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AI in Banking Industry | Banking AI Solutions | Artificial Intelligence Retail Banking Sector

AI in Banking as a Breakthrough Solution



The common bottlenecks which might slow down your business growth

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Delayed Financial Transactions

Human involvement for financial transactions is a traditional slow moving process.

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Manual Processing Systems

Traditional manual processes are paper-based and lack efficiency, which is compounded by the adherence to inflexible working hours.

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Increased Customer Expectations

Human interaction is not able to keep pace with the increasing demands for customer service.

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Expanding Volumes of Structured and Unstructured

Banks are expected to meaningfully store, analyze and manage huge volumes of data.

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Multiple Banking Locations

Banking is now available in remote and rural areas and system coherency is severely lacking.

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Competitive Pressure

The competition is rising with banks around every corner, with increasing demands for higher levels of service and efficiency

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AI in Banking for Streamlined and Efficient Transactions

Interact and conduct financial tasks with automated and high-powered solutions for AI in the banking industry


Machine Learning for Financial Transactions

Machine Learning (ML) is able to process natural language and incorporate learning that extends itself to faster decision making and more accurate financial transactions. Automated systems are capable of operating with little or no human interaction. From basic banking to complex procedures, AI in the banking industry solutions can create automated systems to provide a speedy and highly effective level of service.

Automated Data Analysis

Data collection, analysis and application can be conducted through automated AI systems at a level of efficiency and speed that is much higher than any physical process. The automation feature for this data is applicable to very high volumes of data that are churned out through a meaningful analysis using predictive technology for AI in the banking sector. Furthermore, suggestions for improved sales and higher revenue generation can be made to customers and bankers alike.

Cognitive-based Solutions

Through the cognitive-based solutions that are embedded in solutions for AI in the banking sector, it is now possible to offer customers with a highly personalized experience at a lower cost. Customized advice and offers provides the bank with a competitive advantage that is significantly attractive to customers, along with reliable suggestions for improvement through pattern identification and risk analysis. These systems pick up on transaction history and can work as a virtual relationship manager.

Fraud Detection

Automated AI systems conduct routine monitoring of account activities, suspicious behavior, pattern establishment, and flagging of irregular activities. This makes fraud detection and risk management more manageable. Additionally, AI in retail banking can greatly benefit from anomaly detection technology due to the high level of fraudulent activities and the subsequent revenue loss involved. Through the monitoring feature of AI, these anomalies are identified before a transaction is processed.

Mobile Banking Applications

Apart from personalized services, AI for retail banking can considerably improve customer recommendation and advice through mobile banking apps that function across multiple devices and networks. It helps customers to track their personal financial transactions through automation of routine tasks, with banking advice that is coherent and backed by volumes of data-related research. The risk of offering inaccurate advice is mitigated when a computer takes over the role.

Contract Intelligence Platform

A could-based platform that can conduct intelligent analysis of finance-related documents and identify meaningful points for actionable suggestions. This drastically cuts down on the number of physical hours required to evaluate these documents, as it is speedily executed through machine learning in seconds. The potential of this technology can be further applied to initial screening of customer documents, demographic gauging for bank-related sales, etc.

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Use Cases

What We Offer?

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Robotic Process Automation

Among our host of banking AI solutions, OSP Labs offers robotic process automation to elevate the operational efficiency of banks and reduce overall costs. This is done through the integration of robots into software systems, such as internet bots, that can automate tasks at a much faster and proficient level than physical involvement. These could be simple tasks, such as banking requests or more complicated procedures, such as audits and formatting requirements. International transfer procedures can also be automated through this software.

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Robotics and Digital Assistants

These assistants are AI robots that are installed into mobile devices to offer high quality banking solutions, by performing tasks that are similar to, but more efficient, than a physical personal assistant. We further empower our robots with an emotional quotient to be able to offer personalized suggestions through the identification of the financial emotions of customers. This is executed through complex social media analytics from related platforms, with an additional feature of judging national and international trends.

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Data Mining and Machine Analysis

At OSP Labs, we use intelligent analysis techniques and advanced data mining to offer banks with solutions to daily operations and predict customer outcomes and likely financial decisions. Furthermore, our intelligent software leverages predictive analysis technology to prevent frauds and alert banks on its likelihood, rather than the delayed reaction of rectification to frauds that have already occurred. The natural language processing capabilities further enhance efficiency to offer customer recommendations.

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