Automating Data Management Significantly Improves Efficiency for an Oncology Business Intelligence Platform

The Aunalytics Daybreak™ data platform improves the performance of technology solutions by automating data management, ingestion, and cleansing to provide a single source of truth that is updated daily. AC3, an oncology business intelligence company, experienced this efficiency upgrade firsthand.

AC3 logoAC3’s platform automates billing processes and provides revenue cycle insights to oncology providers. The platform unites practice management, healthcare data, and innovative technology intelligence into a single environment that delivers full transparency and automated actionable insights to simplify workflows, increase efficiency, and secure revenue integrity. Realizing that current fee schedule management processes can be cumbersome and continued to involve manual tasks that posed some areas of vulnerability, AC3 determined its solution needed increased automation to close the gap and protect against such vulnerabilities.

Therefore, AC3 decided to look for more efficient ways to take charge of data and better prepare it for reporting and analytics. The company selected the Daybreak platform to aggregate data from siloed systems and lay the foundation for their solution that enables healthcare practice groups to avoid manually building billing systems and avoid costly data errors. Aunalytics provides features that enable analytic solutions like fee schedule generation and the ability to build master records of accurate patient data. The platform cleanses data for accuracy and governance and transforms disparate data into a golden record for a single source of truth ready for analytics and reporting.

To learn more about how Daybreak has enriched the AC3 oncology solution, download the case study here.

Man in data center with laptop

Why Cybersecurity Should Be a Top Priority for Mid-market Businesses

Man in data center with laptopCybersecurity should be a top priority for mid-market organizations. With remote working at its highest, most businesses now hold some form of sensitive data in the cloud and workers access company data from remote locations. Zero trust security principles based upon a user’s credentials instead of a user’s location within a firewalled company facility are the new norm.

At the same time, the number of cybersecurity attacks has increased to its highest levels ever. It has been reported that ransomware attacks increased over 90% in 2021. Ransomware has hit new levels of sophistication, with demands for payment skyrocketing into the tens of millions. McKinsey reports that attacks are motivated by:

  • Vulnerabilities posed by pandemic weary organizations and workers logging in from unsecured home networks
  • Ever advancing connectivity driven by advancing digitization
  • Threat actors are now “dwelling” undetected within victims’ environments (instead of using a smash and grab approach) to better understand where the highest value data and information lives and then selling that to the highest bidder
  • More companies have been forced to pay ransoms to regain control of their networks and data, so hackers are further incentivized to innovate on this lucrative threat

Companies need to ensure they remain resilient by focusing on ransomware prevention, preparation, response, and recovery strategies. This is a journey—threats continue to evolve and staying ready means staying up to date with new threats of increasing sophistication, cyber security strategies, and best practices. Over time, increasing cyber maturity creates a resilient environment where attacks may still occur but do not have the same impact they would otherwise.

Mid-market businesses need expert skills in cloud security and data security, which is not standard in mid-market IT department skillsets. Keeping servers in a closet guarded by your IT department is extremely risky for data protection. With constantly looming cyber threats, organizations should make cybersecurity best practices a top business priority—and Aunalytics is here to help.

Side-by-Side Client Success Model

Side-by-Side Client Success Model Empowers Bank's Analytics Initiative

Customers are increasingly demanding digital banking experiences, immediate results and responses to sales and service inquiries, and easy-to-use online platforms. While it is common for banks to invest in building mobile and online banking platforms, industry trailblazers are harnessing the power of data and analytics to drive revenue and smarten operations by gleaning better understanding of their customers for timely targeted cross selling opportunities, lower risk lending, and by cutting operational costs caused by ineffective duplicative customer outreach for sales and service.

So, where to start? The data analytics landscape has exploded over the past decade with an ever-growing list of products and services: literally thousands of tools exist to help business deploy and manage data lakes, ETL and ELT, machine learning, and business intelligence. With so many tools to piece together, how do business leaders find the best one or ones? How do you figure out the best combination of tools and use them to get business outcomes?

