Integrating data from all the apps and systems your business uses is critical for increasing your productivity. According to McKinsey, companies that heavily rely on data and make informed decisions are:

• increase profits by 93%;
• boost sales by 82%; and
• improve the speed of sales growth by 112%.

If you are struggling with your disjointed digital system and looking for ways to improve connectivity and achieve seamless integration, you’ll find it in this article.

Definition of Data Integration

Data integration is a process of uniting multiple data sources, making it accessible and actionable from a single interface. Seamless data integration ensures quick access to any data stored in any of your digital assets and consider it comprehensively. Additionally, integrated systems allow for more automation and are able to exchange data between apps automatically, if the proper algorithms exist are involved.

A business may need to integrate data when one department generates data valuable for another department.

The approaches and strategies to data integration vary but there are traits all the data integration strategies share the parts like master server, data source network, and trained users who operate with the data.

To give you an example, typically:

• a user sends a data request to the master server;
• the server collects the required data from both internal and external sources;
• and after extraction, data is unified in a cohesive form and presented to the user.

Data integration is about data unification from different sources to be used for analysis and stored in a comprehensive way. Data integration allows businesses to get rid of time-consuming processes of data collection, copying, and reformatting. In an integrated system, these actions are performed automatically.

Benefits of Seamless Data Integration for Business Processes

Improved Operational Efficiency

With seamless integration, businesses can automate manual tasks, eliminate effort duplication, and achieve better workflow efficiency. Eventually, it leads to lower operational costs and better productivity.

Enhanced Data Security

A centralized data management system is also a more secure environment that protects an organization from data fraud and mitigates the risk of data loss.

Increased Agility and Flexibility

An integrated IT system is easier to adjust when changing market conditions or policies. A single data endpoint will allow to add, delete, or change applications and data from a single management console.

Better Customer Experience

Seamless data integration creates more opportunities for personalized customer experience, improving satisfaction and retention rates.

Cost Reduction

As the integrated business system with unified data reduces manual tasks and a huge part of data management routines, it becomes cheaper for a business to handle its data.

At the same time, improved business processes save resources for other tasks and reduce the necessity of additional hardware and software for data management.

The Most Effective Data Integration Strategies

There are different ways to integrate your system and its data. In this section, we will review five of them. Each approach to data integration suits different business scenarios for the businesses of various sizes, different goals, and the data integration budget.

Manual

A manual data integration strategy involves analysts that take responsibility for the process. The process relies on just o few data sources and requires minimal support on the part of your team. Thus, the manual approach won’t be a burden on your budget.

However, the human-dependent data systems will be hard to scale in the long run. The more datasets you connect — the more employees you’ll need to manage them. Additionally, the human factor can result in mistakes.

A manual data integration approach is a great quick fix before you develop your long-term data integration strategy.

Middleware

This is a type of software that basically acts as an interpreter between legacy systems and modern ones; it connects those applications, so they can exchange information. This approach improves the speed of data streaming, allowing systems to easily connect with each other. On the other side, the middleware needs supervision from technical specialists all the time and it can only work with the particular types of systems. If your integration goal is only to connect legacy with new systems, this is a good choice; however, it is only a communication tool and you will struggle in the data analytics area.

Application-based

If you pick this option, the software will handle everything, including finding, extracting, cleaning, and integrating information from various separate sources. The information that was separated before and had different formats will have an opportunity to be transferred from one point to the other. Analysts and managers can focus on something else because an automated application will take on everything, providing a seamless transfer of the data. Unfortunately, you still need to have a qualified expert monitor the actions of the program from time to time.

Also, there is a problem with standardization — each service provider offers its own way to do it. But the biggest challenge of this approach is the actual creation of the application that will work in cohesion with every department across the entire organization — the time and effort of many technically proficient experts is required. It could fit big enterprises that have resources to do it right as well as a long-term strategy for integration.

Uniform access

This approach allows access to information from different locations and sets in one unified view, while the data stays in its initial place. Without the need to have multiple places to store information, storage requirements will stay low and you will be able to connect a number of systems. However, it has some risks in the data integrity area because a large number of sources will be used. The amount of the information could be quite large, so not all data hosts will be able to handle it without upgrades. If you have a company that requires unified access to separate systems and you have a powerful enough data host, it will be perfect for your case; you can get everything you need without major modernization processes.

Common storage

This is similar to the previous method — but common storage means not just providing a unified view, but also copying all information to the data warehouse. Being far more versatile, this approach is considered one of the most widespread ways of integration. The host system is not that loaded with information anymore; thus, you will have an option to manage data versions. Also, analysts and managers could work with stored copy to run complex operations without putting data integrity at risk. But on the other side, there are some disadvantages to it — like the additional costs of storing the information and hiring the right technical experts to perform this integration as well as maintain it. Undoubtedly, this is the most sophisticated and expensive approach of the five; however, it could enable experts to work with the most complex queries, providing you the best insights possible.

How to Choose the Right Strategy for Your Business

Choosing the right data integration approach is just one element of turning your business into a truly data-driven company. It’s not just selecting the right software or a single solution; a data integration strategy is part of your big puzzle — it’s a vision of innovation and growth. Answering these questions will help you better understand the direction of your strategy:

• You need to see clearly what you are planning after successfully completing a data integration project. What is the bigger picture?
• Can you see your company using the latest technology or would you like to settle for legacy systems? If choosing the first option, you should consider paying closer attention to cloud platforms and infrastructure — as they can provide maximum flexibility.
• What are your tangible expectations out of the integration strategy? There are multiple benefits of data integration explained in this article, but can you see how it will work for you and your industry?
• What experts and technical resources do you have in your company? Do you have an opportunity to collaborate with a dedicated team on developing a custom solution?

Integrate Data from all Part of Your Business System with ProcessMIX

ProcessMIX is a consolidated platform with a low-code engine, automated CI/CD, embedded testing tool, and release control. The platform holds all the aspects of app creation, deployment, management, and support in one place.

ProcessMIX includes a broad set of functionality and customisable components for building complex back-end services, creating and executing business rules, and decision-making. It also offers an AI-powered assistant to further accelerate engineering, allows bootstrapping any project in minutes, and provides one-click integrations and rapid API creation.

However, it’s better to use the platform once than to read about it. Try the ProcessMIX Demo for free to evaluate its functionalities for your project. Before starting to use the platform, get familiar with our how-to guide and book a call with our support team to discuss your project requirements and estimations. We can help you choose the right tech stack, integrations, and

Data integration strategies for seamless business processes was originally published in ProcessMIX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Technologies evolve at an ever-increasing pace. Implementing and utilising the new tech can introduce gains in capabilities and productivity, and potentially determine one’s place among the competition, but it takes a certain level of maturity of the IT organisation to do it. According to a BCG study, digital leaders achieve earnings growth that is 1.8 times higher than “digital laggards”, and more than double the growth in total enterprise value — so staying on top of your digital game can be extremely rewarding. But why doesn’t every company manage to do it?

A complete system overhaul can be a complex, expensive, and long-term project — and requires having a top-notch team to execute it. Not every business is prepared to commit resources to such initiatives, especially if their IT team’s capacity is limited and incentives misaligned with Business. In fact, even some market leaders fall short in their digital transformation efforts. Another BCGroup study showed that around 70% of businesses fail to achieve their software modernization goals. In most of the cases, it came down to the following:

• The lack of relevant or niche expertise;
• Inability to develop and implement an effective digital strategy;
• Limiting legacy tech stack;
• Ineffective monitoring of the transformation processes;
• Lack of organisational agility during the process.

The good news is that you can leverage certain technologies to increase your chances of successful modernisation of your legacy systems. One of them is to use a low-code platform to reduce the skill barrier for users. In this article, we will review what you need to succeed in your digital transformation and how powerful low-code platforms can assist you.

What is a legacy system?

The legacy system is a set of software that is based on outdated architecture but still comprises the core of your daily business processes. Legacy systems are not necessarily ancient. Today we can apply this term to systems that are simply no longer compatible with the state-of-art tech and no longer provide the necessary competitive advantage as compared to what’s available on the market.

Negative aspects of continuing to use legacy systems

When not timely modernised or upgraded legacy systems can negatively affect your digital business processes in both scale and scope. Here are some of the major implications of using a legacy business system:

Slow development

Legacy systems often lead to a rising IT backlog. As technologies evolve it becomes harder to integrate new apps with a system that uses old frameworks and architecture. In order to develop and use new apps, you must carefully design them to be reverse compatible with the rest of the system, keeping numerous dependencies in mind.

