The Problem with Relying on Your IT Department for Data Analytics
The Problem with Relying on Your IT Department for Data Analytics
IT departments are primarily concerned with maintaining security and keeping systems operational. IT owns the business function of minimizing internal and external security risks and vulnerabilities, and maintaining core business systems and operations. By asking your IT department to implement data analytics, you are asking them to take focus off of what they are trained to do and dabble into new areas of technology without having the expertise to do so.
Fill out the form below to receive the white paper.
Aunalytics is a data platform company. We deliver insights as a service to answer your most important IT and business questions.
Featured Content
Nothing found.
How to Use AI for Smarter Financial Institution Service
Data has long been used in decision making in the financial services industry. Statistical scoring models based on consumer data like FICO® have been used for half a century to guide lending decisions in the financial services sector. But today’s analytics space has evolved to the point where many other factors not easily digested by credit scoring bureaus play a roll. Imagine a deeper understanding of lending risk factors not commonly reported in credit scores:
- Number of changes of residence in the past five years
- Householding status (single or cohabiting/married)
Imagine having the ability to look at a particular client and understand based on past data how that individual compares in terms of various factors driving that business relationship:
- Which of our financial products is this customer most likely to choose next?
- How likely is this customer to default or become past due on a mortgage?
- What is churn likelihood for this customer?
- What is the probable lifetime value of this customer relationship?
Aunalytics financial services experts understand the most pressing business questions specific for this industry. Working with our financial services experts, Aunalytics’ Innovation Lab data scientists have developed proprietary machine learning, AI and deep learning algorithms based on a solid understanding of the data commonly collected by financial institutions. Our data engineers understand the types of data commonly created and used by the industry, common data sources and have created integrations to bring data from across a bank together into a single analytics-ready feed. The end result is data organized into industry specific relational data marts ready to answer questions posed by business users from financial services institutions.
A SHAP value chart for a remarkably accurate loan default risk model we developed. A benchmark with testing data provided by one client was able to predict 30% of that customer’s loan defaults with 99% accuracy, or predict 75% of all loan defaults with 75% accuracy (i.e. 0.99 precision at 0.3 recall or 0.75 precision at 0.75 recall).
Take the example of a recent model we developed at Aunalytics to predict loan default risk. Looking at a chart of the SHAP (Shapley Additive Explanations) values for this model, we can see a number of common-sense observations confirmed. For example, high interest loans (represented by a pink dot in the Account_InterestRate line) and low FICO scores (represented by a blue dot in the Lend_OriginalFICOScore) positively correlate with default risk. This model discovered some much less intuitive characteristics of high risk loans as well: For some loans, payment frequency (Lend_PaymentFrequency) was actually the single most important factor for predicting loan defaults. Moreover, a well-known but not always properly appreciated factor to default risk is illustrated visually: the type of loan being underwritten (Account_ProductType) is in many cases just as important as a customer’s credit score to default risk. Auto loan applicants with high FICO scores might be more of a default risk than customers with low credit scores shopping for a home mortgage.
In so many cases, machine learning techniques enable more accurate and understandable models of risk, propensity, and customer churn because they represent a more complex model understanding of the various factors that go into risk modeling. Our models deliver greater accuracy than simpler, statistical models because they understand the relationship between multiple indicators.
Through AI and machine learning enriched data points, clients can easily understand a particular customer or product by comparing it to other customers with similar data. Whether you want to know if a customer is likely to select a new product, their default risk, churn likelihood, or any other number of questions, our data scientists and business analysts are experienced and committed to answering these questions based on years of experience with financial services businesses.
What is the best analytics tool for business users?
What is the best data analytics tool for business users? As more business leaders face this question in recent years, most are finding just how hard it is to answer. The data analytics landscape has exploded over the past decade with an ever-growing landscape 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?
As with most things, the best tool set is simply the one that tailors itself best to the problems and questions that need to be solved. For some users, this could be how to integrate and clean data across siloed systems. Others may want to know how to publish analytical datasets of relevant data and metrics to analysts and marketing researchers. Others may have questions about how to derive value from large amounts of data with machine learning.
The Answers Platform
Aunalytics has built its data platform of tools to answer all of these questions. We believe in providing answers to questions with our integrated data analytics platform and leveraging our industry expertise to put these tools to work for you.
