument to collect customer data, firms have become able to obtain
data without direct contacts with customers or individuals. For example, they can collect data
that people disclose on the internet via SNS voluntarily, or that their customers input when
conducting searches, or from e-commerce websites.
Firms can also collect data even without their customers' explicit intention to provide data. For
example, they can collect customers' data related to their purchasing activities by offering new
digitized payment instruments, or obtain customer information by offering economic incentives
such as special discounts to customers that provide their data through loyalty cards.
Another remarkable change has been seen in the capacity to process data. Today we are
becoming able to process big data very rapidly by utilizing innovative information technologies
such as AI. Furthermore, a large amount of graphical or sound data, which was difficult to use in
the past, is becoming easier to be efficiently utilized through technologies such as "deep
learning," in which AI automatically learns by itself through digesting such data.
Potential of big data on the economy
As such, rapid increases in the volume of data, and significant improvements in its processing
capacity, are exerting a big influence on the economy and financial services.
Currently, companies such as Google and Amazon, which are now at the world's top level of
market capitalization, are collecting and leveraging big data through utilizing their platforms
covering the world, and making it a source of their added-value and profits. In this regard, big
data can be seen as a new type of "asset," in terms of a profit source, instead of traditional fixed
assets such as branches. Indeed, neither Google nor Amazon has physical "branches" in a
traditional manner.
Moreover, new businesses such as the sharing economy, can also be made possible by utilizing
big data for connecting various idle resources and needs scattered all over the economy.
For a wide range of companies, including giant global companies or new industries, the utilization
of big data and AI may improve productivity in various ways, such as accurate analysis on
demand, more efficient business processing, and enhancing added value.
In emerging and developing countries with large populations, several e-commerce enterprises,
backed by rapid popularization of smartphones, accumulate gigantic amounts of customer data,
and the utilization of that data has facilitated the expansion of various businesses and economic
activities in those countries.
Potential of big data on financial services
Big data may also extend the frontiers of financial services.
Firstly, financial services themselves can be more sophisticated through effective use of big
data. By using customers' transaction data to grasp their needs and analyze risks, it becomes
easier to provide customized financial services tailored to each user, and to flexibly adjust the
contents of services if necessary.
For example in the field of insurance, in order to overcome "adverse selection" and "moral
hazard," which have been regarded as inherent problems in the insurance industry, efforts are
being made to finely adjust the insurance fees by using a new technology known as a "smart
contract," and collecting a wide range of data such as how customers drive, and how they
manage their health.
Moreover, new authentication technologies such as biometrics authentication through big data
analysis enable customers to use various financial services in a more secure manner.
Secondly, big data may facilitate the networking of financial services with broad industries. For
example, safe and efficient payment instruments are extremely important for e-commerce and
the sharing economy. On the other hand, data obtained through these businesses can be useful
for providing and customizing financial services. Consequently, new networks between financial
services and various industries can be established, such as linking retail sales businesses with
payments, loans, and insurance services.
Thirdly, big data may also enhance financial stability through facilitating refined risk management
and the efficient allocation of risks. However, when a variety of entities which are different from
traditional financial service providers enter financial services, central banks are required to
closely monitor their impacts on financial stability and their structures.
Data security issues
Along with the enhanced utilization of big data, cyber security, data protection, and stakeholders'
consent on the usage of big data, are becoming all the more important. Since "trust" has an
important meaning especially in finance, these issues are becoming critical factors for
maintaining the stability of payment settlement systems as well as financial systems.
Recently, enormous amounts of non-anonymized data such as, who bought what, when, and
where, are being collected. While such accumulation of non-anonymized data substantially
enlarges the potential of data usage, the relevant entities are required to pay extremely careful
attention to data protection and privacy.
If people were to worry about the practices of managing big data and feel uneasy about their own
privacy, it would become difficult to make big data contribute to economic development and
welfare. Thus, I would like to ask all the relevant entities, who collect and utilize data, to pay due
attention to ensuring data security.
III. Big Data and Central Banking
Big data also has substantial implications for central banking.
All the operations and policy conduct of the central bank are closely linked with data collection
and processing. Every operation including the settlement of funds and securities, and the
processing of treasury funds through daily operations of the central bank's system, the core
infrastructure of the economy, is made up of gigantic amounts of data processing.
In carrying out macro policies such as monetary policy, it is an important precondition that policy
entities including the central bank can collect and analyze various types of economic data quickly
and efficiently, and timely grasp the developments of aggregate demand, general prices, and the
impacts of policy actions on the economy and financial markets. Indeed, many central banks,
including the Bank of Japan, are collecting and aggregating large amounts of data such as price
statistics, corporate surveys, and financial market data, by themselves. Since central banks are
processing as well as utilizing large amounts of data, central banks are required to continuously
examine how to utilize and leverage new technologies for collecting, processing, and analyzing
various types of data.
IV. Closing Remarks
I think that big data has great potential to vitalize various economic activities, innovate financial
services, and increase economic welfare, as long as data security is firmly secured.
In the well-known movie "Moneyball," open-minded and thorough analysis of data, free of
prejudice and convention, leads to the finding of new and advanced strategies that drastically
change traditional baseball tactics. Also in volleyball, the current offense strategy with multiple
options of attack including those from backguards, which is supported by precise data analysis,
has been widely adopted in recent years, which I could not imagine when I was coaching high
school students decades ago. As such, analysis and utilization of data has demonstrated its
potential in various areas more than ever before.
Given rapid increases in the volume of data and significant improvements in its processing
capacity, I also have great expectations for the possibilities that utilizing data will increase
opportunities for serendipity, that is, lucky encounters with unexpected discoveries or events, and
will lead to creations that open up new frontiers. I believe that big data has huge potential to lead
to new creations and value-added seeds which are free from prejudice, going beyond the
psychological "wall" formed by conventional business customs. I think that such cases are
already being seen.
In order to maximize the opportunities for such serendipity, positive dialogues among a wide
range of stakeholders are critical and indispensable. I would be very happy if this forum could
become the place where such new creations and discoveries are made.
I would like to close my remarks now by wishing that today's FinTech Forum be fruitful for all the
participants.
Thank you for your attention.