What did the two data scientists do to the financial industry?

Let's explore some industry-specific examples to understand the value that different industries gain through the adoption of AI.

Let's start with the Fintech industry.

What is Fintech industry?

Fintech, or financial technology, utilizes technology to enhance and revolutionize financial services and procedures. It covers a broad spectrum of applications and solutions designed to streamline financial transactions and services to make them more efficient, accessible, and user-friendly. This can encompass online banking, digital payment systems, blockchain technology, robo-advisors, peer-to-peer lending platforms, and cryptocurrency. In essence, fintech merges finance and technology to improve how individuals manage, invest, and engage with their finances.

The two data scientists and the financial industry:

Financial institutions value data as a critical asset and are winning today; in this story, we will understand how investing in data assets pays off.

Idea:

The Success Story of Capital One Bank Richard Fairbank the founder, Chairman, and CEO of Capital One.?Capital One is a national, brick-and-mortar bank that mixes elements of traditional banks and online-only financial institutions. At the same time, it's best known for its rewards credit cards. Capital One was established in 1994 after spinning off of Signet Bank.

We have to begin the story from the late 90s from the little Signet bank, where the transformation of the business of consumer credit began.

There was a time when credit cards had uniform pricing because there was no sufficient data to deal with credit cards' different pricing on a massive scale, and banks believed customers would not stand for price discrimination. What! How old school were they? But we see this for the future, and we also know people from the future will give a What! Expression of the Myths We Have in the Financial Industry.

Richard Fairbank and Nigel Morris, two data scientists with backgrounds in finance and consulting, played a pivotal role in the success of Capital One. Their expertise in data science and vision for the financial industry's future was instrumental in the transformation of Capital One.

They believed that they could provide sophisticated solutions using predictive modeling

Richard Fairbanks and Nigel Morris went to big and small banks with their idea of using data science to turn customer data into actionable business intelligence.

They were shot down by all but?Signet Bank, a small financial institution based in Virginia.

Richard Fairbanks and Nigel Morris persuaded the management of Signet Bank that employing predictive modeling would be a beneficial strategy. They recognized that a relatively small number of customers contribute to over 100% of a bank's profit from credit card operations. By accurately modeling profitability, the bank could tailor more attractive offers to its most valuable customers.

Implementation:

There is always a big problem to solve in an unprecedented journey. Yes, Signet Bank also had one. In an extraordinary journey, Signet Bank encountered a significant challenge. The bank needed more data to analyze profitability effectively, making it difficult to tailor loan terms to individual customers. Traditional banks typically provided credit based on predetermined terms and a specific default model, which limited their ability to assess the profitability of alternative terms for different customer segments. This was because they only had data to analyze the profitability of previously offered terms, primarily for customers who met the criteria defined by the existing credit model.

Signet Bank adopted a fundamental data science strategy by strategically investing in data acquisition as a pivotal business asset. The focus shifted to assessing the willingness to invest and the associated costs.

In the case of Signet, experimental initiatives were launched to collect data on customer profitability under varying credit terms. This involved the randomized offering of distinct credit terms to different customers to evaluate the impact on customer profitability.

The best data science team can yield little value without the appropriate data;

At that time, this was seen as a foolish move by people watching this from outside of a data-thinking context. They were sure that these moves would bring huge losses to the Signet bank, which is true, as it was incurring losses. Still, Signet management is mature enough to consider those losses as an investment to build the data asset because Richard Fairbanks and Nigel Morris have justified the investment spent to build this data asset by walking the management through the value this data asset will be creating.

Monetisation:

"Signet Bank's decision to view the initial losses as investments in data paid off in the long run."

Despite the industry-leading 'charge-off' rate, 2.9% of balances went unpaid, increasing to almost 6%; the losses were a necessary part of the process.

The data scientists at Signet Bank worked tirelessly to develop predictive models from the data, assess them, and implement them to enhance profitability. Despite facing objections from stakeholders, the company considered these losses as long-term investments in data and persisted with their efforts.

Signet Bank's success story highlights the importance of taking a long-term view of data investment.

The credit card division at Signet Bank experienced a remarkable turnaround and became highly profitable. Subsequently, it was separated from the bank's other operations, which were overshadowing the success of consumer credit.

Fairbank and Morris implemented data science principles across the business.

Following this, Signet Bank sold its operations to Capital OneBank, where Fairbank and Morris played instrumental roles in growing Capital One into the largest credit card issuer with one of the industry's lowest charge-off rates. This transition was mutually beneficial for Bank and its customers.

The correct data often can only substantially improve decisions with suitable data science talent.

Challenges Capital One faced:

Capital One faced several challenges when it first entered the industry. These challenges included skepticism from the industry, a lack of track record and reputation, securing initial funding and capitalization, understanding and adhering to regulatory requirements, and establishing the necessary technological infrastructure.

One of the major challenges for Capital One was the skepticism from the industry due to its nonconventional approach to credit card services. The use of data and technology for credit decisions was a departure from conventional risk assessment methods, leading to initial resistance from the traditional banking industry.

As a newly formed company, Capital One had no known track record or reputation in the financial services industry, making it difficult to gain the trust of customers. Additionally, securing initial funding and capitalization was a significant hurdle for the company. Understanding and adhering to regulatory requirements, as well as establishing the necessary technological infrastructure, were also challenging tasks for Capital One.

Furthermore, entering a highly competitive market dominated by established banks required effective marketing and differentiation to convince customers to switch to a new bank in the industry. Economic conditions and fluctuations also presented challenges, particularly during periods of economic downturn.

Consumer education was another significant issue for Capital One, as it required effective communication and marketing to convey the value addition of their approach to credit cards and the use of technology in financial services.

Despite these challenges, the founders of Capital One, Richard Fairbank and Nigel Morris, demonstrated strong determination and commitment to innovation. This allowed the company to overcome initial obstacles and establish itself as a pioneering force in the credit card and broader financial services industry.

Success of Capital One.

Capital One's remarkable financial performance is a testament to its forward-thinking approach. Through embracing fintech, the company has achieved impressive growth across its revenue, earnings, and assets under management.

Capital One's leadership in innovation and technology has ensured its continued success in the financial industry. By diversifying its services and focusing on customer satisfaction, Capital One has demonstrated a commitment to meeting a broad range of financial needs. Strategic acquisitions have further solidified its position as an industry leader, driving its continuous evolution and growth.

Conclusion:

Two data scientists from the late 90s have brought so much value to the Fintech industry; considering the technological advancement we have today, are we taking advantage of dominating the financial industry? Just applying the technology is not going to take us anywhere. Business leaders who can understand the pain of your institution and the customers can bring creative thought processes and break the myths that are stopping us from evolving and becoming unstoppable by enlighting the technical experts with the right problem to solve the collaboration of the Business and technical leaders with the AI are essential for the Fintech journey to today's world.