Diminishing pool of talent

Software development is not a learn-once-use-forever endeavour. Skilled programmers keep pace with modern practices and development approaches while the junior ones simply start with those. So there’s a progressively smaller pool of specialists available that you can recruit to maintain and develop your legacy system — creating a major recruitment bottleneck and exacerbating the dependency issue further.

High cost of maintenance

According to the U.S. Government Accountability Office, companies spend 70–80% of their IT budgets on fixing problems with their legacy systems and related operations. In the meantime, they lose the opportunity to invest this money into new talent acquisition and innovation — things that add value to the business.

How to know when it is time to modernise your legacy system?

Here is a checklist that will help you to decide if your business needs a revamp:

• The systems of your competitors outperform your software;
• The system’s scalability is limited and doesn’t align with the company’s current business objectives;
• It’s becoming increasingly difficult to find and recruit developers with the skill set required to maintain and extend your system;
• The IT backlog is growing regardless of the expanded development team and efforts;
• You experience increasingly longer development time for the new features;
• Your team spends more time keeping the lights on rather than innovating;
• Your infrastructure costs are rising disproportionately.

If several or all of the points reflect the current state of your business, it is high time to begin your digital transformation.

Replace, rebuild, or re-architect: which approach to select when deciding to modernise your legacy software?

When it comes to legacy software modernization, there are three ways that you can take — replacement, rebuilding, and re-architecting. Let’s review their pros and cons in detail:

Legacy system replacement

The first path that involves little to no development efforts is legacy system replacement with a COTS (Customizable off-the-shelf solution) software. Choosing this path, you just substitute your previous vendor for another one.

Pros of legacy system replacement:

• You don’t need to design and develop the new system by yourself. The fastest replacement process compared to other modernization strategies;
• The security of the system is on the provider’s side. The provider takes responsibility for your data safety and the performance of the system.

Cons of legacy system replacement:

• Commercial software doesn’t address the particular business needs of a company or an industry. It just presents you with a set of one-size-fits-all features. If some customization is possible with COTS software, it is very narrow.
• You’ll need to adjust your business to the off-the-shelf solution provider to modernise a legacy system. You may need to change your design and process flow to be able to replace your legacy system with COTS.

Re-architecting legacy systems

Re-architecting a legacy system means recreating a part of your legacy system so that it can be integrated with the disruptive technologies you need to implement. In other words, you leave what works well and re-architect those apps and solutions that pull your business back.

Re-architecting will be a good fit for your business if there’s no acute need to rebuild the core of the app and you don’t have sufficient time and budget for it.

Pros of rearchitecting legacy systems:

• You upgrade your system without downtime;
• The major processes, dependency mapping, and skills to operate the system remain the same (i.e. no need to retrain your employees);
• Reduces risks of choosing the wrong tech for legacy system replacement.

Cons of re-architecting legacy systems:

• The core of the system will be out of use one day. Therefore, by choosing to re-architect you’re just postponing what needs to be done eventually.

Rebuilding legacy systems from scratch

The third and most radical way is to build a modern business system instead of a legacy one. This way will involve a higher budget and more time to be implemented properly and delivered but is fully customised for your business needs. However, the time and investment you will need to rebuild your system will depend on the development approach.

Pros of rebuilding a legacy system:

• You can create a future-proof solution tailored to your particular business needs;
• You control the source code of the system which is crucial for your company’s confidentiality;
• Your own system will enable you to use more services and technologies you need.

Cons of rebuilding a legacy system:

• Rebuilding the system may require more time and money, and often depends on having a certain level of organisational maturity in the IT department, including skilled and specialised engineers in-house. You’ll also need to develop and implement the parts of the new system in phases.

How low-code platforms can help you with modernising your legacy software

Low code is a rapid software development approach that enables developers to create applications with minimal hand-coding, using visual interfaces and pre-built components. It ensures quality standardisation, reduces the human error factor, simplifies knowledge transfer and significantly accelerates development. Low-code platforms allow businesses to utilise pre-built elements for rapidly engineering conventional system features and customising other parts.

Replacement and rebuilding

Rebuilding or replacing legacy systems has been effective but costly for modernisation initiatives. However, with the help of low-code tools like ProcessMIX, the process has become dramatically easier and more affordable, allowing you to drive complex digitalisation programs with a skeleton crew without dependency on highly specialised talent. Businesses can now rebuild and replace tools at least three times faster, reducing the barriers to modernisation.

For example, a government agency used low-code tools to modernise its legacy core system. The old system was no longer meeting modern security standards and couldn’t keep up with continuously changing legislation. Using a low-code platform they were able to replace the legacy system in just 6 months. The brand-new system proved to be more secure, robust, efficient, and reliable.

Extension

In the past, businesses turned to refactoring or re-architecting legacy tools to add new functionality, considering it a cost-effective approach. Re-architecture could be required to enable better data structure, robust APIs, high load performance, and availability of the core system. But simple single-function applications can be built quickly and connected to existing databases or deployed as extensions to the legacy platforms, quickly enhancing existing functionality and workflows.

Hybrid approach

The hybrid approach involves combining multiple modernisation strategies to achieve desired outcomes. For example, rehosting certain elements of the legacy apps to improve security and then utilising strategies like legacy application re-platforming to enhance functionality. A common example is migrating legacy datasets to a modern, secure host and simultaneously rebuilding or replacing other elements of the legacy application to effectively manage and utilise this data.

Try ProcessMIX platform for modernising your legacy systems

ProcessMIX is a low-code platform purpose-built for complex back-end development. Initially, the tool was originally engineered for the banking industry — with an emphasis on high standards for security, reliability, and performance, making it highly suitable for any modernisation projects. ProcessMIX includes a broad set of functionality and customisable components for building complex back-end services, creating and executing business rules, and decision-making. It also offers an AI-powered assistant to further accelerate engineering, allows bootstrapping any project in minutes, and provides one-click integrations and rapid API creation.

You can try out the platform with a free ProcessMIX demo. It will allow you to evaluate the platform’s capabilities and see if it fits your digitalisation needs. If you have any questions on how to enable your engineering team with ProcessMIX, please contact our team or read our comprehensive User Guide.

Is your legacy IT system holding the business back? was originally published in ProcessMIX on Medium, where people are continuing the conversation by highlighting and responding to this story.

The success of any business depends on its relationships with customers. That goes doubly for banks who not only need to inspire trust and deliver the best service to their clients but also need to compete against neo-bank competitors.

Thanks to the technological advancement of past decades, banks can process and get more information about their customers’ needs and expectations, empowering them to make decisions and deliver better service.

At the same time, creating effective banking digital systems and applications is often a long and costly process, with technological upgrades for banking systems, client-side applications, and more convenient digital services taking anything from months to years.

But times have changed and software development made it an evolutionary step towards more agile low-code solutions. The low-code approach opened wider possibilities for creating effective solutions for banks and their clients. This approach allows us to implement new tools faster and build apps that produce more personalized experiences for customers. In this article, you will learn more about the capabilities of low-code platforms for banking service personalization and how these solutions work.

What are low-code platforms?

A low-code platform is a software tool for fast software development of any complexity. In contrast to no-code platforms, low-code allows users to code manually for custom features and integrations.

Low code follows the robust software development approach. Such platforms allow users to build software several times faster than with traditional development methods. Low-code facilitates the development process with pre-made components and includes an array of productivity tools for custom development.

The intuitive low-code platforms’ interfaces open the software development for citizen developers. With a short platform-specific introduction, any domain worker can start building and managing an app using the low-code approach. At the same time, custom development on low-code platforms requires professionals to step in. The level of low-code developers’ expertise can be lower due to the wide arrangement of tools that enhance the process.

How low-code platforms work?

Let’s find out what exact features make the low-code approach an effective and reliable way of creating banking solutions for personalization.

Visual development flow

Low-code platforms have visual development interfaces where users can drag and drop components and make them work together with graphic connectors. The components for certain types of applications are ready-made so the users only need the right set and to set the parameters. Visual development in low-code platforms is pretty much like a code constructor that is intuitive and easy to work with.

