
Financial Technology
A Dummy’s Guide To Financial Predictive Analytics Software
By TechDogs Editorial Team

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Overview
What if there are significant and unpredictable expenses? Imagine your car breaks down and the repairs burn a hole in your pocket. Or, completely hypothetically, you are bitten by a spider and have to bear medicinal expenses? (To add to the misery, you don’t even turn into Spider-Man!)
Our point is, wouldn’t it be easy if someone from the future could predict expenses and whisper them in your ear? While that’s impossible, the next best thing is to leverage technology to predict future expenses, earnings and other fiscal metrics.
Yes, we’re talking about Financial Predictive Analytics Software – read on!
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Every business, no matter the size, industry or age, needs robust financial operations. If money isn’t managed well, even large businesses can go bust. One critical aspect of managing the financial operations of a business is predicting its future financial demands and whether the business can meet them.
This is where businesses need a friendly, helping hand (no, it’s not Spider-Man!).
Financial Predictive Analytics Software aids in forecasting future financial events based on historical data. The software recognizes the patterns and trends in financial data, analyzes them, and generates predictions and forecasts resulting in actionable insights and quicker data-based decision-making. These solutions are used by financial institutions, businesses and banks to forecast market movements and adjust their financial strategies accordingly.
So, let’s learn more about Financial Predictive Analytics Software!
A Quick Look At Financial Predictive Analytics Software
You may have set reminders for recurring financial commitments; for example, your Netflix subscription or health insurance coverage. Imagine if you could get similar reminders for predicted expenses.
Ting! Junior’s football game is next month and you need to buy him a new pair of shoes!
Well, wouldn’t that be incredible?
Similarly, financial institutions and businesses also need to understand and make monetary plans for the future. Financial Predictive Analytics Software helps them understand how they need to pivot and strategize to remain successful. Businesses can use predictive analytics to predict changes in customer behavior and market trends. This helps them make better financial decisions by predicting future sales, expenses, profits, potential risks and opportunities. For instance, managers can improve their sales strategies based on data-backed insights and predictions about the market.
Yet, no one could have predicted how ubiquitous this tool would be a few decades ago!
Evolution Of Financial Predictive Analytics Software
Businesses have used data analytics to gain insights from data for decades now. However, predictive analytics came about later when businesses wanted to understand future demand. No one likes to get caught off guard, right?
Here’s how it happened:
Due to lower prices for hard disks in the late 1980s, businesses began collecting significantly more data. This meant that businesses stored years' worth of financial, market, product and customer data.
Then, in 1989, Howard Dresner at Gartner introduced a Business Intelligence approach to make better decisions by analyzing the data organizations had amassed. The term “business intelligence” referred to strategized decision-making based on data. Large companies started embracing this concept by analyzing customer data and later expanded it to financial records.
Data mining started in the 1990s to find patterns in large data sets. By analyzing massive volumes of data, businesses were able to gain accurate customer and financial insights. This led to companies questioning if the future needs of the customer could be interpreted from past customer behavior.
In 1999, Salesforce successfully demonstrated how cloud computing could be leveraged for faster and more scalable data analytics. With this, businesses started migrating their data to the cloud.
This introduced a new paradigm where businesses had more data available than ever. Organizations started using predictive analytics routinely to improve their competitive edge in the industry. Soon, predictive analytics spread to the financial aspect of the business – and the rest is history!
Today, Financial Predictive Analytics Software is used by most businesses to evaluate their financial health and plan future growth. So, how does it do that?
How Does Financial Predictive Analytics Software Work?
Imagine you purchase two pairs of black jeans. You would probably not buy another pair of jeans, especially a black one, for a few years, right? However, your neighbor Jack hasn’t bought a pair of black jeans in a decade. Predictive software might predict, based on simple data, that you are an ideal target for black jeans compared to Jack as you’ve displayed a fondness for them. Sounds wrong, doesn’t it?
This is why Financial Predictive Analytics Software defines probabilistic outcomes. It does not tell you who will win the next Superbowl, rather it answers the question “What is most likely to happen?”
This allows businesses to develop proactive strategies based on the most likely outcomes. Businesses can then refine their strategies to meet business goals better and reduce risks. The software interprets existing financial data using descriptive and diagnostic analysis to calculate possible future outcomes. To do this, sophisticated Machine Learning models are used to analyze the data, capture trends and patterns as well as find anomalies. The models assess the relationships among various financial variables and generate a precise future state. Using real-time indicators, the software can also anticipate future economic and financial trends, market risks, changes in customer behavior, etc.
This means it can be applied to various business tasks. That’s what we’re covering next.
