App for Getting Instant Loans / Online Lending Platform for Small Businesses
Digital lending platform (and a matching mobile app client) with an automated loan-lending process
Digital lending platform and corresponding mobile app client that fully automates the loan process (e.g., origination, online loan application, KYC, credit scoring, underwriting, payments, reporting, and bad deal management).
Features a custom, AI-based analytics and scoring engine; virtual credit cards; and integration with major credit reporting agencies and a bank account’s aggregation platform.
Engagement model
Time & Materials
Effort and Duration
Ongoing, since February 2018
Solution
Loan Lending App
Project Team
2 iOS Developers, 1 PM, 1 BA, 1 Data Scientist, 3 Back-end developers, 1 QA Engineer
Tech stack / Platforms
Project Background
The client is a FinTech startup with decades of experience in the financial services industry. Recognizing a gap in the current business-loan lending sphere for small and midsize businesses, they decided to launch a fully digital, online loan platform (and a corresponding mobile app) that would fully automate traditional loan business and provide the following benefits:
- Allowing end clients to apply for, receive, and make payments for a loan without having to leave their home
- Lower operational costs for capital providers and lower interest rates for end clients by minimizing human involvement and fully automating the loan process
- Disbursement of more loans with a lower default rate, using an AI-based, self-learning, credit-scoring module
- Moving operations from brick-and-mortar branches to the online platform
The client was looking for a technical partner with profound expertise in the FinTech industry, specifically in digital-lending technologies, artificial intelligence, and mobile app development. Itexus was selected for our expertise in these areas, as well as for our flexible, startup-oriented approach.
Functionality Overview
- A mobile app for end clients with user registration, KYC, loan application, agreement signing via DocuSign, virtual credit card issuance, payments, statistics, and reminders functionality.
- Administration Module featuring overall stats about app performance, user management, scoring settings, and reporting.
- Back office with advanced reporting and loan portfolio-monitoring functionality.
- Advanced credit-scoring model that uses credit history, transaction data, and an ensemble of statistical and machine-learning algorithms to determine credit risk, interest rate, and other parameters.
- Automated Know Your Customer (KYC), Anti Money Laundering (AML) processes through the integration of leading industry KYC/AML providers, such as Experian.
- Automated ‘Bad Deal Management’ module, which automatically sells nonperforming loans to a collection agency.
Third-Party Integrations
- Plaid is a service that allows users to easily, securely, and reliably connect their financial data to apps and services. With its help, we can access and receive relevant and necessary data (e.g., account balance, list of transactions and their categories, and loans.) from a linked financial institution.
- PayPal is an online payment platform that offers low-cost services to individuals and businesses. We use it to enable our clients to conduct online payments.
- DocuSign is a service that enables certified online delivery, acknowledgment, electronic signature, and storage of eDocuments over the Internet. With this service, users can sign loan agreements and other documents online.
- Mbanq is a fully digital and compliant BaaS platform with a unified database and quick time-to-market, that supports a wide range of financial services. It is used to open different types of accounts, process payments, issue virtual and physical credit/debit cards, etc.
- Experian offers a wide range of services for the verification of individuals and companies, including the full suite of KYC and KYB procedures, AML compliance, scoring modules, etc. It is used for collecting user data and receiving clients’ scores in order to make better lending decisions.
- Acuant is a technology provider of identity verification, document authentication, and fraud prevention. With its help, we verify user identity and automate KYC decisions for user onboarding.
- Jumio‘s identity verification, eKYC, and AML solutions fight fraud and other financial crimes, ensure compliance, and help onboard eligible customers into apps faster. We use it to monitor our customers’ transactions to prevent fraud and ensure compliance with AML regulations.
Project Approach
Discovery
The project started with a discovery phase, during which an Itexus Business Analyst and our Software Architect performed an in-depth market and requirements analysis, and created the initial project documentation:
Software Requirements Specification
Document describing all functional requirements, with use cases, diagrams, user screen mockups, user journey, etc.
Software Architecture Document
Document describing suggested technology and architecture of the system, addressing third party integrations, security, performance, reliability, and other non-functional requirements.
Project Plan and Work Estimate
Detailed project plan with all work broken down into 8-16 hour tasks, including priorities, dependencies, and team structure.
UX/UI Design
At the start of the project, our team of UX/UI specialists designed an intuitive, user-friendly UI of the mobile app (in accordance with Apple’s Human Interface Guidelines). The UI mockups were combined into a clickable prototype and used in a video for marketing purposes, long before the system was ready.
Development
- Agile/Scrum development process, conducted using two-week sprints with demonstrations of new product versions and feedback-collecting sessions at the end of each sprint
- Continuous integration and deployment process
- Combination of different tests (unit, automated service, UI-level, and manual)
Artificial Intelligence-Based Credit Scoring
A dedicated team of data scientists from Itexus worked in close collaboration with credit bureau specialists to create an AI-based credit scoring module. This module used different factors (e.g., credit history reports, transactional and social data, the value of collateral, projections for future inflation, and overall economic conditions) to forecast the probability of default on a loan and to calculate optimal loan parameters in real time. The credit scoring module uses a combination of algorithms — ranging from logistics regression to deep neural networks — to achieve optimal performance, regardless of data volume. Models are updated and retrained on a daily basis as new data comes in.
Results & Future Plans
The final product has been delivered within budget and on schedule, ready to launch in the App Store. The client is currently negotiating deals with major national and local community banks in the United States to launch the financial platform as a means to deploy capital through the platform. The Itexus team is currently working on the second version of the product, turning it into a white-label solution.
Related Projects
All ProjectsFinancial Data Analytical Platform for a Large Investment Management Company
Financial Data Analytical Platform for a Large Investment Management Company
- Fintech
- Enterprise
- ML/AI
AI-based data analytical platform for wealth advisers and fund distributors that analyzes clients’ stock portfolios, transactions, quantitative market data, and uses NLP to process text data such as market news, research, CRM notes to generate personalized investment insights and recommendations.
Wealth Management Platform
Wealth Management Platform
- Fintech
Wealth management platform connecting investors with a professional wealth-advisory company, allowing investors to answer a questionnaire and receive either a recommended model portfolio or a custom-tailored individual portfolio, that is further monitored, rebalanced and adjusted by a professional wealth-adviser based on the changing market conditions and client’s goals.
AI-Powered Financial Analysis and Recommendation System
AI-Powered Financial Analysis and Recommendation System
- Fintech
- ML/AI
The system uses machine learning techniques to process various content feeds in realtime and boost the productivity of financial analysts and client relationship managers in domains such as wealth management, commercial banking, and fund distribution.
Algorithmic Intraday Stock Trading System – Stock Trading Bot
Algorithmic Intraday Stock Trading System – Stock Trading Bot
- Fintech
Machine learning can automatically create and refresh an algorithm for solving a complex problem based on a large volume of data. It’s not necessary to search for business-important patterns. Instead, a team of qualified professionals should prepare the right data set for training and automate the entire data processing and application process. But at the same time, it is very important to ensure the quality of data and continuous quality control of algorithms.
Contact Form
Drop us a line and we’ll get back to you shortly.
For Quick Inquiries
Offices
8, The Green, STE road, Dover, DE 19901
Żurawia 6/12/lok 766, 00-503 Warszawa, Poland