The truth is that many tools are built for data scientists, data engineers and other users with technical expertise. With most tools, if you do not have a data science department, your company is at risk of buying technologies that your team does not have the expertise to use and maintain. This turns digital transformation into a failed project without business outcomes instead of sparking data-driven revenue growth.

Yet most mid-sized financial institutions do not have teams of data scientists or data engineers and it does not make business sense to add these FTEs. Really, mid-market banking is stuck between a rock and a hard place in trying to compete with big banks and not get left in the dust of industry giants taking more market share by using data analytics to sweeten customer experiences. So how does the mid-market compete?

Side-by-Side Client Success Model

Side-by-Side Solution

A side-by-side client success model provides value that goes beyond most tools and platforms on the market by providing a data platform with built in data management and analytics, as well as access to human intelligence in data engineering, machine learning, and business analytics. While many companies offer tools, and many consulting firms can provide guidance in choosing and implementing the tools, integration of all the tools and expertise in one end-to-end solution built for non-technical business users is key for digital transformation success for mid-market businesses.

To learn how Aunalytics helps mid-market banks and credit unions achieve success in data analytics implementation and beyond through their side-by-side client success model, download the full case study here.

Cloud-based data management

Insurance Company Discovers Solution to Data Management Challenges with Aunsight Golden Record

Cloud-based data managementA major global insurance company was creating a new customer-facing portal and needed a data management solution to deliver synchronization of data updates from the portal to its backend insurance policy and analytical systems. Customers would start using the web portal to update information, such as contact information, and the insurance company desired a solution to automatically communicate the data entries and changes to other company systems. The goal was for the most up to date customer data to be available for use in the line of business applications across the company and to ensure that data would remain consistent across ten separate systems for over two million customers cross the globe.

The insurance company initially selected a cloud-native data management solution provided by a company in Silicon Valley. They began a proof of concept project. However, the solution did not perform as planned. Despite being promoted as an out-of-the-box master data management solution, the product required users to write “glue code” to map and connect data sources to the platform. The insurance team soon realized that they would also be responsible for maintaining the glue code and connectors—the solution did not do this. They calculated that they would need to hire at least one more full time employee to do this work.

Further, the platform was built for a technical audience and was not intuitive to use. It required more training than originally thought. And because it was built for a highly technical audience, it limited who from the insurance company team would be skilled enough to use it. The technical skills required to use the platform meant that the burden would be on the IT department to fix data errors reported by business users, and respond to data query requests from the business, in addition to having to build and maintain connectors to data sources and govern and secure the data. This workflow would not be sustainable long-term.

Unsatisfied with the Silicon Valley solution, the global insurance company launched a second proof of concept project to try Aunsight™ Golden Record. Instead of merely integrating the data sources, the Aunsight Golden Record platform cleansed data, eliminated duplicate records, used ELT/ETL and other techniques to normalize data from the different data sources into a single automatically generated schema. To learn how Aunsight Golden Record resolved this company’s data management challenges, download the full insurance use case. 

Financial institutions are frequently targeted in cyberattacks

Financial institutions are frequently targeted in cyberattacks—here’s how to protect your bank or credit union

Financial institutions are frequently targeted in cyberattacks Financial institutions consistently have been the most cyberattacked industry for the past decade. It is no surprise, given that banking enterprises hold large volumes of sensitive data about people, companies, and governments, and their transactional business revolves around massive volumes of money transfer. Hackers will continue to strike with increasing sophistication since the data held by financial institutions is of high value with the potential for extremely lucrative financial gains if stolen. For example, the Europe-based Carbanak and Cobalt malware campaigns targeted more than 100 financial institutions in greater than 40 countries during five years from 2013-2018, and the criminal profits yielded over a billion Euros. 

Attacks are increasingly sophisticated and cyber criminals continue to invest in new and complex criminal strategies and campaigns. Hackers in banking often take advantage of the interdependencies of financial institutions to service products such as credit cards and mortgages for other banks. From one bank breach, the cyber cartels jump to the partnered financial institution to steal its data as well. 

