In today’s rapidly evolving digital landscape, the banking industry has undergone a profound transformation. Comprehensive digital solutions have emerged as a key enabler, empowering banks to provide enhanced services, streamline operations, and deliver exceptional customer experiences. At CriticalRiver, we have embarked on a mission to transform and redefine your banking experience in the digital age. Our platform serves as the gateway to a new era of banking, where traditional barriers and cumbersome processes are dismantled to make way for a smoother, more efficient digital experience. By leveraging the power of cutting-edge technologies, we have revolutionized every aspect of banking, ensuring that you have the tools and resources necessary to thrive in the digital realm.
Seamless Onboarding, Secure Identity: Embrace the Future of Banking
Our platform offers a seamless onboarding process with facial recognition, voice analysis, and fingerprint verification, eliminating paperwork and enhancing speed and accuracy through biometrics, OCR, and machine learning.
Enhanced Security and Fraud Prevention
Unlocking the Power of AI: Safeguarding Your Finances in Real-Time
Our AI-powered systems employ advanced techniques like Anti-Money Laundering (AML) algorithms to safeguard your finances, detecting and preventing fraud, identity theft, and financial crimes in real-time, providing you with peace of mind.
Personalized Lending and Credit Scoring
Credit Made Personal: Fast, Accurate, and Tailored to Your Needs
We democratize credit with accessible digital platforms, combining alternative data and machine learning for faster, accurate assessments and personalized loan approvals, empowering individuals and businesses to achieve financial aspirations efficiently.
Real-Time Risk Assessment
Stay Ahead of Risks: Real-Time Monitoring for a Secure Banking Experience
Our advanced risk assessment capabilities continuously monitor customer transactions and behavior, enabling proactive measures to safeguard your financial interests. Stay ahead of risks with real-time identification and adaptation of risk scores.
AI-Driven Customer Support
Intelligent Support at Your Fingertips: 24/7 Assistance for All Your Banking Needs
We offer unwavering customer service through chatbots and virtual assistants, providing instant and accurate round-the-clock support. Our AI-driven assistance ensures a smooth and hassle-free banking experience.
Join us on this transformative journey as we embrace the digital revolution in banking. Explore our comprehensive solutions that empower you with enhanced security, personalized lending options, real-time risk assessment, and AI-driven customer support. Discover the future of banking and unlock a world of possibilities with our digitally empowered platform.
Fraud Detection Architecture
Our fraud detection and prevention system utilizes artificial intelligence (AI) and machine learning (ML) to identify possible fraud instances before they occur. The system consists of the following key components to identify, mitigate, and prevent fraud.
1. NLP-Based Customizable Rules Engine: All the transactions are screened for potential fraud via this customizable rule engine. A fraud rules engine allows to implement logic to manage fraud and risk on your platform. The rules engine allows the creation and prioritization of rules to be used in managing fraud.
2. AI-Based Fraud Detection: The transaction is again screened via the AI-based supervised engine to identify the fraud and reduce the false alerts. Once the transaction is identified as potential fraud, it is forwarded to a case worker to take the necessary action. The resultant action is used as a feedback mechanism to further harden the system and improve accuracy.
The system also provides actionable dashboards and reports for the organization to evaluate and fine tune the business.
Anti-Money Laundering Architecture
Our Anti-Money Laundering (AML) transaction monitoring solution manages high-risk transactions as they occur, or retrospectively via batch upload, by using a comprehensive and configurable ruleset and AI based on suspicious activity patterns. The system provides the following features:
Outgoing payment details are captured by transaction monitoring and screened via the following AI systems to identify the high risk and suspicious transactions.
Transaction Filtering and Screening: This AI-based component detects potential AML transactions and reduces false alerts. This module in turn uses CRR, Client screening, and onboarding to identify the potential transactions
Event-Driven Review: The transactions are then forwarded to this system, where the AML team conducts event-driven evaluations to detect and analyze the risks that consumers may bear, which might result in repetition and financial losses.
All the details are audited and actionable dashboards and reports are generated for further optimizing the system.
Digital Biometric Onboarding
Digital Biometric Onboarding
Implementing digital biometric onboarding offers numerous quantitative advantages for financial institutions, particularly in risk mitigation and minimizing potential fines. For instance:
- Accuracy and reliability of biometric technologies reduce the risk of identity theft and fraud, resulting in lower financial losses and associated damages.
- Adopting digital biometric onboarding enhances compliance with regulatory frameworks like AML and KYC, reducing the likelihood of fines, penalties, and reputational damage.
- Streamlining operational efficiency through automation leads to faster customer onboarding, reduced staffing requirements, and improved resource allocation, resulting in measurable cost savings and increased productivity.
- Quantitative advantages include risk mitigation, avoidance of fines and penalties, and operational cost savings.
- Embracing digital biometric onboarding helps financial institutions achieve tangible financial benefits, fortify security measures, and become industry leaders in the digital era.
