Banking Forward: Analytics Trends in Financial Services
Banking Forward:
Analytics Trends in Financial Services
In the world of financial services, staying ahead of competition means embracing analytics trends that enhance customer and member experiences and operational efficiency. As technology continues to reshape the industry, financial institutions are turning to advanced analytics solutions to gain insights on customer and member behaviors.
Higher Customer and Member Engagement through Online and Mobile Services
Improving the online and mobile experiences is at the forefront of modern banking strategies. Institutions are not only investing in robust mobile banking apps but also leveraging app data to gain deep insights into customer or member behavior. By analyzing transaction patterns, engagement metrics, and user feedback, banks can uncover valuable insights that inform strategic decisions and improve service offerings. This increased access to mobile services significantly enhances the customer and member experience by providing convenient access to financial information anytime, anywhere.
It’s important to note that improved mobile services play a crucial role in shaping personalized experiences, which have become a cornerstone of customer engagement in the banking industry. Through advanced analytics, banks can decipher intricate client data to understand their preferences, goals, and financial behaviors. This allows them to create tailored advice and personalized financial plans on a large scale. Detailed client profiles allow banks to anticipate needs and offer relevant products and services proactively, thereby enhancing customer satisfaction and loyalty.
Highly Personalized Advising
Advising Services, like personalized experiences, is another solution that ensures each client receives tailored assistance aligned with their specific needs. Advising Services have evolved significantly with the integration of customer relationship management (CRM) technology. By using CRM tools, banks can compile comprehensive customer profiles enriched with transaction history, communication preferences, and financial goals. This wealth of data allows financial advisors to deliver customized guidance that addresses each customer’s unique circumstances and aspirations. Such personalized advisory services foster stronger client relationships, driving loyalty and retention in a competitive market.
Enhanced Customer Service through AI-Powered Chatbots
Similarly, AI (Artificial Intelligence) is revolutionizing customer interactions within the banking sector and how they might seek out help. AI-powered chatbots are being deployed to handle routine inquiries and provide instant assistance, reducing wait times and enhancing customer satisfaction. These chatbots are integrated seamlessly into banking platforms, offering users real-time support and guidance. Moreover, AI-driven virtual assistants are being used to deliver personalized money management tips, empowering customers and members with actionable insights to make informed financial decisions.
Open Banking Initiatives
And while AI is implemented to assist clients, open banking ensures that clients retain ultimate control over their data. Open Banking represents a new era of connectivity and collaboration in financial services. By securely sharing customer information through APIs (Application Programming Interfaces), banks can build partnerships with third-party applications and services. This integration allows for enhanced functionalities such as aggregated financial insights, streamlined payment processes, and personalized financial recommendations.
Predicting and Preventing Fraud and Cyberthreats
Finally, with the increase of cyberthreats and ransomware, cybersecurity and fraud detection continue to trend as well. Effectively identifying and mitigating malicious threats calls for strategic planning and investments in tools and infrastructure. Investing in cybersecurity further enhances customer and stakeholder trust by committing to protecting their data and assets.
In conclusion, the banking and credit union sectors are embracing advanced analytics trends to enhance customer experiences, streamline operations, and drive sustainable growth. By leveraging technologies like AI, CRM, and open banking principles, institutions can deliver personalized services that cater to individual needs and preferences effectively. Embracing these trends not only positions banks as industry leaders but also ensures they remain relevant and responsive to evolving customer expectations in a digitally-driven world.
At Aunalytics, we are committed to empowering community banks and credit unions with cutting-edge solutions that leverage these trends. By partnering with us, community banks and credit unions can optimize their operations, strengthen customer and member relationships, and prevent cyberattacks and fraud events that can erode consumer trust. We believe in supporting our clients to ensure that they remain at the forefront of the financial services sector.
Organizations Shift to Cloud-Based Analytics and IT Platforms
The growth rates of cloud-based IT solutions in the areas of analytics and artificial intelligence have been substantial in recent years. The increasing volume of data and the need for faster, more accurate insights have driven organizations to adopt cloud-based analytics solutions at a rapid pace. This has resulted in the growth of cloud-based data warehousing, business intelligence, and big data analytics solutions.
