RNDpoint
About RNDpoint
RND Point delivers solutions for Financial Industry since 2014. We offer custom software product development as well as integration of FICO and OutSystems platforms in banking, fintech and retail. We support our clients from decision making to working project, giving support in real time and augmenting clients' team. RND Point is a trusted partner for FICO and OutSystems integrating platforms for risk management, decision making, process automation, fraud detection, compliance, scoring and more.
RND Point delivers solutions for Financial Industry since 2014. We offer custom software product development as well as integration of FICO and OutSystems platforms in banking, fintech and retail. We support our clients from decision making to working project, giving support in real time and augmenting clients' team. RND Point is a trusted partner for FICO and OutSystems integrating platforms for risk management, decision making, process automation, fraud detection, compliance, scoring and more.
Key Insights
Services & Focus
Industry Focus
Client Focus
Portfolio
Microservices Implementation in Banking
The microservices implementation was the next step in our collaboration with the retail bank that had previously ordered a new debt collection system. In the first phase of building the debt collection management system for the bank, we participated in the redevelopment of the predictive dialing system (PDS) based on the microservices approach. The reward for success was our greater involvement in replacing the legacy architecture.
During the preliminary research of the bank’s high-level architecture and existing systems all the challenges were taken into consideration and the right systems were selected. Additionally, as we were not the only party dealing with this project, our areas of our responsibility were defined:
The PDS: reassembling the existing backend into microservice containers.
The brokerage system: conducting system analysis, developing functionaland non-functional requirements, and connecting banking applications through microservices.
The AML system: conducting system analysis; further development is being planned.
The microservices architecture functions on independent lightweight modules, which are grouped around particular features. These microservices in the customer’s banking applications exchange data via a variety of compatible formats and protocols. These protocols are then synchronized on demand.
The architectural changes RND Point implemented have opened the way for easy and risk-free implementation of new features. The choice of microservices also proved to be much more cost-effective compared to the legacy architecture.
Mobile applications for Overdraft management and P2P payments
Retail bank received numerous complaints from its customers about the performance of existing applications. RND Point has already delivered its previous projects to the bank. Therefore the bank management invited us to rebuild the applications.
Our experts migrated the functionality and developed new features using OutSystems low-code platform for two the Bank’s apps – P2P Money Transfer and Installment Credit Card. With OutSystems functionality, RND Point’s specialists achieved the following:
Optimization of P2P Money Transfer and Installment Credit Card applications.
Significant improvement of the applications performance.
Applications security enhancement.
Scalable Administrator panel development.
Optimization of database operations.
RND Point’s specialists continue to be actively involved in further development of P2P Money Transfer and Installment Credit Card applications. At the same time, our consultants helped the Bank’s development department to learn the features of the OutSystems platform in order to effectively make knowledge transfer. We have developed all the required application functionality on the OutSystems platform. Our experts have significantly enhanced application security through the refinement of the authentication and money transfer functionality. The application has been launched. Currently, we are implementing new requirements on functionality, including integration with the Apple Wallet. Application development is ongoing. For the site and mobile application: development of the Partner’s Personal Account, updating the rubricator. We will make integration with affiliate sites at item level. For the administrative side: the formation of financial and legal documentation, further database integration and restructuring.
Credit Decision Platform for Lending
The Credit Decision Platform (CDP) is a multi-modular solution for both manual and automatic loan origination application processing.
Fast development and delivery in less than 3 months.
Fail-proof integration with all the internal and external systems.
Processing of 1,000 applications in less than 15 minutes.
Fast and easy adaptation to new business requirements without coding.
To meet the strict deadline and the requirements elicited at the business analysis stage, RND Point’s engineers used the cloud-based FICO Application Studio, which is built on the OutSystems Rapid Application Development platform.
Thanks to our choice of effective and reliable development tools, the development process itself was straightforward and well-paced, with no unexpected issues.
Our engineers finished the development and delivered the fully functional credit decision platform within the contractual terms.
IMPACT
The very first stress testing showed the credit decision platform could process up to 1,000 applications in 15 minutes. Before the delivery, it would take at least three months for the bank’s entire loan department to process as many applications.
In the first year after the CDP launch, the bank reported its record revenue.
Thanks to these achievements, we were able to carry on our collaboration with the bank with much more scaled-up projects. This collaboration is still ongoing.
Debt Collection Automation from A to Z in Just Several Months
Collection is a past-due debt management collection system. It covers all banking front-office workflows related to debt collection.
Decision-making strategy development — completed
Pre-collection stage operations — completed
Soft-collection stage operations — completed
Hard-collection stage operations — completed
Collection agencies — completed
Legal collection agencies — in progress
The customer, the owner of the Collection system, is a sizable commercial bank with a focus on lending to individuals. Therefore, debt collection management is one of the bank’s essential business operations.
It goes without saying that the bank already had a debt-management system, but by that time it became out-dated and not reliable any longer so a quick implementation of a new system was really a mission critical requirement.
As the bank had already used FICO-based solutions with satisfying results, they chose FICO as the basic technology for the debt collection automation system to be developed and implemented by an external vendor.
Our long-term cooperation was subject to our team’s successful completion of the first project stage: Business Rules Management System (FICO Blaze Advisor) implementation. Our company was well familiar with FICO and we proved to be a reliable and qualified partner, so we were proposed to develop the whole debt management system.
Thanks to the choice of the OutSystems-based FICO Application Studio and Oracle technologies, we are able to carry out the development much quicker in comparison with custom development.
IMPACT
The bank started using the system as soon as the first phase was completed due to its stability and reliability.
After the first six months of operation, our automated debt collection system made it possible to manage problematic debts 32% faster on average.
As our cooperation smoothly expanded from one iteration to another, the bank became one of our largest customers. Now, we continue to collaborate on other projects.
Insurance Fraud Detection Software
Our client, the Moscow Municipal Compulsory Medical Insurance Fund, is a state agency formed to finance compulsory health insurance programs and control the rational use of funds.
Insurance fraud is a serious problem for the Fund. Fraudulent claims make up a significant part of all claims received by the Fund, which leads to severe financial losses every year.
To prevent such heavy losses, the Fund decided to take a more rigid approach to detecting and responding to fraud claims. Toward this goal, they were looking to hire specialists to develop an automated fraud detection solution, and that is how they turned to our partner company.
This partner had been working with us for several years and knew about our strong expertise in building complex algorithms and optimizing business processes. The partner invited us to participate in the project and take on some of the heavy tasks.
Working together with our partner, we divided the functions as follows:
The partner company was responsible for business analysis: their team developed specific rules and analyzed cases (see below).
Our experts were responsible for development: we built machine learning algorithms, set up batch processes, and created a system that processed data under high-load conditions according to the developed rules.
To identify fraud committed by the insurance companies and medical providers subordinate to the Fund, we developed a comprehensive ML-based solution.
It covers the following steps:
Creation of rules, a set of characteristics used to group invoices into cases.
Algorithmization of rules.
Application of rules to cases with their further analysis, where a case is a series of procedures followed by a medical center when treating a particular condition.
Rule updates that result in further training of algorithms.
Automated decision-making for detecting incidents, or suspected violations.
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