Developer productivity tools

When it comes to custom development, low-code platforms assist professional developers in many ways. First, they have convenient IDEs (Integrated Development Environments) that improve the development team’s collaboration with project managers. The IDEs allow developers to merge code consistently and employ a reversible app creation history. Then, low-code platforms usually include AI assistants that can guide developers during the process and suggest the code parts.

Embedded testing and debugging tools

Low-code platforms have testing and debugging tools that facilitate QA processes. The platforms are able to check both visual and custom parts of solutions you build on them to find any errors. As soon as a problem arises, the low-code platform can alert users of it and link the part where it has occurred. In fact, the low-code platforms won’t approve software for deployment if there is any problem in the visual development flow.

Seamless Integration

Low-code banking applications can be integrated with social media, web portals, and a banking client base to provide better personalization. The low-code apps get connected to the 3rd parties through different types of APIs depending on the source. The banking app integration process takes a few minutes.

Quick deployment

Cloud-based low-code platforms allow for the deployment of applications instantly in the cloud environments. This means you don’t need to spend weeks on pre-deployment preparations and start getting value from banking personalization technologies right away.

Banking customer engagement model

Banks employ various technologies to ensure seamless interactions with customers. Among the software and tools they use to connect with clients are:

• Mobile applications and web portals. The face of a bank in a digital world. Customers can create their profiles, activate bank accounts, and get lending services via these applications.
• AI-powered chatbots. An integral part of banking mobile and applications. Smart digital helpers that answer the FAQ and redirect clients to corresponding specialists, if needed.
• Omni-channel support. Apart from chatbots on a website or mobile application, banks connect with their customers on social media, via phone calls, and e-mail. Establishing integrated support infrastructure requires thorough channels’ integration and systems.

The role low-code platforms play in banking service personalization

Low-code platforms are about speed, flexibility, ease of use, and security. These traits make them a perfect fit for customer service tool creation. Here are the features low-code provides to enhance banking service personalization.

AI-powered apps

Low-code platforms are embedded with AI that can facilitate customer service and data analytics. AI-enabled low-code platforms for customer service personalization allow banks to build chatbots, get insights into customer preferences, and improve client account security.

Effective customer support

Low-code customer portals allow users to find the answers to their questions effectively. Instead of waiting in a long phone line or looking on the Internet, they can find any data they require by searching on a low-code info portal. Also, banking service personalization low-code platforms can provide tools for personalized suggestions and advice for banking mobile/web app users.

Enabled customer agents

Low-code platforms for customer management tools development allow domain experts to orchestrate digital processes themselves. Increased digital competence of the bank’s employees is reached by the pre-made components and an intuitive interface. Such low-code platforms also increase the maintenance speed and reduce IT support in the customer service department.

Improved KYC (Know Your Customer)

AI-powered analytics along with social media integrations of low-code platforms provide more detailed data on each customer. With low-code tools for baking client profiling, users can score the prospects, define the most demanded services, and advertise to the target audience.

Fast way to comply with regulations

With low-code platforms, bankers can create solutions for clients faster according to the new regulations. In addition, the ready-made low-code banking systems are easy to adjust for the changing service regulations.

Flexible applications

Using low-code platforms banks are able to brand their applications, forms, and tools. Also, it comes in handy when a bank needs to adjust the functionalities of the applications in response to customer feedback.

ProcessMIX for customer service tools development

If you are looking for a low-code platform capable of producing any banking service personalization solution, consider ProcessMIX. Get a free ProcessMIX Demo version and make a step toward your customers.

ProcessMIX is a low-code platform for back-end development that was created with banking software development needs in mind. ProcessMIX has pre-made components to build a vast array of software for banking service personalizations including chatbots, rule-based automation tools, client scoring algorithms, AI-powered data analytics tools, and many others.

With ProcessMIX, you can build applications of any complexity in days and integrate them with your existing banking infrastructure in minutes. The platform facilitates personalization solution development on all levels making both visual and custom creation easier. Explore more on ProcessMIX functionalities in our user guide.

The role of low-code platforms in creating personalized banking experiences was originally published in ProcessMIX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Loan decision-making is an extremely complex task — there are so many points to consider before making the final decision! Fortunately, the latest advancements in Big Data management, process automation, and analytics create the perfect ground for effective credit decisions, doing the hard work for you.

Such tools speed up the loan processing time and drive precise outcomes for both lenders and borrowers. In contrast, legacy loan decision-making practices fail to provide such a level of efficiency and rarely please borrowers.

But which technologies make use of digital data and automation to bring the future of credit decision-making? You’ll find out right here

Benefits of modern credit decision-making software

Higher revenue

Software for loan decision-making increases a bank’s capacity to grant loans. Due to the faster and easier application processing and calculations, bankers can serve a wider range of customers. Automated decision-making allows for an increase in profits with on-point credit conditions and service availability.

Efficient lending service

Credit processing systems eliminate manual tasks and improve the overall banking software connectivity. Banks need to comply with a huge amount of service regulations and laws that require meticulous attention. It is difficult for employees to keep all these rules in mind, which sometimes causes costly mistakes. Loan processing software automates compliance routines and allows for employers to avoid problems occuring with regulators as a result of simple errors.

In addition, digitized and integrated loan decision-making apps are able to send loan data to other parts of the banking system. It facilitates cross-department communication and streamlines internal operations.

Decreased credit-loss rates

The precision of loan decision-making software reduces risks related to credit granting. Automated credit decision-making solutions allow us to make informed borrower scoring, improve KYC (Know Your Customer) processes, and present optimal credit conditions. With the right credit conditions, bankers can be assured of credit repayment success.

Convenient customer service

Credit decision-making software speeds up credit time-to-decision, so the customers don’t need to wait for loan approval for weeks. Also, the system allows the customer to get the loan when they want and where they want. It means that they can submit an application online, get a notification of the decision, and get the money on their card without ever visiting the bank. Additionally, credit decision-making systems help banks to develop optimal credit margins and repayment time for the customer.

How automated credit decision-making works?

Credit decision automation software now works in several stages. Each stage involves a particular set of software that allows digitizing loan granting services.

Credit decision-making starts with receiving the application. Today, banks get applications from their web customers’ portals or mobile banking applications. Then, the decision-making system analyzes the application conditions against the bank’s rules and allocates it to a corresponding department within the bank. The allocation rules depend on the type of borrower (individual, enterprise-level customer, etc.) and the purposes of the loan.

When the application gets to the right credit basket, the decision-making system evokes customer data from internal and external sources for analysis. At this stage, the system checks the borrowers’ credit history, demographics, and other relevant metrics scripted in the credit decisioning software. On the basis of this information, the system scores the customer and notifies a department employee of the borrower’s eligibility for a loan. The deep analysis of the data is usually performed by AI/ML technologies that derive the necessary information from large chunks of data.

If the requested loan conditions for a customer are risk-free for a bank, the employee approves the credit. The approval sets off, allowing the system to send an approval letter to the customer. When the terms are accepted, the system initiates the transaction by the bank to the account of a borrower. If the decision-making system spots risky conditions, it can either deny the loan application or offer another set of loan conditions. The decision-making is supported by other technologies like AI/ML and RPA.

Credit decision automation solutions of the future

What technologies comprise a modern credit decision-making system?

Modern loan decision-making technologies work in combination to make banks’ credit strategy work. They work in all the loan decision-making stages, facilitating application submission, processing, and approval. Here are the core technologies that support the decision-making processes.

Business rules management systems

Business rules management system or BRMS is the software that drives the credit decision process. The bankers develop the rules according to their credit strategy and integrate them with the bank’s database, client-side applications, etc. The system organizes separate rules in decision trees and automates their execution. BRMS ingests the necessary data from databases and external sources and checks the borrower’s data against these rules. After the whole rule-tree execution, the BRMS gives out the final decision and notifies the employees.

Scoring engines

Scoring engines are an inseparable part of business rules management systems. It uses a set of rules to evaluate the borrower and define the borrower’s eligibility for certain credit conditions. The borrower scoring relies on the customer’s credit history, demographics, and other metrics. For instance, a borrower gets a high score if he or she has an impeccable repayment history, a decent level of income, and property that can grant the security of the loan. With the scoring engines in place, bank employees get rid of paperwork and hours of customer analytics.