Applications Of Financial Predictive Analytics Software
Financial Predictive Analytics Software assists businesses in various ways, including:
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Developing Credit Risk Models
Machine learning techniques deployed within Financial Predictive Analytics Software help financial institutions forecast credit risk. This lowers the likelihood that borrowers will default, safeguarding banks, lending companies and businesses.
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Identifies Areas For New Revenue
The tool allows businesses and banks to find new opportunities by forecasting market changes based on business and economic factors. The software helps predict the returns made on potential investments, start-ups and emerging sectors.
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Cash Flow Prediction
A precise cash flow forecast gives businesses the ability to manage their finances effectively, monitor cash flow and cash turnover. It alerts stakeholders when there is a major change in the predicted cash flow, allowing them to strategize in time.
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Fraud Detection
Fraud in the financial sector is no joke! Financial services providers, banks and financial institutions must provide the highest level of security for customers since hackers are constantly coming up with new ways to compromise their systems. Financial Predictive Analytics Software can strengthen security or prevent fraud by identifying fraud attempts before they can cause damage.
You don’t need to be Nostradamus to predict that these applications of Financial Predictive Analytics Software have numerous advantages – read on to know what they are!
Benefits Of Financial Predictive Analytics Software
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Decreased Operational Costs
By integrating Financial Predictive Analytics Software into budget creation, risk modeling and cash flow monitoring, businesses get better insights into daily financial processes and can increase the cost-effectiveness of their financial operations.
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Minimized Financial Risks
Using Financial Predictive Analytics Software can help financial institutions and banks model the future economic scenario and make data-based decisions to minimize the risk.
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Decreased Frauds
With Machine learning and statistical models, organizations can process volumes of financial data to detect fraud in real-time with higher accuracy. The software also uses data on previous frauds to identify fraud requests and attacks.
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Personalization Of Service
The tool analyzes large amounts of customer data, allowing companies to better understand customer profiles and needs. This enables the delivery of personalized financial services and assistance at scale.
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Increased Revenue
Machine learning-powered predictive models allow financial professionals to understand data better and make data-driven decisions. This can lead to more profitable strategies and higher revenue.
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Increased Employee Satisfaction
The automated nature of predictive analytics reduces manual work, allowing employees to focus on more valuable and productive tasks. This increases overall employee satisfaction and productivity.
Impressed, right? Every business can benefit from Financial Predictive Analytics Software to glean insights about the future. Talking about the future…
What’s The Future Of Financial Predictive Analytics Software?
The global Financial Predictive Analytics Software market is expected to grow at a compound annual growth rate (CAGR) of 17.8% from USD 2.02 billion in 2017 to USD 7.72 billion by 2030. The rising demand for big data and predictive analytics solutions is responsible for the market's expansion.
Additionally, there is more interest in the tool due to the growing demand for fraud prevention and risk management solutions in the finance sector. Vendors will concentrate on developing cloud-based Financial Predictive Analytics Software as the adoption of cloud-based deployment increases. These solutions will be available via a SaaS-based subscription model, enabling smaller businesses and start-ups to benefit from the power of financial predictive analytics.
We hope this prediction comes true as soon as possible!
It’s The End
Financial Predictive Analytics Software helps businesses forecast cash flows, income, expenses, etc. accurately and make better plans for investments and expenditures. It also helps mitigate financial risks and develop strategies that can maintain financial viability even in times of financial crisis. Finance is the backbone of your business – give it the support it needs with Financial Predictive Analytics Software!
Frequently Asked Questions
How does Financial Predictive Analytics Software work?
Financial Predictive Analytics Software operates by analyzing historical financial data using sophisticated Machine Learning models to identify patterns and trends. By interpreting this data, the software generates probabilistic outcomes, allowing businesses to develop proactive strategies based on the most likely future scenarios. These strategies can help refine financial decision-making processes, meet business goals, and reduce risks.
How does Financial Predictive Analytics Software work?
Financial Predictive Analytics Software utilizes machine learning models to analyze historical financial data, recognize patterns and trends, and generate probabilistic outcomes. It interprets existing financial data using descriptive and diagnostic analysis to calculate possible future outcomes, enabling businesses to develop proactive strategies based on the most likely scenarios.
What are the applications of Financial Predictive Analytics Software?
Financial Predictive Analytics Software is applied in various areas such as developing credit risk models, identifying new revenue opportunities, predicting cash flow, and detecting fraud in the financial sector. It helps businesses and financial institutions make informed decisions, manage risks effectively, and enhance operational efficiency, ultimately leading to increased revenue and improved customer service.
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