Accelerating Midsize Financial Institution Business Outcomes with AI Intelligence as a Service
Accelerating Midsize Financial Institution Business Outcomes with AI Intelligence as a Service
Many financial institutions have struggled to efficiently and consistently use AI technologies for strategic and operational purposes. To meet this need, the Aunalytics® Innovation Lab was established to provide deep insights to midsize financial services organizations lacking large AI budgets. This combination of powerful analytics and intelligence services with an experienced data science team allows organizations to gain access to an affordable alternative to HyperCloud-based AI solutions.
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Bridging the Mid-Market Talent Gap for Digital Transformation
Bridging the Mid-Market Talent Gap for Digital Transformation
To achieve business value from data technology investments, mid-market companies need the right technical expertise and talent. Yet many mid-market firms push this onto their IT manager, assuming that since it is technology related, IT has it. This is a mistake because most IT departments do not have time for data analytics. They are busy full time keeping company systems stable and secure, and providing support to your team members. This by necessity results in IT deprioritizing data queries over crucial cybersecurity attack prevention. Business analysts and executives get frustrated waiting for data query results, and the data is stale or the business opportunity has passed by the time query results are in.
But even if your IT team had time for it, it still is a mistake to rely on traditional technology administrators for data analytics success. This is unless your IT department has expertise across a wide range of skill sets, from cloud architecture, database engineering, master data management, data quality, data profiling, and data cleansing. What’s more, your IT manager would need to have command over data integration, data ingestion, data preparation, data security, regulatory compliance, data science, and building pipelines of data ready for executive reporting from multiple cloud and on premises environments.
When you read this laundry list of needs, it becomes clear that most mid-market IT departments lack the specialized experts needed to derive business value from their data. Unlike larger enterprises that have the resources to hire skilled staff for these roles, the mid midsize organization requires another option that provides access to the right tools, resources, and support. One that integrates, enriches and is trained in utilizing AI, machine learning, and predictive analytics to achieve more useful results.