Artificial Intelligence and Machine Learning

AI enhances the processes in BRMS and scoring systems. The technology performs data analysis, and calculation, and facilitates credit model execution across the credit decision-making system. With AI-supported loan automation solutions, banks are able to create profitable conditions faster. At the same time, ML (Machine Learning) allows banks to continue improving their credit models. The technology takes into account the success rates of credit repayment and allows AI to develop more effective strategies for the future.

Robotic Process Automation (RPA)

RPA is also a supportive technology that has to do with lending automation. It automates repetitive tasks and executes the processes following the decision outcomes. In addition, RPA technology enhances regulation compliance allowing the structure of the automated services in line with governmental requirements.

Low-code platforms for credit decision-making system development

The low-code approach is the game changer for banking software development. Low-code platforms allow financial organizations to develop loan processing solutions faster and reduce development costs. The effectiveness of low-code development is defined by several aspects:

Visual development

Low-code platforms use the ready-made parts of code expressed as graphic components. To create an app, the users need to drag and drop the components into the development environment and set the parameters for each component. In relation to credit decisions, low-code platforms for banking software development offer the ready-made infrastructure for BRMS and scoring solutions development. Eventually, the business rules management systems development boils down to choosing the necessary parts of code and defining the rules.

Customization capacity

In contrast to no-code platforms, low-code platforms give bankers the space for decision-making software customization. Manual coding on low-code platforms still requires professional developers’ input. However, the level of developers’ expertise can be lower due to the low-code’s productivity features like automated testing, IDE (Integrated Development Environment), AI-assisted development process, reversible app development feature, and fast deployment.

Availability for citizen developers

Due to the ease of use and app management with low-code platforms, regular banking employees can develop and adjust the rules without professional developers. After a quick low-code training session (or several easy-to-digest sessions), domain experts can implement credit decision-making models to set the parameters of custom components.

Security

Low-code platform providers are responsible for the security and stability of decision solutions. They use multiple practices to ensure the safety of operations in their systems with AI fraud detection, 2-factor authentication models, and role-based access rules. Low-code decision-making systems comply with multiple banking software security regulations such as ISO27001.

Join the future of credit decision-making with ProcessMIX

Start your credit decision system development with the ProcessMIX free demo. ProcessMIX is the back-end low-code development platform for banking software development. It has a ready-made infrastructure for credit decision-making solution development and allows users to customize it as much as users need. You can easily integrate the ProcessMIX loan processing automation system with multiple data sources and other bank applications.

ProcessMIX employs AI/ML and PRA to execute the rules, analyze data from multiple sources, and improve borrower scoring. Several enterprise-level banks have already benefited from ProcessMIX credit decision-making automation solutions. Check our case studies to see how they did it.

What is the future of credit decisioning? was originally published in ProcessMIX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Today, more and more banks are considering replacing their core business system. Most financial organizations are still using the old core systems built in the 1970s and 1980s. The financial organizations were reluctant to invest in the new systems due to the long-term replacement process. Bankers got away with quick fixes like COTS solutions and other narrowly-focused software.

However, technology advances at a rapid pace making legacy systems more costly and unviable. According to a Bloomberg article, the necessity of digital banking services spiked after the 2019 pandemic. Legacy systems rarely employ cutting-edge technologies (AI, ML, RPA) that improve banking operations efficiency. In 2018, Gartner’s research showed that legacy banking systems are about to be extinct by 2030 due to these reasons.

In this article, we will review the downsides of legacy banking systems. Also, we will indicate the faster ways for bankers to replace them with up-to-date solutions.

Why legacy credit system replacement is crucial

Banks are under pressure to upgrade credit digital processes for both internal and external reasons. These are the major factors that push them towards legacy banking system replacement:

Rising customer expectations

Bank clients expect to access as many services from their smartphones or laptops. It’s convenient to manage your bank account, apply for the loans and repay them online. Legacy credit systems fail to handle the risks tied to the online, paperless loan granting processes.

Tight competition

Banks need to digitize their credit-related processes due to survive in the competition. Legacy credit systems have low time-to-decision, lack automation, and are harder to manage. Instead, the banks with modern credit systems and practices get an edge over the competitors with automated decision-making, improved risk management, and effective process execution.

Regulatory pressures

FinTech regulations get stricter and raise the bar for credit process standards. Banking technologies are expected to be faster, safer, and integrated with modern digital tools. Often, legacy credit systems cannot fit into the modern image of a banking credit management system. It limits the array of services a bank is allowed to present to customers and lowers the prestige of an organization itself.

How do legacy systems hinder banking organization development?

The pressure points highlight the weak sides of legacy credit systems. They hinder banks’ digital transformation and reduce profitability and credit-related process efficiency.

Higher maintenance costs

Credit systems created without a modern vision in mind are loss-making.

A legacy credit system is harder to fix and support. Enterprise-level banking systems include thousands of lines of code and work with huge volumes of data. Finding and fixing a problem that may arise during peak hours can take too much time and effort. It leads to higher IT spending and system idle time costs.

Also, there is an increasing shortage of specialists capable of managing legacy credit systems. The reason is the outdated programming languages and technologies which form the basis of such systems. The vast majority of developers strive to learn sought-after development practices. So, there are fewer specialists that work with legacy credit systems — they charge more and are hard to find.

Inflexible credit models

The old credit systems are harder to adjust in response to changing credit strategies. Every time a bank with such a system needs to add new properties to a system, the professional developers need to get back to the source code.

The same thing happened with the integrations and 3’d party service integration. Although additional banking services consider legacy credit system requirements, a bank will have to change its credit strategy to the features of the solution. That’s because off-the-shelf solutions for legacy credit system supplementation have no customization options.

On the other hand, the old-fashioned credit models are hard to scale in response to the rising amount of applications. It is extremely daunting to add new features for effective credit application processing.

Poor customer service

With the legacy system in place, banks risk dropping out from the competition due to the low-quality service and inability to present state-of-art services online. Customers expect their bank to offer online payments, fast and paperless loan granting, and support. Legacy credit systems rely on practices that are no longer effective compared to credit software with powerful decision-making engines, AI-powered risk management, and RPA process automation. As a result, customers have to wait for a long time to have their loan applications processed.

Additionally, outdated credit automation systems fail to provide service personalization features. They cannot process customer data from multiple sources in a way to offer optimal credit conditions to clients. At the same time, today’s BRMS systems and AI data analysis do a great job of making credit decisions in line with customers’ demands.

Internal inefficiencies

Legacy credit software provides poor internal data management and team collaboration. The outdated solutions are still leaving much space for paperwork and handleless digital data. Moreover, the old systems lack integration capacity. Thus, the bank’s agents waste time reentering the same data in the various banking system parts. And finally, the task assignment with legacy credit solutions demands human involvement. On the contrary, modern credit software allows one to set the task assignment parameters in a rules management engine once and distribute loan applications across departments automatically.

Increasing risks

Outdated credit models don’t give banks enough tools and functionalities to enhance risk management. Such systems are still relying on bank employees’ eyes, while the current risk management solutions analyze credit-related processes with AI. Legacy fraud detection, borrower data analysis, and calculations cannot provide the level of precision necessary to comply with contemporary service regulatory requirements.

How to facilitate legacy credit system replacement?

Legacy credit system replacement is a complex process. It requires preparation and a bank’s credit strategy refinement. First and foremost, a bank should choose the tech stack to bring all the new tools and credit decision-making core. You cannot use a one-size-fits-all approach when developing your credit software. So, the starch and the system itself should reflect your business strategy in detail. Therefore, the off-the-shelf solutions can only be a workaround during the long-term custom credit system replacement. But traditional custom development of such tools can take years and millions of dollars to deliver.

However, there are faster ways to develop modern credit systems or their parts. One of the most effective and fast today is low-code development. Banks can pick low-code platforms to build the whole infrastructure for credit decision-making with it or integrate separate parts with it. Low-code platforms for loan system development bare several benefits:

Development speed

Low-code platforms are based on visual development approach that includes pre-made components, graphical connectors, and drag-and-drop functionalities. To build the credit processing app low-code platform users don’t need to write code manually from scratch.

At the same time, low-code platforms allow to customize the applications with manual coding. For instance, when a bank needs to implement a unique strategy into its decision-making process, it can build the basis from ready-made code components and add custom elements with code.

Manual development with low-code platforms is also easier than traditional. Low-code platforms include IDEs (Integrated Development Environments) that facilitate development team collaboration and CI/CD processes. IDEs do it with features like version history, testing tools, and AI assistants.

