A Data Intelligence Cloud for Financial Services Analytics

Financial services companies implementing digital transformation projects to enhance customer experience, operational efficiency, and security are evaluating AI to further impact the value chain, predictability and responsiveness. The rise in cybercrime, new regulations, FinTech disruptions, blockchain adoption and ongoing customer retention issues requires business leader to analyze an avalanche of data to make better real-time decisions.

Being able to understand the hundreds of data points from within the enterprise as well as publicly available data to analyze and model risk, fraud, operations, and customer experience is the prime catalyst for financial services AI transformation projects.

Compound that with the ever changing regulatory issues and compliance requirements and the impact of economic and governmental events and you have a recipe for chaos. The good news is that recent advancements in zero-code generative artificial intelligence (GenAI) has made it possible to develop an intelligent cloud to improve outcomes and optimize financial services analytics in a secure, cost-effective and scalable manner.

What is a data intelligence cloud and why should financial services professionals care?

Modernization of legacy applications has become a “need to have” for financial services organizations looking to maintain their competitive standing and operational profitability. Instead of continuing down the path of proprietary solutions that require dedicated tools and resources, many are now evaluating an data intelligence cloud solution that leverages new advancements in GenAI and reinforcement learning. Simply put, a data intelligence cloud is a cloud computing platform that leverages to power of GenAI to enhance its capabilities and transform data into usable information accessible by the average person.

The impact across the financial service market is staggering according to industry analysts. One example from McKinsey Global Institute projected that “Generative AI has the potential to deliver significant new value to banks – between $200 billion and $340 billion.” And according to the Gartner Group “AI adoption in the finance function is advancing quickly.”

Ultimately financial services professionals are experts in their field and not usually comfortable with the rapid advancements in technology. So, having the ability for a financial services executive to “converse” with a machine using natural language (NLP) to get the analytics they need to make better decisions and ensure fair banking while accurately predicting credit scoring and operational risk by inspecting hundreds of variables instantaneously identifying the potential for risk, fraud, or regulatory violations

Improving outcomes and optimizing financial services analytics

A successful AI transformation/data intelligence cloud project for financial services analytics will empower business leaders to get actionable insights in real-time while maintaining security and privacy and free data analysts to innovate instead of generating reports. Some of the specific use cases include:

• Fraud Management & Anti-Money Laundering: Use GenAI to implement the most expansive and predictive set of fraud models to automatically identify, classify and surface suspicious activities while also examining fair banking activities across all levels of the organization effectively presenting results to all stakeholders.
• Credit Scoring & Risk Management: Use GenAI to reduce fraud losses by scoring 100 percent of all transactions in real time at the POS as well as evaluate alternative strategies for pricing, hedging or transferring credit risk to facilitate regulatory compliance and risk disclosure requirements.
• Customer Retention & Marketing Automation: Use GenAI for analysis of account behavior for modeling an accurate early warning system and execute timely, personalized campaigns that take into account customers' current and future needs to ensure retention and attraction of ideal prospects.
• Operational Risk & Performance Management: Use GenAI to analyze cause-and-effect relationships between KPIs, develop predictive scorecards, create more robust, accurate simulations and scenarios to optimize capital reserves by improving the internal control environment.

The good news is that you won’t have to wait months or even years to realize the benefits of an intelligent cloud for your financial services organization. New developments in open-source, zero-code SaaS platforms mean that legacy system modernization projects can be tackled with a data intelligence cloud that reduces dependencies on proprietary systems and the costs of dedicated tools and resources.

Why wait months when you can have a solution in days or even minutes?

Vendors like UBIX deliver on the promise of a zero-code, highly scalable and flexible cloud architecture that leverages the best-in-class cloud technologies to support modern data workloads, including analytics, AI, and ML. A perfect fit for any AI transformation or intelligent cloud project. With an architecture that is designed to adapt to the varying demands of large financial services enterprises, allowing them to scale up or down based on their specific requirements.

Learning how GenAI and emerging advancements like Reinforcement Learning can deliver on the promise of a data intelligence cloud for financial series analytics has never been easier. Download our free eBook titled “5 Steps to AI Business Transformation Success” to help better understand the nuances of emerging AI concepts and technologies and offer a set of best practices for consideration to ensure digital transformation and business-led AI success. Or if you can spare 22 minutes for a mini–AI Readiness Workshop, you can contact one of our AI experts today.