Similarly, the growth of artificial intelligence has been driven by the cloud, as it allows organizations to access powerful AI algorithms and training data without having to invest in expensive hardware. The cloud has also made it possible for organizations to scale AI solutions quickly and easily, leading to an increase in the adoption of cloud-based machine learning and deep learning solutions. These trends are expected to continue as organizations look to leverage the power of AI and analytics to gain a competitive edge in the market.
This growth in cloud-based analytics and AI has been driven by the larger business adoption of cloud IT because of its numerous benefits such as increased flexibility, scalability, and cost savings. Cloud technology allows companies to access their data and applications from anywhere, reducing the need for physical infrastructure and freeing up resources for other areas of the business. This shift towards cloud computing has also improved disaster recovery and business continuity, as data can be stored and accessed remotely. Additionally, with the rise of cloud-based solutions, businesses have been able to access advanced technologies and services without having to invest in expensive hardware and software. This has resulted in increased competitiveness, innovation and better overall business performance.
APIs add efficiency and flexibility to cloud environments
The power behind the most widely adopted cloud platforms are APIs (Application Programming Interfaces), which play a crucial role as they allow different software systems to communicate with each other and access data from the cloud. This has enabled organizations to build custom solutions and integrate disparate systems seamlessly, making the use of cloud technology much more efficient and flexible.
APIs also allow for automation and streamlining of processes, reducing manual errors and freeing up time for more valuable tasks. APIs make it possible to add new functionality and services to existing systems, allowing for continuous improvement and innovation. In essence, APIs provide a bridge between the cloud and an organization’s systems, enabling organizations to harness the full potential of cloud computing and drive digital transformation.
Analytics moves to the cloud
In terms of business outcomes, cloud-based analytics allow businesses to access and process large amounts of data in real-time, regardless of the size or location of their operations. This enables organizations to make informed decisions quickly and respond to changing market conditions with agility. Secondly, these solutions are much more cost-effective, as businesses only pay for what they use and do not have to invest in expensive hardware or IT infrastructure. The cloud provides businesses with access to a wide range of advanced analytics tools and technologies, enabling them to gain insights from their data in new and innovative ways. These solutions are highly secure and reliable when they are managed by experienced cloud service providers who ensure that data is protected and the solution is always available. Overall, they are considered to be a better choice for businesses because of their scalability, flexibility, cost-effectiveness, and secure approach to data analysis.
Likewise, cloud-based AI or AI as a Service (AIaaS) provides organizations with access to deep insights without having to invest in expensive experts or the necessary hardware and software to implement such solutions. This makes it easier for organizations to deploy and scale AI solutions as they only pay for what they use and do not have to invest in maintaining their own infrastructure. Furthermore, these solutions are more flexible and can be customized to meet specific business requirements, enabling organizations to generate valuable insights that help them to differentiate from their competitors. Finally, cloud-based AI makes it possible for organizations to collaborate and share AI models, allowing them to leverage the collective expertise of their partners, customers, and employees to create better solutions. In short, it is a high-value choice for businesses as it provides a more accessible, scalable, affordable, and collaborative approach to artificial intelligence.
Moving to the cloud accelerates digital transformation
Leading research and advisory firm Gartner reported that “Cloud migration is not stopping, IaaS will naturally continue to grow as businesses accelerate IT modernization initiatives to minimize risk and optimize costs. Moving operations to the cloud also reduces capital expenditures by extending cash outlays over a subscription term, a key benefit in an environment where cash may be critical to maintain operations.”
Aunalytics provides a highly redundant and scalable cloud infrastructure that enables midsized businesses to reap the benefits of the cloud at a reasonable cost. The Aunalytics Cloud provides a wide range of solutions—including cloud storage, backup and disaster recovery, application hosting, advanced analytics, and AI. Moving from on-premises computing to a cloud environment is a key step in an organization’s digital transformation.
Investment in Artificial Intelligence is Vital for Banks and Credit Unions
Has your bank or credit union made investments in artificial intelligence yet?
Advances in artificial intelligence (AI), and the promise it holds for the future, have been making news all year. And it’s no wonder that financial institutions are taking notice—a recent survey from the Economist Intelligence Unit found that 77% of bankers believe that unlocking value from AI will be the differentiator between winning and losing banks. Yet, many institutions are falling behind in AI maturity.