In some types of cyberattacks, criminals make slight changes to data, which may not be immediately detectable. Because nothing is stolen at the time, users may not recognize the attack. However, once the criminals gain access to this data, they can manipulate algorithms in the system for their own financial gain. Timestamp manipulation is a newer strategy, whereby criminals have found that they are more likely to evade detection if they manipulate time for an otherwise valid transaction. Changing timestamps can alter the value of capital and trades. Because the parties to the transaction appear to be legitimate, this type of fraud is harder to detect. 

Other criminals outright steal data for financial gain by selling it, hold data hostage for ransom profit, or pilfer intellectual property such as an organization’s competitive strategy and business plans to sell to interested parties. But the main goal in banking cyber-criminal activity is direct profit from a modern-day bank heist—stealing money from the bank. 

Despite the increasing complexity of cyberattacks against financial institutions, there are some tools and best practices that banks and credit unions can use to protect themselves from these threats: 

  • Continuously update security technology and protocols as threats evolve and adapt with the help of a dedicated full-time security team.
  • Employ 24/7/365 monitoring with remote remediation to quickly stop attacks in their tracks
  • Monitor endpoint devices to stop attacks before they hit networks.
  • Monitor cloud security including application use across the financial institution.
  • Monitor email and Office 365 using tools specially designed to thwart attacks on these platforms, such as proactively recognizing and removing phishing scams.
  • Have a dedicated security team and SOC, or hire an expert outside managed security services firm that embeds tools, technology and 24/7/365 monitoring to serve as your SOC.
  • Push frequent patches so that user devices are equipped with the latest security protections.
  • Adopt deep learning or AI monitoring, mitigation and context investigation that can more quickly identify threats.
  • Encrypt data so that it is not compromised even if a breach occurs.
  • Use multi-factor authentication to protect against unauthorized access.
  • Instruct employees and customers to only access bank data in a secure location over a non-public Internet connection.
  • Train employees on cybersecurity threats quarterly.
  • Develop a solid business recovery plan for when an attack occurs.

Learn more about how Aunalytics Advanced Security helps protect financial institutions, and businesses in other highly regulated industries, from cyberattacks.

Marketing pitfalls: duplicate mailers

Marketing pitfalls can damage customer relationships—here's how to avoid them

While the main goal of marketing is to gain new customers or increase spend from existing customers, at times, marketing effort can do more harm than good. Unfortunately, a marketing campaign could not only fail to entice customers, but certain pitfalls could actively damage customer relationships. Fortunately, there are ways to avoid them. Below are three major mistakes that marketers are prone to making.


#1 Duplicate Mailers

Marketing pitfalls damage customer relations, for example, duplicate mailersThere is nothing more frustrating than opening up the mailbox and receiving multiple duplicate postcard mailers from a single company.  Or when they are addressed to you using two variations or spellings of your name. Or when one is addressed to another member of your household and the second to you. Even worse, when one is addressed to you and another to a generic “household” at your address. Your household typically does not require more than one.

This leaves you to focus on the wasted paper and postage instead of the product or service being marketed. And if the company sending the mailer knew more about the target customer, perhaps the target is someone who does not respond well to snail mail and doesn’t like it. Mailed promotional materials go straight into the recycling bin without even entering houses in many households. This type of waste would be avoided by intel on channel preference of prospects.

When you receive duplicate mailings from a company that you do not do business with currently, it can be viewed as a sign that the customer experience would lack attention to detail, personalization and efficiency. This is a turnoff. That company is likely to be put on a mental list of those you do not want to do business with – period.