Unlike most tools on the market, Aunalytics provides a comprehensive, end-to-end data platform with all the tools your organization needs:
- Data integration, cleaning, and migration in the loud with Aunsight™ Golden Record
- Data transformation, processing, and delivery with Aunsight Data Platform
- Machine Learning and Artificial Intelligence with Aunsight Data Lab
- Delivery and exploration of the data lake with the Daybreak™ Analytical Database
Side-by-Side Service Model
More importantly, Aunalytics’ side-by-side service model provides value that goes beyond most other tools and platforms on the market by providing access to human intelligence in data engineering, machine learning, and business analytics. While many companies offer one or two similar products, and many consulting firms can provide guidance in choosing and implementing tools, Aunalytics integrates all the tools and expertise in one company as your trusted partner in digital transformation.
A Comprehensive Platform
While there are a large number of options to choose from, we at Aunalytics believe our distinctive approach and comprehensive platform tools provide the best solution for all but the largest companies who may wish to create custom analytics solutions in-house. Wherever you are on the data analytics journey, from just beginning to explore the possibilities in your data to global companies with established data science teams, Aunalytics can provide a path through the complicated landscape of tools and infrastructure to grow your company’s data analytics program.
Credit Union Uses Daybreak to Deliver Insights Specific to Its Business
Case Study:Credit Union Uses Daybreak to Deliver Insights
The President of a Michigan credit union wanted to incorporate data analytics for better executive decision-making. As new community banks and credit unions kept moving to his region, he was concerned about the credit union’s ability to compete and distinguish themselves from other local, white glove financial services options. To meet this goal, the president wanted a dashboard to view all member data in one place, but he did not know where to begin.
This case study summarizes how the credit union was able to laser in on what it needed based upon their failed attempts. It needed a solution with a focus on reporting to the end user to deliver insights that would give business outcomes. It needed Daybreak™.
Aunalytics is a data platform company. We deliver insights as a service to answer your most important IT and business questions.
Featured Content
Nothing found.
Provident Bank Case Study
Bank Jumpstarts Journey to Predictive Analytics & AI
Provident Bank, a mid-sized bank with $10 billion in assets, is the oldest community bank in New Jersey with branches across two states. Although they have successfully met their customer’s needs for more than 180 years, they knew that they needed to invest in technologies today that would carry them into the future.
Aunalytics is a data platform company. We deliver insights as a service to answer your most important IT and business questions.
Featured Content
Nothing found.
Insurance Company Lacks Customer-Centric View of Data
Insurance Company Lacks Customer-Centric View of Data
Aunalytics is a data platform company. We deliver insights as a service to answer your most important IT and business questions.
Featured Content
Nothing found.
Aunalytics Introduces Next-Generation Daybreak for Financial Services
Empowering Users with Advanced Analytics and Valuable Business Insights to Accelerate Competitive Advantage
South Bend, IN (March 23, 2021) – Aunalytics, a leading data platform company delivering Insights-as-a-Service for enterprise businesses, today introduced its next generation of DaybreakTM for Financial Services designed for mid-sized banks and credit unions. The enhanced solution empowers community financial institutions with advanced analytics and valuable business insights to improve customer relationships, strategically deliver new products and services through data-driven campaigns and drive competitive advantage with Aunalytics’ side-by-side digital transformation model.
As with many businesses, financial institutions have a plethora of data that is typically siloed across many systems throughout the organization. Aggregating and integrating this data is a major challenge that can be difficult and time-consuming, if not nearly impossible, such as with transactional data. According to leading analysts, 70 percent of big data and analytics deployments will fail to meet cost savings and revenue generation objectives due to skill and integration challenges.
“We have data; every bank has data—tons of it. What we didn’t have was a way to integrate all this data into something useful,” said John Kamin executive vice president and chief information officer, Provident Bank. “We embarked on a journey that would not only allow us to turn data into information but enable us to look forward with predictive analytics and AI capabilities. Aunalytics helped us jumpstart that vision.”
Built from the ground up for mid-sized 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 artificial intelligence (AI) and machine learning (ML) driven analytics to glean customer intelligence and insights in focus from relevant business information. 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:
- Who are my current customers that have a loan and not a deposit account?
- Who are my most profitable members?
- Who are my customers at risk for churn?
- Which loans were modified from the previous day?
- Who are my current members with a HELOC that are utilizing less than 25% of their line of credit?
