Banks and other financial companies are currently facing various challenges, including changing customer expectations, increasing competition from Fintech companies, and regulatory compliance. While there is no single band-aid solution to all the challenges in the financial industry, one strategy stands out — data analytics.
Data analytics in banking and financial services allows companies to optimize their processes to become more efficient and competitive. With better analytics, banks and financial services companies will be better equipped to succeed.
How Can Companies Use Analytics in Banking and Financial Services?
Businesses in the financial services industry typically have access to incredible amounts of data. Still, issues like data silos and outdated data procedures prevent them from accessing all the valuable opportunities stored within that data. Traditional data analytics in banking and financial services involved creating basic reports and dashboards. More complex analysis is not only possible today, it’s necessary.
Banks and other companies in the industry can use advanced data analysis in several key ways including:
Fraud is an incredible drain on banks and other financial companies, costing them billions each year. The direct financial cost of fraud isn’t the only concern, either. Certain fraud cases can damage a company’s reputation and brand. Data analysis offers a way to detect fraud faster and prevent it from becoming more costly.
Using big data and advanced analysis, financial institutions can seamlessly track and analyze customer behavior to detect unusual activity as soon as it occurs. Machine learning applied to customer behavioral data makes this data analysis even more powerful. With AI in data analysis, financial institutions can better predict when or where fraud will occur to prevent it before it ever happens.
Credit Risk Analysis
Financial institutions are always looking for better ways to manage the risk associated with giving out loans to customers. Data analysis takes all of the educated guesswork out of credit risk assessment. Applying big data analytics to traditional data like total outstanding debt and credit history as well as non-traditional data like mobile data and social media activity will improve financial institutions’ credit risk assessment process. This strategy offers a more complete picture of each potential customer and assesses their creditworthiness. Financial institutions can use it to minimize their risk.
Certain data analysis tools also integrate real-time data. That feature gives the bank or other finance company the most up-to-date, relevant information to use in loan decisions.
Developing New Products
Another application of data analytics in banking and financial services is in the development of new financial products. By analyzing data about how well products sell (or don’t sell) and which customers buy which products, financial institutions are better able to develop successful products going forward. Analysis of external data such as historical market activities when certain economic conditions are present can also play a role in developing new financial products.
5 Ways Data Analytics is Changing the Financial Industry
The applications of data analysis in banking and financial services listed above show that data analysis is already disrupting the financial services industry. More specifically, some of the ways financial institutions benefit from advanced analytics include:
1. Better Understanding of Customers
Understanding your customers is key in any business, and finance is no exception. By aggregating customer data across multiple channels, you can pinpoint who they are, what they care about, and therefore what financial services they really need. This information can help you finetune your marketing efforts so that the right customers are exposed to the right products at the right time, increasing your sales.
2. Enhanced Productivity
Any process in your business, no matter how well-developed, can get quicker and more effective. Data analytics offers a way to streamline your operations and increase your employee’s productivity. With the right data analysis solution, your data will be organized and accessible to all the team members who need it, all in one place. That frees up time that can then be spent analyzing the information, working with customers, and making impactful decisions to push your business forward.
3. Cost Reductions
If you’re currently applying some form of analysis without a strong data analysis solution, one major risk is bad data. Bad data is any data that isn’t complete, accurate, accessible, and usable. It’s more than just inconvenient, too — bad data is costly. Implementing a current, high-quality data solution can bring down these costs or eliminate them entirely. Data analysis also helps financial services firms reduce manual errors and associated costs.
4. Greater Visibility
Outdated data solutions often produce data silos — collections of data that only one group within your organization has access to. They can lead to miscommunication between departments and missed opportunities to get more out of data. Modern data solutions solve this issue by giving financial institutions the ability to look at the big picture of their business from user-friendly dashboards. Everyone in the organization can access the information, leading to better communication and efficiency.
5. Improved Risk Mitigation
Risk mitigation is essential to any financial institution, and data analysis can significantly improve it. Once you identify risks to your business, you can use data analysis to assess how likely it is that a given negative outcome will occur and how it would impact your organization. This method of risk assessment is much more precise than manual risk assessment. Ongoing data analysis of real-time data can also alert you immediately when risk events occur so you can respond quickly and limit the damage.
Data analytics is the best way for financial services companies to tackle the current challenges in the industry and stay ahead of the competition. It’s not enough to simply implement some basic analytics, however. To get the most out of your data, you need powerful data analysis solutions that apply tools like machine learning to provide actionable insights for your business. Live Earth can help. Live Earth’s platform leverages AI technology and real-time data integration to help financial institutions reduce risk exposure while maximizing revenue opportunities. See how the platform works today.