Why Banks Need to Use a No-Code ML Decision Engine Across The Customer Lifecycle
- Collections, Industry News, Product and technology
As the digital banking landscape becomes increasingly crowded and customers demand more personalization and convenience, banks and financial institutions need to embrace new technologies that can help them deliver a better experience at every touchpoint throughout the customer lifecycle.
That’s where ML decision engines come in. These technologies use machine learning algorithms and artificial intelligence to help organizations make faster, smarter decisions across the entire customer journey, allowing them to quickly adapt to changes in customer behavior.
And in today’s digital world, this is a key asset in the financial industry. Customers expect their financial institutions to know them, anticipate their needs, and offer them the right products at the right time.
Companies that use this technology will be able to win over customers who want more personalized services, better experiences, and more control over how they manage their money.
The problem is, implementing an ML decision engine can be time-consuming and expensive for those organizations that lack the resources and technical expertise needed to do it on their own.
The solution? Using a no-code ML decision engine. These systems allow companies to use machine learning to win customers and improve their operational efficiency in just a few clicks.
In this article, we’ll explain how banks and other financial institutions can use no-code ML decision engines across the customer lifecycle to optimize their processes and provide a seamless experience that’s personalized, intuitive, and always available.
How are ML Decision Engines used in the banking industry?
Stronger customer acquisition
ML decision engines help banks and financial organizations collect and analyze data about potential customers, so they can better target them with the right messaging and offers – which leads to more effective acquisition rates and stronger customer loyalty.
Higher customer lifetime value
ML decision engines are able to identify patterns in customer behavior through deep learning and then use those patterns to predict future customer actions – allowing companies to provide services that meet their needs in real time to increase the customer lifetime value (CLV).
Lower operating costs
As the banking industry continues to evolve, there is a great deal of pressure on banks and financial institutions to cut costs. One way they are doing this is by using ML Decision Engines in their operations. These engines automate processes (e.g: approve loans) and eliminate the need for human intervention, which means that they can reduce operating costs.
Lower credit risk
ML decision engines can analyze data from thousands of consumers and predict which borrowers are likely to default on their loans. This allows organizations to make more informed decisions about who they lend money to, resulting in fewer defaults and less damage to their bottom line.
What’s a No-Code ML Decision Engine?
A no-code ML decision engine is a machine learning platform that allows non-technical users to build and deploy custom machine learning models without writing code.
Instead, you use pre-built visual tools (e.g: drag-and-drop functionality) to manipulate the data and the parameters of the model.
These tools drastically cut down on implementation time and training costs for financial companies looking for a more efficient way to utilize machine learning techniques in their workflow.
In the banking industry, it can be used for a wide variety of applications, including business and financial forecasting, customer segmentation and targeting, risk analysis, and more.
In addition to these benefits, other advantages of no-code ML decision engines include:
Advantages of No-Code ML Decision Engines
Easy to implement and deploy across multiple teams
Today’s no-code platforms open up new possibilities that were previously limited to developers or subject matter experts with extensive STEM knowledge, allowing anyone in the organization to build their own custom algorithms.
Users can create and deploy algorithms without ever writing lines of code – a simple drag and drop interface lets them create rules and parameters that can be applied to any data set.
Top-notch usability
A no-code ML decision engine can help banks and other financial institutions build a workflow or customer journey that’s easy to understand and easy to manage.
It can work with any kind of data, and because it’s built to handle all kinds of scenarios, your users can tackle complex problems with ease.
High flexibility
A no-code machine learning engine also makes it easier for financial organizations to tweak their model in order to get more accurate results. The intuitive interface allows them to optimize and adjust various parameters without having to spend too much time on configuration.
Besides, with this type of ML technology, you are not limited by any pre-defined rules and algorithms, which means that you can make your model adaptable to new data and changing situations.
Fast model creation
A no-code engine allows banks and other financial companies to create a model in minutes, not months, and then they can iterate on it quickly as well.
You don’t have to wait for developers or data scientists to build your decision engine, so you can get it out there and start collecting valuable data faster.
