Predictive Analytics in Finance: Understanding What 2022 Holds

Shaivi Chapalgaonkar | August 9, 2021

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The financial industry has been going through digital transformation for years. Digital technologies have helped to automate manual and tedious tasks like processing and reporting of historical data to forecasting and financial predictive analytics.

The financial services industry owes its success to data. Data is constantly evolving in the form of market trends, client investment, customer service, campaigns. Data gives a boost to banking strategies. As reported by Accenture in a recent survey, 78 percent of banks have made the shift to using data for operations; however, only seven percent of them have extended to using predictive analytics in finance.

Predictive analytics in finance has had a slow but steady start. It is an area of growing interest for banks and other institutions as new newer technologies launch in the market. To complete your company’s digital transformation, data analytics in finance will make a difference in that process.

To be successful, organizations must have the ability to adapt to changes.

Having predictive analytics on your side, your organization can deal with ever-changing circumstances with less to no difficulty.

Understanding Predictive Analytics: What is it?

Predictive analytics is a process of interpreting data to measure any possible future outcomes. It is carried out with the help of statistical modeling, historical data sets, and machine learning. The collected historical data is fed into an algorithm that recognizes patterns and forecast trends and possible future behavior from days to years in advance.

Analyzing historical data and predicting the future has been an old practice in the finance sector. Banks and financial institutions have been evaluating past events or historical data for a long time now.

Making precise forecasts in trends and analyzing data becomes easier due to predictive analytics.
There is a wider scope to predictive efforts with more speed and accuracy and apply them throughout strategic and tactical business practice areas. 

Predictive Analytics in the Financial Sector: What are the Benefits?

Many organizations are ready to accept the positive applications of predictive analytics but remain skeptical about the return on investment.

It is worth understanding the potential of predictive analytics to any business big or small. It doesn’t matter if you are not in the banking sector to benefit from taking a peek into the future of financial performance.

Any finance and accounting department can take advantage of advanced predictive analytics for the following reasons:

Precise Monitoring

The technology keeps a regular track of the consistency between expectations and reality to warn you about possible gaps.

Risk Alleviating

Analytics accurately helps you identify any possible threats to your business and warns you.

Enhanced User Experience

Predictive analytics guides you to recognize the strengths of your business and lets you know how to maximize customer satisfaction.

Analyzed Decision Making

You can understand your customers better with predictive analytics. With this information, you can correctly match your customers with the product in a better way.

Importance of Predictive Analytics

Most successful banking and financial institutions depend on predictive analytics because it simplifies and integrates data to increase profits for companies. Predictive analytics can improve different finance processes.

But the importance of analytics goes beyond just banking services and actually goes into a better quality of customer service. Better customer service is only possible because of the advanced technology that shares customer feedback and preferences throughout the organization, in turn giving relevant information to every employee to make necessary product enhancements.

To understand the importance of predictive analytics, below are some of its use cases:

Customer first

Predictive analytics in financial institutions and banking give you a complete profile of your customer base. It is impossible to contact every customer and interview them about their likes, needs and wants. This is where big data analytics in finance comes into play. It gives you the whole information about your customers regardless of the services they subscribe.

Customers usually don’t have the same needs throughout their lives. As they grow older and have families, their financial needs change accordingly. For instance, a young person considering getting married will always try and save monetarily to buy a house, life insurance, college funds, whereas an older couple will save that money for their retirement.

Apart from enabling different financial services, predictive analytics empowers you to serve individual customers with ease. Let’s take an example. When a customer applies for a loan, predictive financial services can help you analyze if the customer can repay the loan.

Predictive analytics also helps offer alternative services like secured loans to customers who may not qualify for the originally applied services.

Online Banking Made Better

Consumer interest fluctuates in spikes. Predictive analytics informs managers enough in advance so they can set up online infrastructures in those areas. Predictive analytics has made it easier to identify a possible customer base. For example, it can provide metrics to the marketing teams. In turn, the marketing teams can target the customers with ads for probable mortgage loans or business loans in hopes of converting them into their customers.

Data analytics in finance also helps in preventing and detecting fraud and abuse. Although detecting fraud doesn’t necessarily fall under predictive analytics, it can inform the IT department about potential scammers and which online services must be protected.

Foreseeing Market Variations

Predictive analytics can predict market variations and changes. By combining internal and external data, your organization can predict revenue growth in particular market sectors.

For nascent or growing companies, predicting market changes is an important ability. Profitable companies should also be reviewed through predictive analytics to generate demand projections owing to the uncertainties caused by the Covid-19 pandemic. Your return on investment can grow or reduce even with the minutest changes to the growth plans that would seriously impact investor confidence in the future.

Predictive analytics also help to establish which marketing campaigns are working and which strategies need to change.

Predictive Analytics and the Future: What Next?

Technological improvements have allowed predictive analytics in finance to improve and change constantly. Any organization can use customized data solutions to meet your customers’ needs and reach new ones efficiently. Your organization can use predictive analytics to move your business and products ahead and understand how the market will thrive, giving you the much needed heads up you would need to change your strategies and tactics. 

Frequently Asked Questions

Is predictive analytics is the future of finance?

