What are Smart Features?
Machine learning is a leading component of today’s business landscape, but even many forward-looking business leaders in the mid-market have difficulty developing a strategy to leverage these cutting edge techniques for their business. At Aunalytics, our mission is to improve the lives and businesses of others through technology, and we believe that what many organizations need to succeed in today’s climate is access to machine learning technology to enhance the ability to make data driven-decisions from complex data sources.
Imagine having the ability to look at a particular customer and understand based on past data how that individual compares in terms of various factors driving that business relationship:
- Which of our products is this customer most likely to choose next?
- How likely is this customer to default or become past due on an invoice?
- What is churn likelihood for this customer?
- What is the probable lifetime value of this customer relationship?
Aunalytics’ Innovation Lab data scientists have combed through data from our clients in industries like financial services, healthcare, retail, and manufacturing and have developed proprietary machine learning techniques based on a solid understanding of the data commonly collected by businesses in these sectors.
A SHAP (Shapley Additive Explanations) value chart for a remarkably accurate loan default risk model we developed shows which features have the highest impact on risk prediction.
From this, we append insights gleaned from machine learning to data models. We add high value fields to customer records to reveal insights about a customer learned from our algorithms. Smart Features provide answers to pressing business questions to recommend next steps to take with a particular customer to deepen relationships, provide targeted land and expand sales strategies, provide targeted marketing campaigns for better customer experiences, and yield business outcomes.
Machine learning techniques enable more accurate models of risk, propensity, and customer churn because they represent a more complex model 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.
Smart Features are one way that Aunalytics provides value to our clients by lending our extensive data science expertise to client-specific questions. Through these 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 businesses in your industry.
Where Can I Find an End-to-End Data Analytics Solution?
The data analytics landscape has exploded over the past decade with an ever-growing selection 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 piece them together 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 for buying technologies that your team does not have the expertise to use and maintain. This turns digital transformation into a cost center instead of sparking data driven revenue growth.
Image credit: Firstmark
https://venturebeat.com/2020/10/21/the-2020-data-and-ai-landscape/
Aunalytics’ side-by-side service model provides value that goes beyond most other 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 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 end-to-end solution built for non-technical business users. The success of a digital transformation project should not be hitting implementation milestones. The success of a digital transformation project should be measured in business outcomes.
How to Assess True Branch Profitability in Mid-Market Banking
How to Assess True Branch Profitability in Mid-Market Banking
Branch profitability calculations are critically important for branch planning. Traditionally, the branch where a customer opens an account receives credit for that customer’s business. But it’s not always that simple. Learn how analyzing the right data can lead to more accurate results.
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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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Mid-Market Bank Achieves Targeted Marketing Success
Mid-Market Bank Achieves Targeted Marketing Success
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 now harnessing the power of data and analytics to drive revenue and smarten operations.
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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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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.
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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.
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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.
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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.
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