Transforming Financial Services and Utilities with Predictive Analytics

Honor Donnie  |  January 6, 2022   |  Credit & Lending  |  Data & Technology  |  Energy & Sustainability  |  ID Verification  

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As technology continues to get more innovative and advanced, companies have become more inclined to integrate these solutions and resources into their processes –– this includes predictive analytics. Predictive analytics uses data to identify the probability of future outcomes based on patterns. From the growing demand for business transparency to the concern of digital security, predictive analytics are proving to be instrumental to the future of business continuity, forecasting, and understanding trends. 

When paired with machine learning or artificial intelligence, predictive analytics can help businesses make more informed decisions using reliable and historical data. ​​In the utilities and financial services sector, predictive analytics will be crucial in shaping the future by improving business intelligence, operational efficiency, and decision-making. Here’s how. 

Predictive analytics in banking and financial services

In the financial sector, predictive analytics play a critical part in measuring credit risk, mitigating fraud, enhancing operational efficiency, and improving the overall customer experience. Between the digital transformation and the rise of fintechs, data is increasingly becoming key to navigating financial services. Using predictive analytics like alternative data, financial institutions can gain a more holistic view of a borrower’s credit risk profile and go a step beyond traditional credit data. This allows greater accessibility to credit for consumers who may be considered “invisible” or “unscorable”. 

By integrating analytics into the credit and lending process, financial institutions can also establish baseline criteria to better understand changes in a borrower’s payment behavior to detect financial distress. Additionally, as more processes become digital, the risk for fraudulent activity increases. With predictive analytics banks and credit unions can improve their fraud detection methods to ensure applicants are who they say and to mitigate account takeover risk. Overall, expanding credit access and minimizing fraud risk help to improve the customer experience thanks to reliable and streamlined processes.

Predictive analytics in utilities

In the last couple of years, the energy market has embraced predictive analytics heavily. With the rise of more sustainable practices, smart technology has taken off in residential and commercial properties as both businesses and residents strive to better understand and measure their utility usage. The data collected by IoT solutions provide historical data and help establish a baseline for greater transparency into energy usage and equipment performance. 

Implementing the use of predictive analytics will streamline the collection of data into tangible insights.

These predictive analytics, in conjunction with machine learning and artificial intelligence, can help companies and residents cut back on utility usage. Utility companies are also embracing the digital transformation and incorporating more technology into their processes. By harnessing time-stamped operational data, they can adapt energy production to meet fluctuating demand needs, predict and avoid potential outages, and improve the customer experience by providing critical insight into customers’ utility usage.

Implementing the use of predictive analytics will simplify the collection and translation of data into tangible insights. Additionally, this data supports personalized solutions for customer usage leading to better retention. Now more than ever, companies must be prepared to adapt to the changes that are following the global digitization era. From the growing effects of climate change on business operations to the rise in electric car production–energy consumption is affecting all aspects of day-to-day. New predictive analysis in your business operations will provide resiliency, transparency, and an improvement in customer experience.

 

It’s Time to Modernize Energy Data >>

 

When predictive analytics and utility data meet

Predictive analytics is a powerful tool alone, but when combined with utility data, the possibilities are endless. In the financial services industry, leveraging the two can open new doors to more customers. This could lead to greater operational efficiency, mitigate fraud risk, and give greater insight into a borrower’s utility payment history, providing proof of occupancy, and address verification. 

In the utility sector, proper utility data collection and management can support energy management programs, ESG goals, and equipment maintenance. Collecting data over time provides valuable insight into how equipment is performing, facility management, and where adjustments can be made to reduce usage. Leveraging Urjanet’s reliable and direct access to utility data gives companies insights to support energy and sustainability processes, identity verification, and credit scoring. By combining utility data with predictive analytics, you can enhance business processes and optimize efficiency. Ready to harness your data? Speak to an expert today to start your predictive analytics process.

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About Honor Donnie

Honor Donnie is a Marketing Intern at Urjanet, with a passion for content creation. When she’s not at Urjanet, she can be found studying Political Science at Clark Atlanta University.