Easy Integrations

Low-code applications for credit systems are easy to integrate with existing solutions as well as modern ones. The low-code platform offers pre-made connectors for multiple technologies so the integration process takes only a few minutes.

Flexibility

Low-code apps are easy to adjust whenever you need them. You can change the properties of the low-code credit solution within minutes without any programming. In addition, low-code apps are easy to scale due to reusable code components and flexible infrastructure.

Seamless Maintenance

Low-code platforms reduce IT department app support and maintenance. Owing to the intuitive interface and visual flows, domain experts and citizen developers (employees with little low-code training) can keep track of the app’s performance and change the properties of the app in several clicks.

Security

Low-code platform providers are responsible for the security and stability of the banking apps created on their platforms. Low-code development platforms often comply with government security standards for banking software like ISO27001, ISO20022, etc.

Try the ProcessMIX platform for credit system development.

ProcessMIX is a back-end development low-code platform. Initially, the platform was developed for the banking industry’s needs. ProcessMIX includes functionalities and customizable components for credit decision-making engine development, AI-powered fraud detection tools, borrower scoring engines, banking data management, online support, and more.

The platform allows users to create automated credit decision-making flows, complex borrower scoring, transaction security control apps, calculation, and risk-management apps. The credit software is supported by AI trained especially for banking operations control.
You can try to use the platform right away with a free ProcessMIX demo. It will allow you to evaluate the platform and see if it fits your credit system development project requirement. If you have any questions regarding loan processing software development with ProcessMIX, you can contact our team or read our comprehensive User Guide.

Downsides of legacy credit systems was originally published in ProcessMIX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Financial software is the staple upon which the global economy is built. Since the first online banking app appeared in 1991, banks have been adopting digital services at a rapid pace. Along with the technology, customers have been including more online service requirements. And here we are in 2023. 89% of recent McKinsey report respondents use at least one payment service daily. At the same time, 54% of digital wallet users are likely to expect the service from their bank.

For banks, the digital transformation process is never ending. They develop an app, then modernize it as innovations pop up, and repeat. But, with traditional software development methods, it’s become hard to catch up with the sector’s innovators.

According to Gartner, the demand for software has outgrown the capacity of developers to produce it. That’s why bankers and other businesses turn to low-code development. It is the fastest way to build financial applications and services. Microsoft anticipated 450 million of 500 million apps to be created in the next 5 years and will be designed on low-code and no-code platforms.

In this article, you’ll discover how you can use low-code platforms to develop your banking applications fast and with a reasonable budget.

What is low-code?

Low-code refers to a visual development approach combined with manual development capabilities. Low-code platforms offer a convenient visual development environment with pre-made code components. The components work for different banking app functionalities. Users can compile apps by dragging and dropping them on a low-code development environment.

The ease of use allows citizen developers to build through the whole app creation cycle including app integration, testing, and deployment in the cloud or on-premises. It’s certainly true — sophisticated law-code banking apps require custom features and code components. Therefore, for the majority of banking apps, the input of professional developers will be a must.

Why low-code is a game-changer in banking software development?

A great deal of low-code productivity lies in improved CI/CD processes. In a low-code platform, developers and domain experts can collaborate through the IDE (Integrated Development Environment). The IDE allows both parties to be on the same page at every stage of app’s development. Because of this, bank managers can control the integration of the business strategy into the apps.

Low-code apps are easy to integrate with various databases, 3r’d party services, and other banking applications through APIs (REST, SOAP, etc.). The integration process can literally take minutes. In addition, low-code includes testing tools that automatically check the app flow before deployment. Low-code platforms offer immediate deployment options including cloud (AWS, etc.) and, sometimes, on-premises.

Another important trait that has made the low-code approach a disruptor in FinTech development is its AI/ML capabilities. AI/ML technologies enable banking software developers to create automation and support tools.

And last but not least is the ease of use that reduces the IT department’s involvement in software maintenance. After short low-code development training, non-IT employees can learn to alter the parameters of applications. Eventually, banks will be able to reduce IT operational budgets, or redirect them to more intense projects, and facilitate response to strategy changes.

Types of banking apps you can build with low-code

Low-code platforms allow businesses to produce many types of banking applications. The variety of such apps depends on the low-code platform’s specific features. For instance, there are back-end and front-end low-code development platforms. The back-end low-code platforms offer the components for functionalities whereas front-end ones are for data presentation and interaction. Here are some examples of software you can create using a front-end or a back-end low-code platform:

Client-side applications

Online banking applications with evolved customer profiles. Low-code banking apps for customers allow users to register a bank account, make transactions, participate in bank promotions, apply for loans, and more.

Lending automation

Low-code loan automation tools to get connected to client-side apps or bank websites to perform loan origination, granting, and repayment control with little human involvement. Low-code platforms enable such tools with AI/ML and RPA capabilities that allow the bank to reduce loan processing cycles and reduce risks. Low-code lending automation applications are able to automate borrower scoring and credit decision-making based on data from multiple sources.

Omnichannel support applications

Smart bank assistance is part of the bank’s website or customer application. Low-code banking support bots can answer frequently asked questions. To do that, the assistant takes info from internal resources. If a customer needs some type of service, it redirects them to a particular specialist.

Risk management tools

Banking low-code apps for risk management make risk evaluation considering the data from multiple sources (e.g. social media, personal info, etc.). AI-powered low-code apps evoke sources to derive the information on client demographics, credit history, social status, and other factors relevant to risk assessment.

Fraud detection apps

With a low-code platform, users can create fraud detection software. This type of low-code app spots suspicious actions, false personal information of customers, and restricted transactions. These practices also have to do with the business rules management engines that set the metrics for AI to compare the data against.

Internal operations

Low-code applications can improve internal banking operations with cross-department collaboration tools, automated task assignment, and data management.

Benefits of banking app development with low-code

Faster innovation adoption

Low-code platforms make software development faster and easier. Applied to the FinTech field, they facilitate the development of new automation tools and integration of state-of-art banking digital practices. Even when a solution demands professional development, the process will be much faster due to the low-code productivity and testing tools.

lower development risks

It is difficult to spoil a low-code banking app development as the majority of code is delivered as clean pre-made graphic components. At the same time, custom code parts of the app get AI-powered quality assurance testing at each stage of its development. In other words, a low-code platform will spot any code inconsistency and won’t let developers proceed to deployment before a bug is fixed.

Additionally, the tight collaboration of domain experts and developers will help a bank to ensure that every function of the app responds to the business goals. In contrast to traditional development, the bank’s management can spot inconsistencies early on during the development process. In case of any issues, the developers can use a low-code version history feature to track back to the problem and roll back the code to a needed stage.

Seamless scaling

Low-code apps are easy to scale owing to reusable code components. low-code banking apps easily integrate new features and 3r’d party services in hours rather than days or weeks. Moreover, a bank won’t need to involve professional developers to add new simple features.

Fewer service failures

Due to the pre-made code components, low-code financial applications retain the consistency of the code. This makes such apps less prone to failure. In addition, low-code platforms have embedded software testing/debugging tools (which reduce risks of app failures even more) that signal users about any errors in app performance.

Develop your first banking application with the ProcessMIX platform

Words cannot fully describe the immense impact low-code platforms make on banking app development. The low-code platforms themselves do. Try the free ProcessMIX Demo and see low code in action. This back-end low-code development platform allows you to create both simple and complex applications 3x faster than traditional development practices. ProcessMIX has the AI/ML capabilities to support the development of automation tools for landing, decision-making, fraud detection, client support assistants, and other business-critical banking applications.
Dozens of financial organizations have already used the platform, saving thousands of dollars and months for their app development. Check our case studies to see what they managed to achieve with ProcessMIX.

How Low-code Platforms are Revolutionizing Banking Application Development was originally published in ProcessMIX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Since the digital revolution, banks and lending organizations have been adopting various technologies to provide services online. Largely, this change was motivated by internal process improvement and rising expectations of tech-savvy customers. Payments, transactions, registrations, documentation management, loans, and other banking services became available right on your device.

