Analytics-in-a-Box for Banking is designed as a holistic platform for Retail banking, Financial Reporting, Regulatory Reporting, Data Governance and self-service enabled Analytics.
Using the capabilities of the cloud-native architecture of IBM Cloud Pak for Data platform we deliver a full-featured Data and Analytics solution that combines key capabilities as hybrid data management, unified governance and integration, data science, industry model for Banking and analytics.
Your business lines doesn't trust your DWH, shadow IT is growing, development cycles are too long, deadlines are missed, maintenance costs rise. Sounds familiar?
It is time for you to embrace new modern approach to support the bank in unifying data, ensuring compliance, accelerating digital transformation, in order to better serve customers within a fully managed platform experience.
Customer insights and analytics (CIA) is a Analytical CRM solution with Customer 360 comprehensive view, build by leveraging data from various systems to get a holistic picture of customer financial behaviour. A rich 360-degree view equips banks with powerful capabilities, such as providing more customized experience, relying on meaningful data to make decisions, enabling deeper insights and predictive analytics.
CIA helps bank employees to take a proactive approach and provide better-targeted services to the customers. It is the ultimate tool to treat every customer like a celebrity.
Financial Reporting is one of the most critical challenges facing organizations and particularly banks. This area requires more efforts and resources to produce a thousand reports to feed up with information bank steering committees, shareholders and regulators. Usually, this area is in the priorities of many departments and functions in a bank.
Our Financial Reporting module comes with a flexible industry-standard model and integrated predefined standard reports and KPI's. It combines powerful planning analytics capabilities for what-ifanalysis and forecasting.
Regulatory Reporting serves the needs of compliance with regulatory frameworks throughout the banking organization.
The pressure of the regulations on the financial institutions is considerable and for the purposes of the reporting, its norms are strictly observed. The main purpose of the regulatory reports is to monitor the condition of banks in terms of their stability. А significant amount of work is behind their creation and maintenance, thus, being well-organized and structured in a platform would support the effortful reporting requirements for the banks.
Analytics-in-a-box helps you to operationalize AI and build your Data Science Factory.
It helps you to empower data scientists, developers and analysts to build, run and manage AI models, and optimize decisions anywhere. With Analytics-in-a-box you can unite teams, automate AI lifecycles and speed time to value with real-time insights, risk scoring or next best offer initiatives.
It is built on a data fabric architecture that can optimize access to distributed data and intelligently curate and orchestrate it for self-service delivery to data consumers. Forget about data-lake. With Analytics-in-a-box, you can elevate the value of your enterprise data by providing users access to the right data just in time, regardless of where it is stored.
Analytics-in-a-box is built on top of IBM Cloud Pak for Data - a new kind of data and AI platform that simplifies how you collect, organize and analyze data to enable impactful AI.
Speed time to value with a single platform that integrates data management, data governance & analysis for greater efficiency. Powered by RedHat OpenShift.
Seamlessly build and manage machine-learning models across development and production in a collaborative environment
Efficiently respond to changing regulations with embedded, sophisticated governance capabilities
Achieve the speed and scalability your business needs for today's and tomorrow’s workloads
Redefines your DWH/BI and Data Management strategy. Brings unified solution with a common industry model, data governance and AI infused analytics applications into a single Box.
Industry proven models and data integration patterns have very short implementation cycle. Services can be deployed into production in less than 2 months.
Cloud is the ultimate path. A cloud ready solution will alow natural future growth and utilization of cloud resources and convinience.
A need of an integrated and extensible platform to make data ready for AI is on already on place. Speed client time to value with pre-built intelligent workflows and experiences that operationalize AI in key business domains.
We will help you to:
- Operationalize your data governance strategy
- Identify the right operating model for your culture and organization
- Eliminate common roadblocks to adoption
- Analyze your data governance performance and business impact
- Achieve meaningful, sustainable results aligned to your business objective
Using lightweight integration runtimes to implement a container-based and microservices-aligned integration architecture
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IT COMPASS 2021 is the ninth consecutive edition of our conference, dedicated to the trends in IT
Technology is just an enabler. People are the ones who are getting things done.
A straightforward way to promote greater consistency in the development and application of data and information sources is to have common guidance that teams will adopt and then follow. This guidance, including both standard policies and guidelines, will need to be defined, supported, and evolved over time in a collaborative and open manner.
We are building Data Factories.
We are helping organisations to shift from the slow and bureaucratic strategies of traditional Data Management towards the collaborative, streamlined, and quality-driven agile/lean strategies that focus on enabling others rather than controlling them.
Data governance is essential to an organization’s overall strategy for data management and as part of a complete DataOps practice. Data governance practices provide a holistic approach to managing, improving and leveraging data to help you gain insight and build confidence in business decisions and operations while meeting regulatory requirements.
Modern Data Integration accelerates your projects through automated flow and pipeline creation across distributed data sources. A complete data integration solution delivers data from multiple on-premises and cloud sources to support a business-ready trusted data pipeline for DataOps.
Data Science Factory empowers data scientists, developers and analysts to build, run and manage AI models, and optimize decisions anywhere. Unite teams, automate AI lifecycles and speed time to value with real-time insights, risk scoring or next best offer initiatives.