If a company that you are doing business with sends multiple duplicative mailers to your home, this can be even worse. In this digital world, many businesses ask customer profile questions including preferred contact method. If you opt in for electronic communications and e-bills, sending a mailer shows that the company is either not listening to its customers or the company is not communicating well within its internal teams. You took the time to complete the profile, yet the business can’t be bothered with using your input. Did anyone read your form fill results? Again, this shows lack of personalized customer experience, inefficiency and lack of cohesiveness in operations. As a current customer, you feel even more devalued than the business that does not have a relationship with you.

Sometimes the duplicate mailings are sent to your name using slight variations of your address, such as “Street” versus “St.” If the business cleaned up its mailing list and recognized that this is the same location, it would save on operational costs and make the company look smarter.


#2 Marketing Products to Customers Who Just Bought Them

A second frustration is receiving a mailer from a company that you currently do business with asking you to purchase products or services that you already have purchased from them. For example, a bank sends a mailer to open a HELOC account or a credit card account when you already have that product from that bank. Is the bank carpet bombing mailings to everyone? How wasteful. Is it that the bank does not care enough about you as a customer to take the time to realize which products you already have with them?

The misdirected marketing may cause customers to begin to think that they should place their business with a bank that cares about their business enough to know which accounts a customer has with them. Really, the relationship would be better if the bank stopped trying to engage its customers than continue to do so with communications that miss the mark.


#3 Bad Timing

A third pet peeve with marketing is when the offers are untimely. For example, if you just refinanced your mortgage with your bank, the bank should not send you a mailer 10 days later for a refinancing opportunity. Yes, customers appreciate notification of interest rates becoming more favorable. But given that you just paid closing costs (or folded them into your loan), refinancing 10 days later is not likely. Instead, you run the risk that the customer sees even better terms being offered and feels dissatisfied with his new product or even mad. From the customer’s perspective, if the bank had told him to wait 10 days, he’d have better terms. Marketing can do better on timing.

Marketing should not damage customer relations.


The Digital Data Challenge

Many businesses have a plethora of data that is typically siloed across many systems throughout the organization. Aggregating and integrating this data for marketing purposes is a major challenge that can be difficult and time-consuming, if not nearly impossible.

Hyper-personalized services that factor in intelligence about a customer holistically should form the core of customer relationships. To achieve this goal, businesses can integrate their disparate data architecture across lines of business and functions to create a 360-degree view of customers and allow for targeted marketing based upon data.

New and advanced data analytics powered by artificial intelligence (AI) are available today that enable customer intelligence to drive marketing. Aggregate your data and ensure that it is cleansed to remove duplicate customer lists for mailings. AI-powered analytics recognizes when people with different names are part of the same household to further eliminate duplicate mailings.

Harness the power of your data to personalize a customer’s experience with your company and not only avoid these pitfalls, but enable smarter targeted marketing.

Aunsight End-to-End Data Platform

Aunsight: An end-to-end solution to the data pipeline problem

Data pipelines are hard to deliver. Issues often arise when piecing together various technology tools for each part of the process. We developed the Aunsight™ Data Platform to solve this problem. Aunsight is an end-to-end data solution that includes cloud-native advanced analytics, computing, and data warehouse storage infrastructure and software. The data accuracy feature provides automated data management including data profiling, auto-mapping, ingestion, integration, and cleansing. It also automates the entire process.

Watch the video below to learn more about how the Aunsight Data Platform, along with the expertise of the Aunalytics team, provides a seamless data pipeline that allows financial institutions to utilize machine learning and AI to discover actionable insights in their data.

Digital Banking and Analytics Initiatives Top Banking Technology Predictions for 2022

Digital Banking & Analytics Initiatives Top Banking Technology Predictions for 2022

Bankers looking over analytics reportsWhen looking at major trends and predictions regarding banking technology for mid-market financial institutions this year, two themes top the list—digital banking and analytics initiatives. Mid-market financial institutions have been placing more emphasis on digital banking and analytics initiatives in recent years as consumer preferences and technologies evolve. But over the past two years, the pace of this shift has accelerated. As we move away from the initial shock to our economy caused by the global pandemic, and continue to feel its ripple effects in the supply chain, the jobs market, and price increases in nearly every sector, 2022 reveals that time is of the essence for new leaders to emerge in mid-market banking with smart technology investments.