However, financial apps and systems are complex. They require a high-security level, precision, and seamless performance to ensure top service quality. Because of this, the drive for best-in-class technologies is going strong and led banks directly to AI solutions.
Artificial Intelligence opened the possibility to offer online even the most sophisticated services, like lending. Without the technology, banks couldn’t digitize all the steps of the lending process while eliminating the security risks. The Economist called AI a game-changer in the FinTech industry and found out the technology permeates multiple lending processes. Respondents of the survey use AI to support IT departments, scoring, fraud detection, and other core activities you can see in the graph below.

In this article, you’ll learn about:

• How lenders use AI today;
• AI adoption trends
• How AI automates lending processes and its benefits
• The tools to create AI-powered apps faster and on a moderate budget.

The current state of AI in landing

Banks have already been using AI for several years by now. Although the technology isn’t easy to introduce into the legacy systems, lenders strived to adjust to it at all costs.

AI technology became a hot topic among banks owing to its ability to automate, facilitate, and enhance lending processes. The technology is capable of repetitive task automation (in combination with RPA), predictive analytics, advanced risk assessment, and neural language processing.

AI serves as an employee assistant, making suggestions to the team members to make their work easier. In this way credit consultants and decision-makers can focus on more vital tasks while the system handles most of the document processing and other repetitive actions.

How AI automates lending processes and its benefits

Faster application processing

Loan application processing requires much documentation and borrower data processing. In the past, it took weeks for a bank to make a loan decision. With AI, lending systems are able to process loan applications automatically. First of all, AI-enabled lending applications allocate the application to the corresponding department and assign it to a suitable specialist. AI fills in the fields in the documents with appropriate data, eliminating a great deal of manual typing. It allows the system to derive borrowers’ data from internal and external sources to use it for automated decision-making. When the decision is ready and approved by an employee, the system can then initiate transactions.

Improved borrower scoring

As a part of the loan decision-making process, AI can score borrowers based on a set of rules. All the bank’s employees need to do is define the scoring rules in the system. The rest of the scoring actions like borrower data analytics, calculation, and decision presentation are handled by AI. In the case of borrower scoring, AI works with business rules management systems (BRMSs).

It has greater data processing capacity than bank workers in terms of speed. It finds valuable scoring points in larger volumes of information in minutes (depending on the AI system) and can request additional data automatically. Therefore, AI and a powerful scoring engine do the work of a whole department with more precision in less time.

Costs reduction

Owing to the level of automation and the capacity to execute processes at the same time, AI eliminates the cost of lending processes. As the AI does much work itself, a lending organization won’t need to pay salaries to specialists, as before. It allows banks to reduce budgets for loan processing, customer care, and management.

Internal data management

AI makes internal data management and inter-department communication much faster and easier. Primarily, it distributes the loan-related data and customer profiles in the corresponding data sets. In doing so, AI can analyze the data to make valuable insight into department productivity, expected revenues, and customer demographics.

Service personalization and customer support

By analyzing customers’ profiles and their service interaction history, AI can define their needs. AI-enabled lending applications can suggest the most effective customer care strategies, based on their demographics, levels of income, social status, and other factors. Additionally, it offers the customers suitable loan conditions that are beneficial both for the lender and the borrower.

In terms of customer support, AI can serve as an automated consultant, answering customer questions or directing them to a particular specialist that can help them. Neural language processing, performed by AI, facilitates the client request processing and easily finds the necessary info in the client portals.

AI adoption trends in lending automation

Lenders are still exploring the power of AI and how they can use it to increase their service profitability and customer satisfaction. Here are some trendy AI use directions.

Risk management

AI has revolutionized the bank’s underwriting and risk management processes. Artificial Intelligence can access up to a hundred data points to check the borrower and make precise estimations for a loan amount, payment time, and margins. Additionally, the technology analyzes the customers’ digital data more effectively than humans, which makes loan conditions safer both for banks and borrowers.

Regulation compliance

Large banks investigate AI/ML capabilities to comply with the numerous regulations. AI allows enterprise-level lenders to consider the regulations by means of automated compliance checks. The technology executes regulation checks without errors and doesn’t miss any of the valuable points. Due to the power of AI, banks are now striving to automate as many regulatory processes as possible.

Loan processing capabilities

Lending service providers aim to increase loan application volumes they can process in a shorter time. The volume of loan applications processed depends on the loan application processing cycle time. Automated loan processing combined with AI can handle almost every step of the loan granting cycle, making it several times faster.

AI + low-code = more benefits

AI is a sophisticated technology that requires large budgets and a professional development team. Often, to use AI, banks need to modernize their whole system. However, there are cheaper and faster ways to develop AI-powered solutions. One of the most cost-effective and fastest ways to make AI work without full-scale banking system modernization is low-code development.

You may ask: what has AI got to do with low code? The thing is that when you combine a robust software development tool with AI, you get the AI-powered lending application much faster. Low-code’s visual development approach allows developers to build apps from the ready-made code components. Here’s what the low-code development environment looks like.

At the same time, professional developers can write code for custom features to manage the application with business strategy. Low-code platforms make it possible to integrate the lending application into data endpoints in minutes. Because of this, low-code apps give AI enough data to make an in-depth borrower evaluation.

Low-code development is also accessible for citizen developers and domain workers which can reduce system maintenance costs when the application is ready. For instance, the sales department can change the parameters of customer scoring without turning to the IT department.

ProcessMIX for AI-powered lending software development

Powerful low-code platforms, like ProcessMIX, integrate AI technology to enable users to create AI-powered lending automation solutions. The platform specializes in banking software development and is an embedded scoring engine, business rules management systems, and AI/ML capabilities.
You can start creating your lending automation app right now with a free ProcessMIX Demo. The ProcessMIX team is ready to help you at any stage of your software development.

Lending digital transformation powered by AI and Automation. How does it work? was originally published in ProcessMIX on Medium, where people are continuing the conversation by highlighting and responding to this story.

In the past, businesses needed to find a professional developer to create even a simple website or a mobile app. Let alone complex software and business management systems. The phrase ‘software development project’ is associated with long-term processes and huge investments.
Now, software development is getting easier. When we need to develop an application, we don’t necessarily need to think of finding teams of outsourced developers, large IT budgets, and a long development process. Research Markets predicts the low-code market to reach $182 billion by 2030. In this article, we will answer why low-code and no-code is the next big thing in the software development world.

What are low-code and no-code platforms?

Low-code and no-code platforms are software-as-a-service products that offer functionalities for robust software development. The platforms have visual development interfaces with a set of pre-made graphic code components. Each component represents a certain function of an application that users can add by dragging and dropping. With these features, low-code and no-code approaches make software development much faster and easier. We will review the features of low-code and no-code platforms that enhance software development further in this article.

The difference between low-code and no-code is revealed by the name: no-code is all about visual development while low-code additionally allows you to write code for customization. However, both approaches have a subscription-based payment model, graphic development flow, and other similarities.

Where to use low-code and no-code platforms?

There are a lot of low-code/no-code platforms for various development purposes. Some platforms specialize in front-end development, and some on the back end. Some have enough power to produce various types of applications, some only one type. Before we move on to the types of software you can build with low-code and no-code platforms, there’s one very important piece of information you should know.

Usually, no-code platforms have narrow purposes, while low-code platforms enable users to build a variety of software. Let’s take Wix and ProcessMIX as examples. Wix is a no-code website constructor that focuses on website development. Using Wix, non-developers can create websites for commercial and personal needs. ProcessMIX, on the other hand, is a low-code platform for back-end development. You can use it for simple projects having no development skills — only a short introduction to the low-code platform is necessary. At the same time, developers can create complex back-ends for automation tools, data management, AI-powered analysis, etc. In addition, the low-code platform will allow you to customize the functionalities to match your business needs better.

Here is the short list of applications you can build with low-code and no-code tools:

• Web applications;
• Data management and analysis tools;
• Mobile applications;
• Business system integration tools;
• Business process automation tools;
• Internal resources.

Low-code platforms serve businesses in every industry. Even banking and healthcare software that has sophisticated requirements can be created with low-code platforms. The use of advanced technologies like AI/ML and RPA allows low-code software to comply with the most demanding security and performance regulations (ISO27001, etc.). Low-code platforms facilitate business digital transformation in the domains of process automation, customer service, internal sources management, and service quality control.

Why low-code and no-code is the future of software development

Millions of pro developers work to make low-code platforms better. Every month more and more low-code tools that cover one or another digital transformation need are appearing on the market.

But what are the factors that allow low-code platforms to be called the future of software development? Here we mention the benefits of low-code you can experience right now.