“As customer interactions become increasingly digital, community banks and credit unions are losing the competitive advantage that local, personalized, white-glove service has traditionally afforded them and, at the same time, they lack valuable business insights that untapped data could provide to improve their operations,” said Katie Horvath, VP of Marketing and Communications, Aunalytics. “Daybreak for Financial Services offers an opportunity to turn that around and regain advantage with the ability to target, discover and offer the right services to the right people, at the right time.”
New features in Daybreak for Financial Services include:
- Golden Record Assurance:
- Daybreak cleanses data for accuracy and governance and transforms disparate data forms and formats into a common language for building data models. Data fields and records are matched and merged into a golden record for a single source of truth, ready for analytics.
- The industry-intelligent data mart is designed specifically for banks and credit unions, allowing them to automatically find customer data across the organization such as lending, mobile banking, ATM, CRM, wealth and trust. Extracting company data from all business units that is accurate and streamed in real-time, enables better decision making. Aggregated data reveals a 360-degree view of customer behaviors and insights for data-driven campaigns and greater customer and product targeting capabilities.
- Smart Features™ :
- Aunalytics data scientists create high value data fields derived from a company’s internal data and added to data models capable of answering industry and functional questions. Business users have access to actionable data, enriched with Smart Features, to answer impactful questions for the first time. For example, if a banking customer has improved a credit score and is now in the “excellent” range, the bank can take action and let the customer know that if interested in a home equity loan, s/he qualifies for low interest rates.
- In addition, Daybreak offers a significant advantage with automated data enrichment and pre-built connectors to most major core systems such as CRMs, loan and mortgage systems, and other heavily utilized financial industry applications. Mid-sized banks and credit unions now have access to external data, allowing them to understand more about their customers’ relationships with other companies and identify products and services that customers might be interested in. This presents opportunities that may have otherwise been missed – learning that a customer has outside investment and mortgage accounts might prompt outreach to the customer to make a switch.
- Natural Language Answers™ and Insights:
- Daybreak is built for the non-technical business user to query data using NLP searching, and visually display golden records of data, analytics results, and insights. Users do not need to know SQL, computer coding, database technical knowledge or IT expertise to find answers to their most important business and IT questions.
- Insights allows users to better understand the information in their data by creating visualizations of their query results. Visualizations can be easily configured and viewed as intuitive graphics, not through complex database filtered lists of endless fields, so users can answer important business questions about customers.
Tweet this: .@Aunalytics Introduces Next-Generation Daybreak for Financial Services, Empowering Users with Advanced Analytics and Valuable Business Insights to Accelerate Competitive Advantage
#Dataplatform #Dataanalytics #Dataintegration #Dataaccuracy #ArtificialIntelligence #AI #Masterdatamanagement #MDM #DataScientist #MachineLearning #ML
About Aunalytics
Aunalytics is a data platform company delivering answers for your business. Aunalytics provides Insights-as-a-Service to answer enterprise and midsized companies’ most important IT and business questions. The Aunalytics® cloud-native data platform is built for universal data access, advanced analytics and AI while unifying disparate data silos into a single golden record of accurate, actionable business information. Its DaybreakTM industry intelligent data mart combined with the power of the Aunalytics data platform provides industry-specific data models with built-in queries and AI to ensure access to timely, accurate data and answers to critical business and IT questions. Through its side-by-side digital transformation model, Aunalytics provides on-demand scalable access to technology, data science, and AI experts to seamlessly transform customers’ businesses. To learn more contact us at +1 855-799-DATA or visit Aunalytics at https://www.aunalytics.com or on Twitter and LinkedIn.
PR Contact:
Sabrina Sanchez
The Ventana Group for Aunalytics
(925) 785-3014
sabrina@theventanagroup.com
Aunalytics Acquires Naveego to Expand Capabilities of its End-to-End Cloud-Native Data Platform to Enable True Digital Transformation for Customers
Naveego Data Accuracy Platform Provides Comprehensive Data Integration, Data Quality, Data Accuracy and Data Governance for Enterprises to Capitalize on Data Assets for Competitive Advantage
South Bend, IN (February 22, 2021) - Aunalytics, a leading data platform company, delivering Insights-as-a-Service for enterprise businesses today announced the acquisition of Naveego, an emerging leader of cloud-native data integration solutions. The acquisition combines the Naveego® Complete Data Accuracy Platform with Aunalytics’ AunsightTM Data Platform to enable the development of powerful analytic databases and machine learning algorithms for customers.