Despite its promise, making a large investment in artificial intelligence may seem risky to many midsized financial institutions. Hiring talent, developing a data management and analytics strategy, building a data platform, and creating AI models can be both time- and resource-intensive. Banks and credit unions want to ensure that the efforts spent to get an AI program off the ground will yield a high ROI, especially in times of economic uncertainty. Yet, failure to innovate and make progress toward digital transformation is not always an option in the highly competitive landscape.
Financial institutions find many uses for AI technologies
Thankfully, an investment in artificial intelligence can improve many processes across an institution. AI can optimize both time- and resource-intensive tasks, decrease risk, and increase revenue by improving the customer experience. For instance, by applying AI and machine learning algorithms to transactional data, banks and credit unions can gain insights into customers or members’ habits and preferences. Some use cases include:
- Detecting and preventing fraud
- Identifying loan default risk at the time of application
- Predicting customer churn
- Winning back business by discovering customer payments going to competitors, and subsequently making a more attractive offer
- Predicting the next best product for each customer then targeting them with the right product at the right time
- Calculating customer value scores in order to better allocate resources to target more valuable customers
Don’t get left behind
Large banks are already utilizing artificial intelligence use cases at scale. In a recent letter to shareholders, Jamie Dimon, Chief Executive Officer of JPMorgan Chase wrote, “Artificial intelligence (AI) is an extraordinary and groundbreaking technology. AI and the raw material that feeds it, data, will be critical to our company’s future success—the importance of implementing new technologies simply cannot be overstated.”
Because of this focus, his company has made tremendous investments in AI. They currently have over 300 AI use cases in production, and employ almost 3,000 people in data management, data science, and AI-research-related roles. This underscores how vital these new technologies are to success in the future.
Unfortunately, not every institution has access to talent and technology at the scale of JPMorgan Chase. That’s why Aunaytics has developed a cloud-based data and analytics platform to provide data management, advanced reporting, and predictive AI and machine learning solutions for midsized community banks and credit unions.
Auna, the AI Agent for Financial Institutions, allows institutions to learn more about their customers and members in order to provide a better overall experience—which in turn reduces risk, increases wallet share, and reduces expenses.
The Truth About Artificial Intelligence in Business
Is the existence of Skynet imminent or is that simply a sci-fi trope? In this brief video, Dr. David Cieslak, Chief Data Scientist at Aunalytics, talks about the capabilities of Artificial Intelligence in business, some potential concerns with AI, and where the technology is headed in the future.
While there exists a broad range of applications for AI, in the business world, this technology has the potential to drastically change how we understand our customers and how we use our data to interact with them. Once created and trained with customer data, AI has the ability to quickly provide suggestions and insights that would otherwise be prohibitively difficult or even impossible to observe on your own.
David Cieslak, PhD, is the Chief Data Scientist at Aunalytics since its inception and leads its Innovation Lab in the development and delivery of complex algorithms designed to solve business problems in the manufacturing/supply chain, financial, healthcare, and media sectors. Prior to Aunalytics, Cieslak was on staff at the University of Notre Dame as part of the research faculty where he contributed on high value grants with both the federal government and Fortune 500 companies. He has published numerous articles in highly regarded journals, conferences, and workshops on the topics of Machine Learning, Data Mining, Knowledge Discovery, Artificial Intelligence, and Grid Computing.
A Data Scientist's Thoughts on Artificial Intelligence, Business, and the Future
A Data Scientist's Thoughts on Artificial Intelligence, Business, and the Future
In this interview, David Cieslak, PhD, the Chief Data Scientist at Aunalytics, describes complex analytics concepts such as artificial intelligence, machine learning, and deep learning, and explains how they are useful for businesses today—and will continue to be in the future. David has been with Aunalytics since its inception and leads its Innovation Lab in the development and delivery of complex algorithms designed to solve business problems in the manufacturing/supply chain, financial, healthcare, and media sectors.
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Do you have the tools and talent to set your organization up for analytics success?
Most business leaders would agree: data is a valuable asset. Having up-to-date, accurate data with which to make data-driven decisions currently gives organizations an edge, but eventually, this will become table stakes in most industries, simply to remain competitive. However, an up-front investment in a strong technical foundation and a shift to embrace analytics culture throughout the organization are required to achieve analytics success.