Problem Statement: Signature matching is a time-consuming and error-prone process when done manually. Organizations need a reliable and efficient method for signature extraction and matching to reduce errors and increase productivity.
Our AI-Based Solution: Signature matching is vital in digital banking onboarding, automating verification for KYC compliance, reducing errors, and enhancing efficiency. It prevents fraud, ensures data accuracy, and enables regulatory adherence. Furthermore, it empowers data analysis for fraud detection and customer insights, optimizing decision-making. Integrating signature matching strengthens digital banking operations, security, and customer trust.
Result: Our solution simplifies the process of signature extraction and matching, reducing the time and effort required to perform these tasks manually. By leveraging AI-based technology, we have increased the accuracy and reliability of signature matching, resulting in better outcomes for organizations.
Machine Learning Models: Yolo8, Auto-encoder for Cleaning, and VGG (Visual Geometry Group) Neural Network for Signature Matching.
Problem Statement: Traditional banking processes for account creation, access to the client area, and account handling are often lengthy, cumbersome, and prone to fraud, leading to increased costs and reduced customer satisfaction.
Our AI-Based Solution: CriticalRiver offers a streamlined and secure account creation process with digital onboarding, access to the client area with facial authentication, and account handling with authentication calls. Our technology utilizes AES256 encryption and timestamps to ensure maximum security and reduce fraud to 0. We also provide KYC/AML checks to verify the client’s identity and share it with the relevant authorities.
Result: Our solution has led to significant savings in operating costs, above 50%, while improving customer satisfaction by offering a simple, fast, and intuitive registration process. Additionally, our authentication calls have increased First Call Resolution (FCR) and reduced costs per call. Our technology is available on multiple platforms, including Android, iOS, and the Web, and works on any device.
Machine Learning Models: OpenCV2 Local Binary Patterns Histograms (LBPH) Face Recognizer.
Automated Verification And Validation Of AOF (Account Opening Form) With KYC
Problem Statement: Manual account opening process is time-consuming and prone to errors, making it difficult to extract information from scanned images of different types.
Our AI-Based Solution: CriticalRiver collaborated with its partner to create an AI-powered system that uses Optical Character Recognition (OCR) technology to validate information on KYC documents and match it with data on account opening forms to detect fraud and discrepancies.
Result: Using the AI-powered system, banks can automate their account opening process, reduce manual intervention, save up to 60% in operational expenses, and reinvest the savings into activities that improve their top line. Additionally, the solution helps detect fraudulent activities, improving overall security.
Machine Learning Models: OpenCV2, Local Binary Patterns Histograms (LBPH) Face Recognizer and VGG (Visual Geometry Group) Neural Network for Signature Matching.
Artificial Intelligence In Finance And Mortgage Industry
Problem Statement: The home buying process involves numerous parties and extensive documentation, making it difficult to fully automate the appraisal process. Extracting information from scanned documents with diverse content and handling the volume of data adds to the complexity.
Our AI-Based Solution: We provide the customer with AI-powered solutions that include:
- Information Extraction: Convert scanned documents into standardized MISMO (Mortgage Industry Standards Maintenance Organization) XML format, extracting 1080 distinct data elements from various sources.
- Data Harmonization and Normalization: Utilize AI and NLP algorithms to harmonize and normalize data from different sources for accurate record mapping and analysis.
- AI Risk Score Prediction: Replace 700+ handcrafted rules with a neural network-based AI model to predict risk scores using appraisal data.
- AI Loan Payment Status Prediction: Develop a deep learning model using 4.5 billion loan records to predict home loan payment statuses throughout the loan’s life.
Result: With AI, the company now offers a fully automated solution for banking and mortgage clients, reducing risks and costs.
Machine Learning Models: Camelot & PyPDF2 extract the data from pdf and ANN (Artificial Neural Network), XGB (Extreme Gradient Boosting) classifier for prediction.
Automated Instruments Clearance
Problem Statement: A certain financial institution faces the challenge of processing a significant number of handwritten banking instruments daily, which necessitates a sizable workforce, posing a challenge to automation efforts.
Our AI-Based Solution: The financial institution employs AI to automate the back-office operations, including clearing all banking instruments and reconciling with the general ledger. The solution uses Optical Character Recognition (OCR)/Intelligent Character Recognition (ICR) technology to extract information from scanned images and validate them with the core banking system, reducing manual effort by 30-40%. The financial institution also tracks the progress using data analytics and KPIs.
Result: The implementation of AI has saved banks almost 50% of their operational expenditure, allowing them to invest in improving their top line.
Machine Learning Models: Pytesseract for MICR (Magnetic Ink Character Recognition) Code extraction from cheque and CNN (Convolutional Neural Network) for Handwriting Extraction & Classification.
AI-powered Loan And Risk Management System
Problem Statement: Banks and mortgages are exposed to high risk of loan defaults and NPA’s and initial risk assessment prior to loan sanction due to changing fraud tactics.
