Fintech, Data Science and Business Initiatives

Initiatives - NYU Stern

Data, structured or unstructured, can provide key insights for business development. Experts hailing from a variety of disciplines have learned to enhance their methodology with statistics and algorithms. These advancements have led to a new field called data science.

A business’s success largely depends on its finances, whether the money is going out or coming in. Data scientists can help businesses stay on top of their capital and maximize profits. This fusion of money and computation has created fintech (financial technology).

Companies such as Cane Bay Partners have been providing businesses with insights into how the market will go and what decisions are best. Many companies have flourished due to enhanced predictive ability and precision. Financial choices largely boil down to complicated math, so it helps to have a skilled technician on hand. A data scientist can sift through big data and find what works and doesn’t work.

Security

One of the stigmas associated with fintech is a perceived lack of security. While large institutions such as credit unions and banks are strictly regulated by the government, small startups tend to have more freedom. Some people might like this because they feel that fintech services will be less of a hassle. Other people might prefer to go to a bank because they feel that it’s safer. Data scientists can help companies strengthen their systems against security breaches, fraud and other nefarious activity. Good security measures will not only protect the company but make the clientele feel more comfortable about their transactions.

Lifetime Value

When a business goes by one transaction at a time, it can miss out on long-term client relations. Not every customer is the same. Some are more likely to spend a great deal of money on one purchase, while others tend to make many small purchases over time. There are also customers who spend a little and then are never seen again. A data scientist can analyze different patterns and determine a customer’s lifetime value. Surveys, social media and purchasing history are just a few things that can be considered. Accurate valuations should enable a business to use targeted marketing, upsells and other techniques to increase revenue.

Risk Evaluation

Even before computers and the internet, risk has always been an important part of financial planning. When a business doesn’t evaluate risk efficiently, it can run into trouble with capital, staffing and customer retention. Data science allows a company to hone in on risk factors with as much accuracy as possible. The process can involve elements that a layman can easily overlook, such as phrasing and typing speed. Data scientists know how to combine subtle nuances with traditional risk assessment methods. With the right foresight, a company can make game-changing investments, take safe loans and expand its reach with confidence.

Fintech is set to grow exponentially over the next decade due to the popularity of data science in universities and training programs. Many young minds are flooding the industry with ideas on how businesses should adapt to modernity. Whether a company is old or new, it’s important to keep up with technology.