Remove Customer Experience Remove Data Remove Operations Remove Security
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A Bank Automation Summit Preview: Key 2023 Banking Automation Trends

Perficient

AI is increasingly being used to automate a variety of tasks in financial services institutions, including customer service, fraud detection, and loan applications. Banks are using AI to analyze large amounts of data, make predictions, and automate complex processes. We’re observing the banking industry’s growing use of RPA.

Trends 474
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Top 6 Trends for the Banking Industry in 2024

Perficient

Banking institutions are responding by integrating advanced technologies, particularly artificial intelligence and data analytics, into their lending operations to enhance efficiency and adaptability. Explore and integrate alternative data sources and innovative scoring models to offer fairer assessments of creditworthiness.

Trends 221
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Trends Shaping the Insurance Industry in 2024

Perficient

Platform Modernization: Enhancing Efficiency Across the Value Chain Organizations are actively embracing artificial intelligence (AI) and cloud technologies to streamline operations and gain insights. Leveraging cloud technology for streamlined operations and enhanced scalability.

Trends 221
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Payments Providers Combat The Conflict Between Security, User Experience

PYMNTS

In financial services, demand for ease of use and security are sky-high, even for business customers. But cloud migrations are often complex, particularly when it comes to remaining compliant with the mounting regulatory initiatives designed to address growing security risks in the financial services arena.

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Fostering FinTech-FI Trust With Data-Driven Security

PYMNTS

Open banking provides opportunities such as upgraded customer convenience and customized financial solutions that can help consumers access bank account details, send payments, manage their budgets and more. Doing so may require tapping into various data sources and integrating with data repositories to gain customer insights.

Security 174
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Customer Data Management Challenges in Financial Services

Perficient

Today, I will dive into the customer data management challenges financial companies might encounter when starting their personalization journey. Data management in any financial services firm is complex. It’s a data-intensive business. To add to this complexity, much of the data is unstructured.

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Kount, Snowflake Team To Offer Customer Data Insights

PYMNTS

1) that it is working with data cloud provider Snowflake to provide enhanced, artificial intelligence- (AI) driven insights into customer behavior, according to an emailed press release. Data on Demand is the key to unlocking huge amounts of both new and existing data from many sources.”.

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