Our Solution Based on AI: We offer AI-powered solutions that analyze various customer-related data and detect customers who are likely to fall into a debt trap. The system also has built-in algorithms for Loan Surveillance Risk Assessment for all types of Loans. The system can monitor customer behavior in real-time and flag any unusual patterns or trends indicating potential risk and provide a comprehensive risk management system for loan portfolios, including automated risk assessment and early alerts for potential issues.
Result: Our AI-powered solutions have helped banking and mortgage clients identify high-risk customers, thus allowing taking required mitigations before sanctioning loans the system also addresses risks, reduces costs, and improves overall performance. This solution offers a self-serve platform for identifying potential risks, and risk assessment, while the Risk Monitoring System generates early alerts to prevent Non-Performing Assets. The system can also help banks maintain a healthy loan portfolio and reduce their overall risk exposure.
Machine Learning Models: Random Forest for prediction.
Large Language Models AI-powered Chatbots
Problem Statement: Existing chatbots struggle to provide accurate responses and human-like interactions. Large Language Models (LLMs) can improve customer experience and increase efficiency. Developing AI chatbots powered by LLMs is a challenging task for many businesses. The problem statement is to create a scalable framework for building effective AI chatbots to enhance business operations and user engagement.
Our Solution Based on AI: Introducing LLM-powered chatbots – the ultimate solution for businesses looking to provide exceptional customer experience and increase efficiency. With our cutting-edge framework, businesses can easily build chatbots that can effectively understand and respond to customer queries in a conversational and engaging manner, powered by the latest advancements in Large Language Models. Our LLM-powered chatbots can provide personalized recommendations, answer complex questions, and even perform transactions, all while providing a human-like experience that customers will love.
With our solution, businesses can reduce response times, improve customer satisfaction, and enhance their overall operations. Say goodbye to clunky chatbots and hello to LLM-powered chatbots – the future of customer interactions.
Machine Learning Models: Gpt4all-j/Llama-cpp.
Predictive Digital It Operations And Incident Auto Healing
Problem Statement: Challenged by the need for quick incident data analysis and KPI reporting, an American network test, measurement, and assurance technology company turned to CriticalRiver for an AI-powered solution.
Our Solution Based on AI: CriticalRiver’s AI/ML solution automates data analysis and reporting, providing insightful dashboards for quick access to incident data and KPIs. It streamlines incident categorization, reduces false alarms, predicts upcoming events, and enhances security through advanced machine-learning techniques. Overall, it improves incident management and reduces manual effort for root cause analysis.
Result: Detailed reports and insightful dashboards that empowered the customer to make informed decisions, and a streamlined process that impressed even the most demanding CxOs.
Machine Learning Models: XGB (Extreme Gradient Boosting), Random Forest, and NLP (Natural Language Processing).
We understand the client’s current processes and the opportunities for improvement.
We offer end-to-end pre-packaged models and data pipeline templates (MLOps) to jumpstart the process.
Enhanced Data Processing Capabilities
We have a 12-step data cleansing and transformation IP accelerator with machine learning algorithms.
Our Strategic AI/ML Partnerships and Past Fortune 500 Experience
Our partners have helped a lot of organizations, and our team has learned from past experiences.
Overcoming the Data & Technical Debt Challenge
Discover more about CriticalRiver’s powerful solution, which enables businesses to unlock the full potential of their data, providing valuable insights, and improving predictive models.
Enhanced data processing capabilities: 12-step data cleansing & transformation accelerator with Machine Learning algorithms.
Improved accuracy and speed: End-to-End pre-packaged (MLOps) models and data pipeline templates.
Data Privacy: Our Federated Machine Learning (FML) expertise helps with data privacy, enhanced scalability, and reduced data transfer. FML enables organizations to train machine learning models without the need to move sensitive data outside of their secure environments, thereby reducing the risk of data breaches and cyberattacks.
Reduced costs and increased productivity: By automating data processing and model
training, companies can significantly reduce the time and resources needed for data management. This frees up personnel to focus on other important tasks and can lead to a significant reduction in costs associated with data processing and model development. Refer to this article, for more details.
“ 12-step data cleansing & transformation accelerator with Machine Learning algorithms ”
Azure Test Plans
Google Cloud Platform
Amazon Web Services
What Is Next (Where the World Is Heading) In AI-Enabled Operations?
And how are we preparing proactively?
Cloud Agnostic Plug & Play Packages
Portable, pre-configured AI/ML models that can be easily deployed across different cloud (AWS/Azure) platforms, enabling seamless integration, flexibility, and efficient resource utilization.
Generative AI with ChatGPT Knowledge Portal & Chatbots
Easily and quickly get insights from all the organization’s structured and unstructured data.
Federated Machine Learning
Enables decentralized data training across multiple devices or servers, preserving privacy and reducing data transmission overhead.