Lower development costs

Low-code tools charge only a subscription fee for a certain user plan. The more sophisticated features are included — the more expensive the plan. Low-code/no-code platform pricing ranges from zero to several thousand US dollars per month. Yes, there are platforms that offer some of their functionalities for free. At the same time, there are demo versions and free trial periods that allow users to test a platform for project requirements.

Although low-code platforms allow you to build apps visually without coding skills, they may require some for custom low-code software development. It means that to low-code development costs you can add the salary of one to three junior/middle developers. In addition, the price of custom low-code development is much lower than traditional due to improved CI/CD processes, productivity tools, and fast integrations.

Reduced IT support

Another feature that makes low-code platforms the development tool of the future is their availability for citizen developers and non-developers. With low code, it’s not necessary to have advanced development skills and experience to build applications. Individuals and regular business employees can handle simple app development, software maintenance, and configuration. The only necessity for them is to learn the low-code development concept and follow platform-specific user guides.

Robust cloud adoption

There was a time when cloud technologies were accessible only to big businesses. Cloud migration was a costly and complex process that involved expert developers. In fact, it still may require the same resources. But low-code platforms facilitate the cloud adoption process to a certain extent.

With low-code platforms, every business has the opportunity to introduce cloud technologies into their processes. Low-code tools like ProcessMIX, Outsystems, and others allow developers to deploy applications on the cloud immediately after the testing. Moreover, users can integrate their existing systems and apps with various cloud services.

Easy legacy system modernization

Low-code and no-code applications can supplement your existing business system or even replace it. Whenever a business needs a new feature, it can be easily created and integrated with a low-code platform. Low code allows for building routine process automation tools, customer applications, client resource bases, business rules management, data analysis tools, etc.

Low-code platforms speed up the app integration process with ready-made connectors. You can integrate and deploy an app in minutes instead of weeks as it is with traditional development.

Improved system flexibility and scalability

Scaling a regular application is a tedious process that requires a lot of effort. To expand the app businesses needed to choose the right technology, plan the process, and spend thousands of dollars on the developers.

Low code changes the paradigm in regard to software scaling and modernization. Usually, all it takes to scale a low-code app is to take the existing code components and add them. Due to the code reusability, the ease of scaling stays the same for custom code parts of low-code apps too.

Additionally, low-code apps are more flexible as you can easily change app properties without coding. To make changes in the existing application, users need only access the project on the platform and change the components.

Conclusion

Low-code platforms have already facilitated digital transformation. According to IDC, 560 million applications were developed by this year. This is two times more than in the previous decades. Most of these apps were produced with the help of low-code and no-code platforms. Considering the current power of these two approaches and the pace of their expansion, it becomes obvious that low-code/no-code tools are the future of software development.

Try ProcessMIX low-code platform

As the old saying goes — a picture is worth a thousand words. That’s why, the best way to see the power of low-code development is to try it yourself. You can start with the ProcessMIX free demo version.

ProcessMIX is a back-end development low-code platform that allows businesses to build automation tools, business rules management flows, customer onboarding apps, etc. To find out more on ProcessMIX use cases, read our clients’ success stories.

Are Low-code And No-code Platforms the Next Big Thing In the IT Sector? was originally published in ProcessMIX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Keeping your software up-to-date, safe, and performant takes resources and effort. As a company’s client base grows, it needs to scale the system — that means new features, integrations, and automation tools. Alongside that, the costs of software maintenance are continuing to rise. Sooner or later, the costs become so high that a company needs to find cheaper and faster ways of maintaining its digital environment. It’s no longer a question of if, it becomes a question of survival in today’s ultra-competitive market.
According to Statista, businesses will spend a whopping $856 billion worldwide on IT. A significant part of this money will be invested in software maintenance.

Fortunately, the software market offers a wide array of options to scale business systems and maintain their smooth performance. COTS software, 3r’d party services, and robust development platforms are some of the most widespread tools to achieve maintenance objectives faster. You can find more details in this study by ResearchGate. However, there’s no match to low-code/no-code. These approaches are disrupting software maintenance, and facilitating the creation of new features, automatization tools, and system security. Here, we will focus on how you can use low-code and no-code platforms to improve your maintenance processes — without any extra stress.

Why do businesses need software maintenance?

Companies need software maintenance to modernize their systems, keep them safe and extend the software functionality to reflect changing business strategies. Fast-appearing innovations and ever-changing software safety regulations require constant system updates. Especially for banking and healthcare businesses where the safety and quality of services are crucial. Any service inconsistency or code breach may put the business in jeopardy.

Developing businesses never stop extending their systems. Although they maintain their systems with new apps, integrations, and services, additional features brought by the new apps allow a business to cater to more customers, improve their experience, facilitate internal activities, etc. Developing and maintaining a business system is key to staying competitive in the market. For instance, if your system fails to process a hundred more service requests per day, there will always be a competitor that will process them for your clients.

What makes software maintenance become expensive?

First off, let’s find out the reasons behind the rising maintenance costs and what factors you’ll need to take into account.

Software maintenance costs are tied to IT staff salaries. The bigger the system, the more developers it requires to stay performant and updated. The average hourly rate of a middle-level developer is $15–30, as UpWork reports. Hire five full-time developers and you’ll spend at least $30,000 in three months.

A business can expect a rise in maintenance costs if:

• The business expenses
• It needs urgent system updates
• The business system requires new features
• The number of clients rises

However, low-code and no-code platforms make software maintenance and scaling processes much faster, easier, and cheaper. Both low- and no-code approaches can be applied to multiple business IT processes, including system scaling with new apps, regulations compliance, automation, etc. But before we dive too deeply into the benefits, let’s get an overall view of low-code and no-code platforms.

What are low-code and no-code platforms?

Low-code and no-code platforms are the software tools used for robust software development. The platforms follow a visual development approach where users can drag-and-drop code components expressed as graphic elements of some kind. Every element has its function and a platform the user can change their parameters whenever necessary.

At the same time, the low-code and no-code platforms differ as the latter doesn’t have the functionalities for software customization. Low code enables developers to create custom components and integrations. In addition, the customization process in low-code platforms is usually accompanied by powerful technologies, such as AI or ML. These technologies enhance the app’s functionalities themselves and allow them to control their performance and quality.

Benefits of low-code and no-code approaches for software

Faster development

Visual development interfaces of low-code and no-code platforms allow the creation of additional features for software faster. It works quickly due to pre-built graphic code components, robust development tools, and drag-and-drop user flows.

In-built testing and debugging tools

Low-code/no-code platforms allow testing applications and systems directly in the platform. The platforms are able to inspect the apps before and after the deployment.

Improved system scalability

Many low-code tools include reusable components that speed up system scaling. It means that you can use parts of previously developed apps to create new features or extend the app. The flexibility of low-code and no-code tools facilitates software scaling so it can take hours or days instead of months.

Easy integrations

Low-code platforms have multiple pre-built connectors to the databases, 3r’d party services, BI systems, and applications. With a low-code tool, you can integrate an app with a 3r’d party in minutes.

Availability for citizen developers

With a low-code platform at hand, a company doesn’t need to hire a large IT department. Low-code and no-code solutions are easy-to-use so that even other department employees can grasp the basic concepts of using them. So, instead of hiring new expert-level developers to maintain your system, you can train the current staff to use low-code tools. Nevertheless, the maintenance of a sophisticated low-code system requires at least a junior/middle developer’s input.

How much do low-code and no-code maintenance costs?

Low-code maintenance costs will consist of the platform subscription payments which can be from free to $1,000 per month. The cost of a low-code/no-code platform subscription depends on the complexity of a platform and the set of features your company needs to maintain it. The more maintenance tasks you try to solve with low-code/no-code, the higher the price for a subscription becomes.

In addition, you can include the salary of a few (1–3) middle-level developers, if you plan to implement complex tools. It’s important for these developers to have experience with low-code platforms.

How to start using low-code/no-code for software maintenance?

To start using a low-code platform for software maintenance you should decide what exactly you need in that relation. Is it just a new feature for your customer application? Then, you can leverage only a no-code solution. However, if you seek a solution that solves multiple maintenance needs, you need a low-code platform. Low-code platforms are capable of facilitating:

Regulation compliance

Low-code tools for back-end development allow users to employ a business rules engine. Business rules are the foundation of compliance automation. Using a BRMS (Business Rules Management System), businesses can create multiple rules and automate their execution across every business app. Usually, low-code rules management is powered by AI/ML technologies that improve precision and facilitate rules execution.