Data continues to explode at an alarming rate and is continuously changing due to the myriad of data sources in the form of artificial intelligence (AI), machine learning (ML), the Internet of Things (IoT), mobile devices and other sources outside of traditional data centers. Too often, organizations ignore the exorbitant costs and compliance risks associated with maintaining bad data. According to a Harvard study, 47 percent of newly created records have some sort of quality issue. Other reports indicate that up to 90 percent of a data analyst’s time is wasted on finding and wrangling data before it can be explored and used for analysis purposes.
Aunalytics’ Aunsight Data Platform addresses this data accuracy dilemma with the introduction of Naveego into its portfolio of analytics, AI and ML capabilities. The Naveego data accuracy offering provides an end-to-end cloud-native platform that delivers seamless data integration, data quality, data accuracy, Golden-Record-as-a-ServiceTM and data governance to make real-time business decisions for customers across financial services, healthcare, insurance and manufacturing industries.
Aunalytics will continue to innovate advanced analytics, machine learning and AI solutions including the company’s newest DaybreakTM offering for financial services. Unlike other “one-size-fits-all” technology solutions, Daybreak was designed exclusively for banks and credit unions with industry specific financial industry intelligence and AI built into the platform. Daybreak seamlessly converts rich, transactional data for end-users into actionable, intelligent data insights to answer customers most important business and IT questions.
“I’m extremely excited to be leading this next chapter of innovation and growth for Aunalytics and to provide our customers with a new era of advanced analytics software and technology service coupled with Naveego’s data accuracy platform,” said Tracy Graham, CEO, Aunalytics. “Now enterprises have the assurance of data they can trust along with actionable analytics to make the most accurate decisions for their businesses to increase customer satisfaction and shareholder value.”
Tweet this: .@Aunalytics Acquires Naveego to Expand Capabilities of its End-to-End Cloud-Native Data Platform to Enable True Digital Transformation for Customers #DataPlatform #DataAnalytics #DataIntegration #DataAccuracy #ArtificialIntelligence #AI #MasterDataManagement #MDM #DataScientist #MachineLearning #ML
About Aunalytics
Aunalytics is a data platform company delivering answers for your business. Aunalytics provides Insights-as-a-Service to answer enterprise and midsized companies’ most important IT and business questions. The Aunalytics® cloud-native data platform is built for universal data access, advanced analytics and AI while unifying disparate data silos into a single golden record of accurate, actionable business information. Its DaybreakTM industry intelligent data mart combined with the power of the Aunalytics data platform provides industry-specific data models with built-in queries and AI to ensure access to timely, accurate data and answers to critical business and IT questions. Through its side-by-side digital transformation model, Aunalytics provides on-demand scalable access to technology, data science, and AI experts to seamlessly transform customers businesses. To learn more contact us at 1-855-799-DATA or visit Aunalytics at http://www.aunalytics.com or on Twitter and LinkedIn.
PR Contact:
Sabrina Sanchez
The Ventana Group for Aunalytics
(925) 785-3014
sabrina@theventanagroup.com
Daybreak: A Foundation for Advanced Analytics, Machine Learning, and AI
Financial institutions have no shortage of data, and most know that advanced analytics, machine learning, and artificial intelligence (AI) are key technologies that must be utilized in order to stay relevant in the increasingly competitive banking landscape. Analytics is a key component of any digital transformation initiative, with the end goal of providing a superior customer experience. This digital transformation, however, is more than simply digitizing legacy systems and accommodating online/mobile banking. In order to effectively achieve digital transformation, you must be in a position to capitalize one of your greatest competitive assets—your data.
However, getting to successful data analytics and insights comes with its own unique challenges and requirements. An initial challenge concerns building the appropriate technical foundation. Actionable BI and advanced analytics require a modern specialized data infrastructure capable of storing and processing a large magnitude of transactional data in fractions of a second. Furthermore, many financial institutions struggle not only with technical execution, but also lack personnel skillsets required to manage an end-to-end analytics pipeline—from infrastructure to automated insights delivery.
In this article, we examine some of the most impactful applications of advanced analytics, machine learning, and AI for banks and credit unions, and explain how Daybreak for Financial Services solves many of these challenges by providing the ideal foundation for all of your immediate and future analytics initiatives.
Machine Learning and Artificial Intelligence in the Financial Industry
Data analysis provides a wide range of applications that can ultimately increase revenue, decrease expenses, increase efficiency, and improve the customer experience. Here are just a few examples of how data can be utilized within the financial services industry:
- Inform decision-making through business intelligence and self-service analytics:
While banks and credit unions collect a wide variety of data, traditionally, it has not always been easy to access or query this data, which makes uncovering the desired answers and insights difficult and time-consuming. With the proper analytics foundation, employees across the organization can begin to answer questions that directly influence both day-to-day and long-term decision-making.
