Fintechs adopt AI to meet specific use cases (KPMG)
The 2023 KPMG survey on AI in financial services found that 87% of financial institutions believe that AI will be essential to their success in the next five years. This is a significant increase from the 73% of respondents who said the same in the 2022 survey.
The survey also found that financial institutions are investing heavily in AI. In 2023, 80% of respondents said they are increasing their investment in AI, compared to 69% in 2022.
The AI Platform Built for Your Industry
Customer Churn Prediction
papAI allows banks to segment their customer base based on various attributes like demographics, transaction history, and customer preferences. This segmentation enables personalized retention strategies for different customer groups.
The platform employs predictive analytics to forecast potential churn by analyzing various factors such as customer engagement, complaints, and account activities. Banks can leverage these predictions to intervene before customers decide to leave.
papAI generates automated action plans based on churn predictions. These plans include recommended actions and strategies to retain at-risk customers
Regulatory and Compliance
papAI provides automated tools for monitoring and ensuring compliance with constantly changing regulations. It can conduct real-time checks on transactions and operations, identifying any potential issues or breaches, thus reducing the risk of non-compliance.
papAI provides transparency and explainability in AI models used for regulatory compliance. Banks can understand how the AI algorithms make compliance decisions and maintain a detailed audit trail of model performance, ensuring they meet regulatory standards for model governance.
Keeping up with ever-evolving regulations is a challenge for banks. papAI offers real-time updates on regulatory changes, helping banks stay informed about the latest compliance requirements and adjusting their processes and models accordingly.
Credit Scoring
papAI offers a wide range of advanced machine learning models designed to assess an individual’s creditworthiness comprehensively. These models analyze various factors such as credit history, income, debt, and more to generate precise credit scores, helping banks make informed lending decisions.
papAI can provide real-time credit assessments, allowing banks to respond quickly to loan applications. It enables banks to automate the credit evaluation process and assess a borrower’s risk profile instantly, resulting in faster loan approvals and a seamless customer experience.
papAI allows banks to tailor credit scoring criteria to their specific needs. It enables banks to define custom credit risk factors and weight them according to their lending policies, ensuring that the credit scoring process aligns with the bank’s unique requirements and business goals.
Predictive Analytics
papAI offers a wide range of advanced machine learning models specifically tailored for investment prediction. These models can analyze historical data, market trends, and various financial indicators to make accurate predictions about potential investment opportunities and risks.
With papAI, banks can perform scenario analysis to understand how different factors and market conditions might impact their investment decisions. This helps banks create more robust investment strategies and make well-informed decisions based on multiple scenarios.
To make timely investment decisions, banks need access to real-time market data. papAI seamlessly integrates with market data sources, providing up-to-the-minute information on stock prices, market indices, and other relevant data. This ensures that investment predictions are based on the most current information.
Import relational databases (postgreSQL, mySQL, Oracle, MicrosoftSQL), upload CVS and Excel files, and insert APIs from a custom Python script.
The AI platform’s agile ETL will speed up massive data transfers to enhance your productivity outputs. The calculation engines are distributed without any configuration on your part.
Create your own analyses and choose from the different vizualization models offered (Statistics, Histograms of numerical and categorical data…). You can also view 2D, 3D and geographical plots.
In papAI, powerful Machine Learning engineering will enable you to swiftly and easily deploy your predictive models throughout your pipelines: Feature Selection, Element Coding & Scaling, and Data Separation.
papAI offers a high degree of explicability of results thanks to its counter factual and feature impact functionality.
Accelerate from Data Collection to AI-Driven Decisions Swiftly
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Real-time Data Processing
papAI can handle vast volumes of financial data in real-time, ensuring that banks can make timely decisions based on the most up-to-date information.
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Customizable AI Models
papAI allows banks to tailor AI models to their specific needs. Whether it's churn prediction, fraud detection, credit scoring, or other tasks, banks can create models that align with their unique business goals and requirements.
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Explainable AI (XAI)
papAI provides transparent and interpretable AI models, allowing banks to understand the reasoning behind AI-driven decisions. This feature is essential for compliance, regulatory reporting, and building trust with stakeholders.
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Scalability
papAI is designed to scale with the evolving needs of banks. Whether a bank is small or large, papAI can grow alongside the organization, ensuring that AI capabilities remain efficient and effective.
AI Implementation with Stepwise Approach to Efficiency
How do we ensure our client's success?
Discover Our Use Cases
Explore our extensive range of use cases to see how papAI can address your specific needs and drive success in your organization.
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AI-powered churn prediction systems have been shown to reduce churn costs by up to 80%.
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