Predictive analytics is called the ‘future of financial software,’ which means it can provide accurate planning and cost-effectiveness.

How can analytics be used in finance?

Analytics helps in predicting revenue, improve supply chains, identify trouble spots, understand where the company is bleeding money, and fraud detection.

How do predictive analytics benefit financial institutions?

Predictive analytics can help financial institutions and customers detect fraud, financial management, predicting markets, improving products, better user experience, etc.

Spotlight

Benu Networks

Benu Networks is a privately held telecommunications Infrastructure company led by an experienced team of telecommunications veterans headquartered in Billerica, Massachusetts, USA. Benu Networks’ carrier-class Virtual Service Edge (VSE) software platform enables the rapid creation and delivery of next generation IP services over a converged infrastructure. The VSE allows service providers to create different service network slices on the same platform to enable the following services: Managed Business Networking, Managed Home Networking, Carrier Wi-Fi, Managed Security, Managed IoT, SD-WAN, and Network Analytics.

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What are the Benefits of Data Modeling for Businesses?

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Effective Ways to Prevent Data Breaches

Article | November 26, 2021

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Forensic investigations – Major consequences of a data breach include, the business that was attacked will be accountable to perform a forensic investigation to determine the causes of the data breach. These investigations are costly and often yield valuable evidence and insights to prevent future data breaches. Future security costs – Victims of a data breach may have to bear costs of credit monitoring for customers whose data was compromised. This may also include the costs of identity theft repair, card replacement, and additional compliance requirements from the PCI. Reputation Having a good reputation is the most prized asset for any organization. As a business, one must constantly put effort into building and maintaining brand integrity. A single compromising episode like a data breach can trash the best of reputations. According to a PwC report, 85% of customers won't shop at a business if they have concerns about their security policies. Customers value their privacy, and a data breach will be perceived as a lack of regard for their data and privacy. Furthermore, 46% of businesses reported that security breaches harmed their reputation and brand value. Intellectual Property The product blueprints, business strategies, and engineered solutions are some of your most valuable assets for any organization. Your trade secret gives you an added advantage over your competitors. Hence it needs to be protected as some may not hesitate to use breached intellectual property. Other significant consequences of a data breach include; A data breach can pit the CEO against the CISO Poisoned search results on your corporate brand Loss of sales after a data breach Unexpected expenses Less attractive to new employees, especially in tech positions Legal penalties after a data breach Understanding the aftermath of a data breach is an important step to safeguarding your business. The next step is to create an action plan is to protect what you've worked so hard on. How does a Data breach happen? Data breaches sometimes can be traced back to planned attacks. But, on the other hand, it can result from a simple oversight by individuals or flaws in the infrastructure. Accidental Insider For instance, an employee uses a co-worker's computer and reads files without proper approval or permission. However, the access is unintentional/accidental, and no personal information is revealed. The data was breached, however, because it was read by an unauthorised person. Malicious Insider This person deliberately accesses/shares data with the intent of causing harm to an individual or company. The malicious insider may have genuine authorization to use the data, but the intent is to use the info in nefarious ways. Lost or Stolen Devices Any laptop or external hard drive with important information on it that is not encrypted or unlocked goes missing. Malicious Outside Criminals These are hackers who attack several vectors to collect information from a network or an individual. Global cost of data breach According to the Ponemon Institute's Cost of a Data Breach Report, global data breaches cost $3.86 million on average in 2020. The amount in 2020 was somewhat lesser compared to 2019 when it hit $3.92M. The same report found that the average cost of a data breach in 2020 totaled $8.64M. Ways to prevent a data breach Conduct employee security awareness training Control access to data sensibly Update software regularly. Require secure passwords and authentication Simulate phishing attacks Evaluate accounts Limit access to your most valuable data. Review your user account lifecycle processes Insist on complex and unique passwords Protect against authentication bypass Store sensitive personal information securely and protect it during transmission Consider implementing a secure SSO solution Secure all endpoints Segment your network and monitor who's trying to get in and out Manage Vendors - Third-party vendors must comply. Conclusion Protecting against data breaches may appear to be a time-consuming procedure. You will be in a better position if you take an encrusted step to secure your data using various methods, policies, and procedures to ease security threats. FAQ’s How does a data breach impact an organization? Depending upon the company and data type, the consequences may include destruction or corruption of databases, leaking of confidential information, the theft of intellectual property, and regulatory requirements to inform and possibly compensate those affected. What is the most common data breach? Hacking attacks are the most common cause of a data breach. However, it is often a weak or lost password that is the vulnerability that the opportunist hacker is exploiting. { "@context": "https://schema.org", "@type": "FAQPage", "mainEntity": [{ "@type": "Question", "name": "How does a data breach impact an organization?", "acceptedAnswer": { "@type": "Answer", "text": "Depending upon the company & data type, the consequences may include destruction or corruption of databases, leaking of confidential info, the theft of intellectual property, and regulatory requirements to inform and possibly compensate those affected." } },{ "@type": "Question", "name": "What is the most common data breach?", "acceptedAnswer": { "@type": "Answer", "text": "Hacking attacks are the most common cause of a data breach. However, it is often a weak or lost password that is the vulnerability that the opportunist hacker is exploiting." } }] }

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