For example, a data-informed employee could make a determination on where to open a new branch based on where most transactions are taking place currently, or filter customers by home address. They could also determine how to staff a branch appropriately by looking at the times of day that typically have the most customer activity, and trends related to that activity type.
- Improve collection and recovery rates on loans:
By implementing pattern recognition, risk and collection departments can identify and efficiently target the most at-risk loans. Loan departments could also proactively reach out to holders of at-risk loans to discuss refinancing options that would improve the borrower’s ability to pay and decrease the risk of default.
- Improve efficiency and effectiveness of marketing campaigns:
Banks and credit unions can create data-driven marketing program to offer personalized services, next-best products and improve customer onboarding, by knowing which customers to reach out to at the right time. Data-driven marketing allows financial institutions to be more efficient with their marketing dollars and track campaign outcomes better.
- Increased fraud detection abilities
Unfortunately, fraud has become quite common in the financial services industry, and banks and credit unions are investing in new technologies to fight it. Artificial intelligence can be used to detect triggers that indicate fraud in transactional data. This gives institutions the ability to proactively alert customers of suspected fraudulent activities on their accounts to prevent further loss.
These applications of machine learning and AI simply scratch the surface of what outcomes can be achieved by utilizing data, but they are not always easy to implement. Before a financial institution can embark on any advanced analytics project, they must first establish the appropriate foundational analytics infrastructure.
Daybreak is a Foundational Element for Analytics
There are many applications for analytics within the financial services industry, but the ability to utilize machine learning, AI, or even basic business intelligence is limited by data availability and infrastructure. One of biggest challenges to the achievement of advanced analytics initiatives is collecting and aggregating data across multiple disparate sources, including core data. In order to make truly proactive decisions based on data, these sources need to be updated regularly, which is a challenge unto itself.
Additionally, this data needs to be aggregated on an infrastructure built for analytics. For example, a banking core system is built to record large amounts of transactions and is designed to be a system of record. But it is not the optimal type of database structure for analytics.
To solve these challenges, Aunalytics has developed Daybreak, an industry-intelligent data mart built specifically for banks and credit unions to access and take action on the right data at the right time. Daybreak includes all the infrastructure components necessary for analytics, providing financial institutions with an up-to-date, aggregated view of their data that is ready for analysis. It offers users easy-to-use, intuitive analysis tools for people of all experience levels—industry-specific pre-built queries, the Data Explorer guided query tool, or the more advanced SQL Builder. Daybreak also provides easy access to up-to-date, accurate data for more advanced analytics through other modeling and data science tools.
Once this infrastructure is in place, providing the latest, analytics-ready data, the organization’s focus can shift to implementing a variety of analytics solutions, such as advanced KPIs, predictive analytics, targeted marketing, and fraud detection.
Daybreak Uses AI to Enhance Data for Analysis
In addition to providing the foundational infrastructure for analytics, Daybreak also utilizes AI to ensure the data itself is both accurate and ready for analysis. Banks and credit unions collect large amounts of data, both structured and unstructured. Unfortunately, unstructured data is difficult to integrate and analyze. Daybreak uses industry intelligence and AI to convert this unstructured data into a structured tabular format, familiar to analysts. To ensure accuracy, Daybreak utilizes AI to perform quality checks to detect anomalies as data is added or updated.
This industry intelligence also allows Daybreak to create Smart Features from existing data points. Smart Features are completely new data points that are engineered to answer actionable questions relevant to the financial services industry.
Banks and credit unions are fortunate to have a vast amount of data at their disposal, but for many institutions, that data is not always easily accessible for impactful decision-making. That is why it is necessary to build out a strong data foundation in order to take advantage of both basic business intelligence and more advanced machine learning and AI initiatives. Daybreak by Aunalytics provides the ideal, industry intelligent foundation for financial institutions to jump start their journeys toward digital transformation, with the tools they need in order to utilize data to grow their organizations.
Aunalytics’ Client Success Team Drives Measurable Business Value
Transitioning to a more data-driven organization can be a long, complicated journey. A complete digital transformation is more than simply adopting new technologies (though that is an important component.) It requires change at all levels of the business in order to pivot to a more data-enabled, customer-focused mindset. Aunalytics Client Success is committed to helping organizations digitally transform by guiding and assisting them along every step of the journey, and ultimately, allowing them to thrive.
