Earnings Before Interest, Taxes, Depreciation, and Amortization (“EBITDA”) is a metric used to evaluate a company’s operating performance and how much profit they’re bringing to the bottom line. The economic volatility brought on by COVID-19 has impacted EBITDA across the Financial Services sector. Market leaders are adjusting their digital transformation strategies, focusing on reducing risk and operating costs through advanced data analysis – with the goal of improving bottom line performance. Key questions being addressed include:

What parts of the business represent the greatest opportunity to reclaim EBITDA – cybersecurity, default prediction, compliance penalty reduction?
Do you have the right data today to drive positive change in those areas?
Are the right processes and systems in place to support the business with Machine Learning and AI capabilities?
Are you prepared to support and scale these capabilities as they grow?

Since the pandemic, digital transformation in the relatively risk averse Financial Services industry has accelerated 10 years in the last seven months. Financial Services companies are getting tangible value faster from Machine Learning & Artificial Intelligence, and we’re seeing a distinct operating model shift & massive disruption, which isn’t following any organization’s timeline.

What are some of the leading practices when it comes to reducing time and cost with AI and Machine Learning capabilities?

Cisco ecosystem partner, Delta Bravo AI delivers value from data faster, bringing multiple sources of data together in a single pane of glass for secure advanced analytics, machine learning, and AI deployment. According to CEO Rick Oppedisano, “…Delta Bravo’s solution architecture enables our customers to deploy a secure and compliant data science environment quickly on the infrastructure that works best for them. Our technology significantly reduces the time required to prepare, analyze and model data, a significant advantage in this volatile COVID business climate…”

Predictive modeling and Anomaly Detection are two valuable areas in the Financial Services and Insurance verticals. Strategic considerations include:

What parts of the business have disjointed systems or processes that impact forecasting?
What forecasting models are stale?
Could these models benefit from additional data sources like weather or e-commerce?
What trends and transactions are outliers and represent risk? Could we have seen them coming in advance?

To communicate more effectively with customers, employees and to make decisions faster, Financial Services companies need to deliver real-time analytics and predictive modeling. To reduce time and cost with AI and machine learning capabilities, Delta Bravo AI provides the following:

Fully managed data science platform built for Cisco Hyperflex/Container
Use Kubernetes open source container orchestration to supercharge performance on the compute layer and optimize resource utilization
Ingest data quickly from any source, including databases, applications, and sensors
Faster testing, deployment, integration, and scaling of models
Brings capabilities of open source and third-party technologies under one roof and security model

For business continuity in the next normal, it is critically important now more than ever before for strong leadership and collaboration between IT and business teams, aligning capabilities with growth & cost strategies to drive digital transformation, and focus on specific use cases like detecting transaction anomalies, reducing regulatory risk, and fighting fraud to help customers solve problems right away. Please contact Don Gest to talk further.

To learn more about connecting your organizations and building a network you can trust check out our recent webinar, the FSI home page, or contact sales today.

And don’t forget to read the complete Connected Experiences series to fully understand all that Cisco’s Connected Experiences has to offer your financial institution.

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Original Source: blogs.cisco.com