Unfortunately, there are many challenges to overcome when trying to bring siloed and dirty data from multiple sources across your business to a single place to be analyzed, including a lack of time and manpower, and the need for data points that don’t currently exist, to name a few. Using data analytics, it becomes possible to better optimize your business by discovering operational efficiencies, reducing costs, tracking customer trends across your organization, and making strategic decisions based on predictive data models. Is partnering with analytics experts the best choice for mid-sized institutions, or should you hire Full-Time Employees (FTEs) to build and manage your data?
There are multiple ways an analytics platform could be created—we’re going to look at two today.
Build it yourself
The first is choosing to create a custom data platform. While not a bad choice, it could take a FTE years to create your analytics platform—if it’s ever finished. An engineer hired to build a custom platform may leave you high and dry with no one to step in to help. Something like this could cost your business months—or even years—of lost money and productivity, leaving you with nothing to show for your platform building efforts.
Even if your data engineer remains with your business, there are other challenges you may encounter. It can be difficult for a single FTE to stay up to date on the newest technological advances and upgrades. Especially when that person is not only expected to clean and update information on thousands of data records, but also take care of system and software updates, keep up with changing trends in the analytics world, and more. A lack of manpower can also make tasks like finding trends in your data nearly impossible, as data processing may be far behind where your most recent and relevant business analytics can be found.
When it comes to advanced analytics, you would need to find and hire additional employees who are skilled in advanced data analytics, machine learning, and AI techniques, and ideally, familiar with your industry. This can be easier said than done. Data scientists, like many in the technology field, are in high demand, and may be difficult to find and hire in smaller geographical markets.
Work with a partner
A different option is working with a trusted technology partner who brings data analytics expertise straight to you. Partnering with an end-to-end provider often saves your company money while allowing someone else to take care of the nitty gritty that goes into creating reports, graphs, charts, and more. Additionally, you are guaranteed to have access to the team you need to build algorithms and find insights in your data. A partner will consistently provide you with the right tools, talent, and resources, while supporting you the entire way. But how could an Analytics as a Service partner help you find the true value of your data?
A good partner will be able to offer the required resources to achieve analytics success—a foundational data platform, automated data management, access to data experts, and data delivery methods such as relevant and actionable dashboards and reports. Imagine having a regular report, generated overnight, every night, for you to review first thing in the morning—without having to invest in many new FTEs and years of development time.
When looking for a data analytics partner, all the things above are important for creating a successful partnership that leads to analytics success. Aunalytics provides data processing and analytics help and would never expect you to go it alone. When you hire us, you hire data scientists, data engineers, and data analysts, reducing the need for multiple expensive FTEs. By having access to a team of data experts by your side, your business can find itself enabled to make better, faster, and smarter decisions based on consistent, real-time data.
How State and Local Governments Can Use Technology to Overcome Economic Challenges
How State and Local Governments Can Use Technology to Overcome Economic Challenges
At present, state and local governments are confronted with significant challenges stemming from the current state of the economy. This includes a decrease in tax revenues, sustained high inflation, and a shortage of proficient IT personnel, who are vital to their day-to-day operations. Industry experts consider technology as an effective solution to address inadequacies during challenging economic periods.
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Aunalytics is a data platform company. We deliver insights as a service to answer your most important IT and business questions.
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How State and Local Governments Can Use Technology to Overcome Economic Challenges
How State and Local Governments Can Use Technology to Overcome Economic Challenges
At present, state and local governments are confronted with significant challenges stemming from the current state of the economy. This includes a decrease in tax revenues, sustained high inflation, and a shortage of proficient IT personnel, who are vital to their day-to-day operations. Industry experts consider technology as an effective solution to address inadequacies during challenging economic periods.
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Banking Institutions Are Behind in AI Maturity—Catch Up or Others Will Eat Your Lunch
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Financial institutions must embrace the use of data analytics powered by artificial intelligence for operational efficiency, risk reduction, revenue growth, and improved customer experience. Yet, it’s clear that financial companies that fail to pick up the pace, moving ahead to the next phase of AI deployment, are in danger of falling far behind. Luckily, there is a clear-cut solution to reaching AI maturity and achieving sustained, long-term success.
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