Below, the Client Success (CS) team has answered some of the most common questions about what they do and how they help organizations achieve measurable business outcomes.
What is Client Success?
Aunalytics CS partners with clients to become their trusted advisor, by building a customized CS Partnership Plan utilizing the client’s unique business needs as the core goals. The CS Partnership Plan creates an exceptional client experience by consistently applying a combination of our team and technology to deliver measurable value and business outcomes for our clients.
What are the main goals of the Aunalytics Client Success team?
The Client Success team has four main goals:
- Designing targeted client experiences (by industry, product, and digital transformation stage)
- Recommending targeted next steps by simplifying and synthesizing complex information
- Delivering proactive and strategic support from onboarding to solution launch, ongoing support, and consulting
- Collecting and responding to client feedback on ways our service delivery can evolve
What are the various roles within the CS team?
There are two main roles within the CS team that interact with clients on a regular basis. The first is the Client Success Manager (CSM). The CSM manages day-to-day client tactical needs, providing updates and direction throughout the onboarding process. As the liaison between clients and the Aunalytics team, the CSM synthesizes complex information into clear actions, mitigates any roadblocks that may occur, and clearly communicates project milestones. The CSM works closely with the clients throughout their partnership with Aunalytics, from onboarding, adoption, support, and engagement.
The Client Success Advisor (CSA) works on high-level strategy with each client, translating Aunalytics’ technology solutions into measurable business outcomes. They partner with the clients’ key stakeholders to understand their strategic objectives and create a custom technology roadmap that identifies the specific steps necessary to reach their digital transformation goals. These goals are integrated into the client’s specific CS Partnership Plan to ensure we are aligned on objectives and key results, with clear owners, timelines, and expected outcomes.
How often can a client expect to hear from a CS team member throughout their engagement with Aunalytics?
The CS team is introduced to clients at the initial kickoff meeting and CSMs initiate weekly touch points to ensure onboarding milestones are being met and to communicate action items, responsible parties, and next steps. During these calls the CS team (CS Manager, CS Advisor, Data Engineer, & Business Analyst) will review the project tracker—highlighting recent accomplishments, key priorities, and next steps. Each item is documented, assigned an owner, a timeline, and clear expectations around completion criteria.
What is the Aunalytics “Side-by-Side Support” model and how does the CS team help facilitate this?
Our side-by-side service delivery model provides a dedicated account team, comprised of technology (Data Engineers (DE), Data Scientists (DS), and Business Analysts) and data experts (Product Managers, Data Ingestion Engineers, and Cloud Infrastructure Team), to help transform the way our clients work. The account team collaborates across the company, in service of the client, to ensure that everyone on the team is driving towards the client’s desired outcomes. The CSA captures this information in the CS Partnership Plan to ensure alignment, key priorities, and ownership of time-bound tasks.
The CS team partners with Aunalytics’ Product, Ingestion, and Cloud teams to share client questions, recommendations, and future enhancement ideas. The Partnership Plan is a custom document that evolves with the client’s ever-changing needs. The CSA reviews the Partnership Plan with the client every quarter to capture new goals, document accomplishments, and create feasible timelines for implementation. The goal of the CSA is to create a relationship with the client, in which they view the CSA as a key member of their internal team (e.g. the same side of the table vs. a vendor).
A successful partnership with Aunalytics’ Client Success team is when concrete business outcomes and value are realized by the client, through the use of Aunalytics’ solutions (products + service).
What are some examples of business outcomes that CS has helped Daybreak for Financial Services clients achieve?
In addition to guidance throughout the initial implementation of Daybreak, CS has assisted banks and credit unions with the execution of a number of actionable business cases, such as:
- Assisting Financial Institutions with implementation of self-service analytics programs;
- Improving collection and recovery rates on loans;
- Implementing pattern recognition to make sure that risk and collection departments are efficiently targeting the most at-risk loans;
- Creating data driven marketing programs to offer personalized services, next-best products, and onboarding. Data-driven marketing allows financial institutions to be more efficient with their marketing dollars and track campaign outcomes better;
- Integration with 3rdparty software systems.
The Aunalytics Client Success team is instrumental in helping clients realize measurable business value. Together with Aunalytics’ strong technology stack, this side-by-side delivery model ensures that all clients are equipped with the resources they need to affect positive change within the organization and achieve their digital transformation goals.