Easier scalability
This is in contrast with traditional coding solutions, where the programming effort involved means that it takes longer to add new rules and conditions to your program. Adding more data or changing the way your ML decision engine reacts to certain situations also requires significant effort.
With a no-code solution, however, you can scale your model extremely quickly and easily – simply drag and drop new rules into place, or configure your existing rules for new functionality. You can even add new data sources in a matter of minutes.
How can Mindigital help?
There are plenty of no-code ML tools out there, but not all of them are the right fit. That’s why it’s important to find a digital banking partner with solid and intuitive web dashboards that non-technical users can use to set up their models, as well as a full suite of automation and analytics tools to streamline your operations.
It should also include other features like:
- A drag-and-drop interface that lets you connect, configure and deploy decision models quickly and easily.
- The ability to access, transform, store and manage data from any cloud or on-premises data source using built-in connectors, without writing code.
- An enterprise-grade security layer with layers of authentication and encryption, so your models run securely in the cloud. You may also need support for advanced security features such as multi factor authentication (MFA).
That’s exactly what we offer at Mindigital Group through our Smart Flow package.
Mindigital Smart Flow
What’s in For Customers?
Full personalized relationship management:
Banks and other financial institutions using Mindigital’s SmartFlow can automate the process of delivering personalized offers and messaging based on customer data, as they move through different stages of the customer lifecycle.
Tying personalized recommendations to every interaction with an organization creates an entirely new experience for customers, providing them with an easy way to get exactly what they want when they want it.
Faster credit decisions:
With our SmartFlow solution, financial companies can easily build an ML decision engine that interprets customer data in real time to make credit decisions more quickly and accurately than any human ever could.
In today’s fast-moving digital landscape where customers expect instant experiences, this is key to enhancing customer satisfaction.
Omni-channel engagement:
Customers demand a multi-channel approach in order to engage with financial organizations. They want to interact on their terms and at the moment of their choosing.
Mindigital integrates the exact channels your customers prefer, such as web push, SMS, email, native in-app notifications, banners, pop-ups, and icons among others.
What’s in For Financial Companies?
Smart customer segmentation:
Mindigital’s SmartFlow solution includes a Customer Data Platform (CDP) that gains real-time behavioral data from your ML decision engine and creates hyper-segmented tags that you can use to personalize your interactions with customers across the entire customer lifecycle – from marketing to onboarding and servicing, to collections.
Drag-and-drop custom solution:
Banks and other financial companies can use SmartFlow’s online canvas to build their custom no-code ML decision engines in just a few minutes. With our intuitive drag-and-drop platform, you can automatically create a flow of smart rules and enable rapid configuration based on your specific KPIs.
These can be applied across all channels or targeted at specific audiences.
Real-Time Analytics:
Our platform also gives you real-time visibility into all of your customer data in one dashboard, allowing you to make informed decisions quickly and seamlessly across multiple channels. This data can include things like customer account activity, transaction history, past interactions, etc.
This feature is an essential part of our customer lifecycle engagement platform and offers excellent opportunities for customer retention and conversions.
Powerful automation and AI-powered optimization:
Mindigital’s patented AI technology learns from real-world customer data and continuously improves its performance in real time. At the same time, financial companies can build no-code ML decision engines that are fully automated to streamline their customer lifecycles and operational workflows.
The Future of Digital Banking
By using an advanced digital banking solution such as Mindigital’s Smart Flow, banks can build ML decision engines in a breeze, achieving more with less effort across their customer lifecycle.
This solution creates a better experience for both financial companies and customers:
- Organizations are able to automate their processes, streamline their operations, access all relevant data in one place, and make faster and smarter decisions to provide a personalized service to consumers, driving growth and conversions.
- Customers will have a seamless, fast, and tailored experience as they have access to all their financial details wherever they go, on any device.
Speak to one of our sales representatives today to learn more about how our powerful no-code platform can help you rapidly build and implement a full-blown ML decision engine at a low cost while still maintaining control of your customer experience and data.
Mindigital ©2022. All Rights Reserved.