Automation tools development

Low-code BRMSs also allow the automation of multiple business tasks and processes. It can be automated data processing, transactions, process initiation, decision-making, and many other repetitive tasks. In the case of automation tool development, low-code platforms employ RPA technology to perform the actions faster and eliminate the possibility of mistakes during the process.

App development

This is the basic feature of every low-code platform — — app creation. The types of applications you can develop depends on the platform. There are low-code platforms for back-end and front-end development. You can turn to a low-code solution when you need any additional app like a customer portal, client application, internal knowledge base, etc.

Reduce your software maintenance costs with ProcessMIX

If you are ready to cut maintenance budgets with low code, try the free ProcessMIX demo now.

ProcessMIX is a low-code platform for back-end development that allows businesses to improve scaling, regulation compliance, and automate business processes. The platform has an intuitive app-building interface and plenty of pre-built components to develop complex apps in weeks. What’s more important, ProcessMIX has a BRMS system powered by AI/ML to build powerful rule-based automation tools for different business software maintenance needs. Moreover, the platform uses RPA technology that makes automation even more performant.

The ProcessMIX platform has already proved itself in banking, manufacturing, and other industries. You can find out more about the results ProcessMIX helped to achieve in the case studies section.

How No-code & Low-code Can Reduce the Cost of Software Maintenance was originally published in ProcessMIX on Medium, where people are continuing the conversation by highlighting and responding to this story.

Digitization and automation have taken financial business processes to next-level effectiveness, productivity, and profitability. Banks and lenders that bring automation technologies to their lending processes get a crucial advantage over their competitors. That’s why the rates of digital transformation in the automation field are growing at an unprecedented rate — especially after the pandemic and the big quit.

The FinTech field offers a plethora of technologies to automate loan-related tasks and processes. In Gartner’s graph below, you can see the major financial technologies and how they are expected to evolve in the next decade.

But do you use the full power of loan automation technologies? Do you take the best of them? Do you automate as many loan processes as possible? You will get the exact answer after reading this article. Here’s what we touch upon to evaluate your current loan automation system and see how to enhance it:

• The loan automation system structure and crucial features
• Loan processes that can be automated
• The positive impact of automation on these processes
• What technologies can you leverage to bring loan automation faster.

What is a loan automation system?

A loan automation system is a set of software that allows banks and lending organizations to automate loan origination, risk assessment, underwriting, repayment control, and analytics. Loan automation technologies work with commercial (business credit lines, invoices, SBA) loans and personal (personal credit lines, mortgages, Buy Now Pay Later) ones.

Core features of loan automation software

The features of a loan automation system can vary according to the particular need of a financial organization and its client base. Let’s consider the core features of every loan origination system by the type of process they automate.

Borrower onboarding and pre-qualification

First, loan automation software should include a digital registration form where the borrower can leave all the required data (a sum of money, purposes, level of income, personal data, etc.). It comes with the pre-defined and automated eligibility requirements the borrower needs to match to proceed with the loan. Then, the system needs an automation algorithm to extract the borrowers’ information and deliver it to other automation software parts. The loan automation system should work with AI to qualify the borrower better. Automated pre-qualification also includes borrower categorization by status and defines the loan type.

Risk management

Loan automation software should be able to process customer data in various formats (XML, JSON, PDF, etc.). To evaluate risks and give out profitable loan granting conditions, the automation software includes business rules management and scoring systems. These systems assess the risk using customer data and score a borrower following the rules defined by the bank. Then the score comes to a decision-making engine that automatically defines the loan conditions with minimum risks. To reduce risks, the system can highlight that additional information from an external source is needed.

Task assignment

The system should automatically assign the borrowers to a specialist that works with these specific client and loan types. Additionally, the system is embedded with an internal chat where the employees can discuss particular cases and make collective decisions.

Underwriting

Automated loan underwriting includes features for cross-department loan approval, automated loan approval forms creation, and automated rule-based loan approval or decline. The system automatically informs a borrower about the decision via email, a customer portal, or a message. It can also transfer the money automatically to the borrower when the loan terms are accepted by the borrower. Powered by AI, the system can suggest alternative credit conditions to the client, if they decline the bank’s loan offering.

Payment control

This part of the system creates and sends payment invoices automatically and tracks the loan payment status (due, fully paid, partially paid). Whenever the borrower fails to pay on time, as agreed in credit terms, the system signals the bank’s employees and the borrower. Then, the system can automatically impose penalties on the borrowers that break payment conditions.

Data management and analytics

Loan automation software also saves the borrowers’ loan history and other data relevant to potential future interactions. It sends the data to a bank’s database and can also derive it when the borrower interacts with the software again. In addition, the system analyzes the data of all the borrowers and is able to produce statistics on loan payment success rates, borrower demographics, and more.

Security measures

Loan automation tools comply with financial software security policies like FCRA, SOC, MLA, etc. Due to AI-powered fraud detection, data encryption, multi-factor authentication, and access control based on roles. These features make lending automation solutions more reliable for micro-lending organizations and large international banks as well.

Loan automation system integrations

To make the loan automation software work fast and improve risk management, you need to integrate it with other bank software and third parties. These are the most important integrations to improve loan automation software functionality.

Client-side application

Integrating a loan automation tool with a customer banking app or a portal facilitates loan processing. With this, borrowers can submit their applications straight to the loan automation system. Also, the integration allows borrowers to control their repayment process while banks can withdraw the funds automatically from a digital account.

Business rules management system

Business rules management systems enhance process automation and allows domain experts to keep the rules up to changing lending strategies.

BI (Business Intelligence) solution

Loan automation software can perform deep data analytics and send reports to the bank’s BI system. This allows the financial organization to process and analyze large amounts of data, and utilize it to make decisions.

Accounting software

Paired with lending automation makes the underwriting process easier. This helps optimize the process for the bank and ensures they keep track of their finances.

Bank accounts

Works for big banks that provide debit cards and digital banking services. Integrating the lending automation system with bank accounts allows for automating loan payment withdrawals with a borrower’s consent.

Loan origination automation technologies

The loan automation process is powered by a number of technologies that allow the process to occur and enhance it. Here are the technologies that are used for automation or for the creation of additional features of a loan automation system.

Artificial Intelligence (AI)

Artificial intelligence is an essential technology for loan automation as it can impact almost any process in a system. AI allows banks to make more precise decisions, better analyze the borrowers’ data, spot suspicious transactions, and create optimal credit conditions.

Robotic Process Automation (RPA)

RPA is another inseparable part of a lending automation system. It handles the automation of an array of processes starting from loan initiation to money transfers. PRA speeds up automated process execution and enhances its delivery to optimize the system.

Low-code and no-code solutions

According to Gartner, 83% of financial executives see low-code automation technologies as a major opportunity to speed up their lending process automation.

Low-code and no-code solutions are a fast way to develop lending automation systems or other financial automation tools. Low-code and no-code platforms have an easy-to-use visual development interface that makes development easier and faster. With them, developers and bank sales experts can build tools from ready-made components for lending automation software. What’s more, low code allows developers to create custom components and automation workflows.

Low-code tools offer pre-made connectors to multiple 3rd party services necessary for the fast lending automation process. The integration process can take several minutes instead of hours.

High-level low-code platforms are powered by AI, RPA, and other technologies relevant to lending automation software. Apart from loan automation itself, these technologies help to maintain the app and keep it secure.

ProcessMIX for loan process automation

If you’ve found a new feature to add to your lending automation system, consider the ProcessMIX low-code platform to kick it into action faster than ever before. Using the platform, you can create additional automation flows and integration in a matter of days or weeks.

ProcessMIX is a low-code platform for back-end that was developed with FinTech in mind. It includes a plethora of out-of-box functionalities for loan automation, credit risk management, transaction security, borrower data management, and others. Powered by AI and RPA technologies, ProcessMIX lending automation drives fast and precise outcomes at any scale.

Explore the loan process automation opportunities with ProcessMIX success stories in the loan automation field. If you are ready to enhance your lending process automation right away, get a free ProcessMIX demo version

How many loan processes do you automate? was originally published in ProcessMIX on Medium, where people are continuing the conversation by highlighting and responding to this story.