Unfortunately, simply providing a mobile banking app is not enough in a world where customers demand personalized digital interactions. A banking institution must augment digital banking technology with customer intelligence and implement data-driven decision making through AI-enabled analytics. This is not a minor undertaking. It may require the bank to make a fundamental shift in the way it operates and the initiatives it prioritizes. Cultivating a data-driven culture is essential in meeting this goal. However, this can be challenging. Many mid-market financial institutions may not yet have the technology and talent needed to facilitate a data-driven culture. It requires data management and advanced analytics technology and expertise. Organizations need to take steps now in order to not only stay relevant—but to truly thrive—in this ever-evolving industry. Staying up-to-date on the latest technological trends is the first step in the process.

To learn more about the top technology trends in mid-market banking, and steps community banks and credit unions can take now in order to bridge the competitive gap, download our eBook, Top 5 Imperative 2022 Banking Technology Predictions for Mid-Market Financial Institutions.

Data analytics are vital to understanding customer banking trends

Data Analytics Helps Midsize Financial Institutions Thrive

Data analytics are vital to understanding customer banking trendsThe financial services industry continues to rapidly evolve. Between mergers, changing customer demographics, and increasing reliance on digital platforms for banking interactions, it can be difficult for smaller institutions to compete with large, national, and online-only banks in this crowded market. As customer interactions become increasingly digital, community and mid-market banks and credit unions are challenged with maintaining the competitive advantage that local, personalized, white-glove service has traditionally afforded them. This is why customer intelligence powered by data analytics helps midsize banks and credit unions thrive. However, they oftentimes struggle to achieve the valuable business insights that untapped data could provide to improve their operations.

It is unlikely that midsize and community banks will “out tech” large banks and fin-techs on their own. However, with the right partners, they have an opportunity to thrive by redefining the local experience and digitally transforming how they operate. Using the right data analytics, they can leverage their local knowledge with personalized customer intelligence to regain competitive advantage.

Customer Intelligence within Reach

Aunalytics’ Daybreak for Financial Services offers the ability to target, discover and offer the right services to the right people, at the right time. Built from the ground up for midsize community banks and credit unions, Daybreak for Financial Services is a cloud-native data platform with advanced analytics that empowers users to focus on critical business outcomes. The solution cleanses data for accuracy, ensures data governance across the organization, and employs AI and machine learning (ML) driven analytics to glean customer intelligence and insights from volumes of transactional data created in the business and updated daily. With daily insights powered by the Aunalytics cloud-native data platform, industry intelligence, and smart features that enable a variety of analytics solutions for fast, easy access to credible data, users can find the answers to such questions as:

  • Which current customers that have a loan but not a deposit account?
  • Who has a mortgage or wealth account with one of my competitors?
  • Which customers with a credit score above 700 are most likely to open a HELOC?
  • Which loans were modified from the previous day?
  • Who are current members with a HELOC that are utilizing less than 25% of their line of credit?

Harnessing their data with Daybreak enables community banks and credit unions to discover patterns, insights, trends, and usage strategies helps to strengthen their position in regional markets and compete with large national banks. With Aunalytics’ customer intelligence data model, they are enabled to deliver timely personalized messages to customers, make data-driven product recommendations, measure campaign ROI, and grow net dollar retention.

Aunsight Golden Record creates a single source of truth for credit union data

Aunsight Golden Record creates a single source of truth for credit union data

Credit unions have a great deal of data spread across various systems. However, it is impossible to create a centralized, accurate and up-to-date record of all of this data manually. Aunsight™ Golden Record automates this process by aggregating, cleansing, and merging data into a single source of truth so credit unions have access to an accurate record of their data in one place.

Watch the video below to learn more about how Aunsight Golden Record, along with the expertise of the Aunalytics team, can help credit unions quickly and painlessly take charge of their data: