Ataira

Transform Data into Insights with Business Intelligence Consulting

Ataira’s Business Intelligence Consulting services help organizations transform raw data into trusted, actionable insights by combining modern data modeling, KPI design, self-service analytics, and Microsoft-based reporting platforms to support strategic and operational decision-making

Business Intelligence Consulting Services

Ataira helps organizations transform raw data into trusted, actionable insights through Power BI strategy, enterprise data governance, and cloud analytics modernization. We design KPI-driven dashboards, reliable data pipelines, and governance frameworks so leaders can make faster, measurable decisions.

Business Intelligence Consulting services are frequently combined with Data Engineering Services, AI Automation Integration, and Cybersecurity and Compliance to build analytics programs that are secure, scalable, and tightly integrated with operational systems.

Financial Portfolio Analytics Platform Case Study

Enterprise lending performance, profitability, and risk analytics for consumer portfolios

Consumer Lending Performance | Executive Overview

Unified view of loan growth, profitability, and risk across direct and indirect lending channels

Total Consumer Portfolio
$1.85B
+9.8% YoY
Previous: $1.68B
Net Yield on Loans
4.3%
+0.35 pts
Previous: 3.95%
Delinquency Ratio (60+)
0.72%
-0.21 pts
Peer Avg: 1.52%
Net Charge-off Ratio
0.48%
-0.37 pts
Prior peak: 1.39%
Annual Loan Losses
$1.1M
Down from $8.0M
Risk-Adjusted ROA
1.15%
Target: ≥ 1.0%
Profitable Credit Tiers
9 / 10
1 sub-prime tier under review
Portfolio Risk Migration
+3.1%
Previous: +2.5%

Portfolio Yield & Loss Trend

Last 8 Quarters

Risk-Based Pricing

Profitability by Credit Tier

Static Pool Analysis

Cumulative Loss by Origination Year

Risk Ranking Validation

Loss Ratio by Score Tier

Credit Tier Performance Matrix

Profitability vs. Risk across credit segments

Static Pool Margin Heatmap

Credit Tier × Origination Year
*Dashboard simulated to respect customer confidentiality though based on actual project objectives

Customer Background

A $1B+ bank with a large indirect consumer portfolio needed a consolidated view of lending performance across originations, risk segments, and vendor channels. Rising delinquencies and charge-offs had driven annual consumer loan losses above $8M, significantly compressing margins and ROA.

Objectives

The engagement focused on implementing a Lending Performance Management framework that would: (1) quantify portfolio profitability by credit tier using a robust IRR-based model, (2) validate that scorecards and risk models were correctly ranking loss risk, (3) deploy static pool analysis for vintages, vendors, and collateral segments, and (4) support best-practice scorecards and dashboards for executives and examiners.

Approach

  • Profitability Review & IRR Modeling – Built a portfolio profitability model incorporating origination volumes, weighted yields, life-of-loan loss curves, repayment curves, fee income, and funding costs, with IRR and NPV comparison against alternative investments.
  • Static Pool Performance Analytics – Implemented static pool loss and repayment analysis by origination month, year, credit tier, collateral type, vendor, and member type to identify deteriorating vintages and high-risk segments early.
  • Risk Ranking Validation – Used static pool loss experience stratified by score tier to confirm that FICO and pooled risk models were correctly ranking loss risk and to pinpoint anomalies for underwriting and pricing adjustments.
  • Vendor & Channel Scorecards – Deployed vendor management reports and market- intelligence scorecards to compare vendor performance and benchmark the portfolio against peer lenders.

Outcomes

  • Reduced annual comsumer loan losses from over $8M to approximately $1M while maintaining competitive indirect volumes and portfolio growth.
  • Validated and fine-tuned risk-based pricing so that each credit tier covered expected losses and costs, improving risk-adjusted ROA across nine of ten tiers.
  • Demonstrated to regulators that scorecards and risk models were appropriately ranking risk, supported by static-pool-based risk-ranking validation reports.
  • Established a best-practices reporting program with monthly, quarterly, and annual scorecards for originations, performance, static pools, and vendor quality, enabling proactive portfolio steering rather than reactive policy changes.

Performance Analytics Strategy and Roadmap Planning

Ataira Performance Analytics Strategy and Roadmap Planning

Understanding your Current Business Intelligence Posture for Rapid Growth and Performance

Visual analytics with a performant data architecture as a cohesive platform serves as a focal point for many organization's business intelligence strategy. It helps communicate performance-based goals to decision makers, individual contributors, and partners. As your reporting initiative expands, you may have questions about best practices for scaling, security, sharing, deployment, and management. We're here to help you navigate these areas and ensure your PowerBI strategy is successful

Start a conversation with us and our knowledgeable experts to:

  • Gain insights with tailored recommendations on best practices for data quality, data modeling, and calculating essential metrics.
  • Receive guidance on envisioning your business intelligence initiative to encourage adoption and drive positive change.
  • Explore key concepts in creating compelling business intelligence and data analytics reporting as part of your market offerings.
  • Delve into the challenges and opportunities of securing, scaling, and nurturing a robust PowerBI ecosystem for your business.

Business Intelligence Strategy & Roadmap Planning is typically executed alongside our Data Engineering Services, Data Analytics Consulting, and AI Automation Integration offerings to ensure that future-state BI plans reflect real data, automation, and security requirements.

Enterprise Data Governance and Quality Assurance Program

Ataira Enterprise Data Governance and Quality Assurance Program

Building a Trusted, High-Quality Data Foundation for Analytics Growth

High-performing organizations build analytics on a foundation of well-governed, validated, and consistently structured data. A scalable governance program ensures that business intelligence, automation, and predictive analytics are all based on trusted information that supports growth and compliance needs. Our team works with business and technology leaders to define clear expectations for ownership, lineage, and quality.

Partner with us to:

  • Establish enterprise data governance standards aligned with industry frameworks.
  • Define stewardship roles, processes, and data ownership models across domains.
  • Implement automated quality monitoring to detect anomalies and improve reliability.
  • Create a sustainable governance roadmap supporting analytics maturity and regulatory requirements.

Data Governance and Quality Assurance is often paired with our Data Engineering Services, Data Analytics Consulting, and AI Automation Integration to ensure that governance aligns with real-world architecture and analytics use cases.

Analytics Modernization and Cloud Data Architecture Transformation

Ataira Analytics Modernization and Cloud Data Architecture Transformation

Transforming Legacy Reporting into a Scalable, Insight-Driven Analytics Platform

Many organizations rely on fragmented reporting systems and legacy data processes that limit their ability to scale analytics. We help clients modernize their analytics landscape through cloud-native data architectures, metadata-driven processing, and integrated semantic models that empower users across the business.

This offering helps teams:

  • Modernize legacy reporting systems into a unified analytics architecture.
  • Adopt cloud-native storage, compute, and transformation pipelines.
  • Implement semantic models for consistent calculations across business units.
  • Design flexible architectures supporting AI, predictive analytics, and automation workloads.

Analytics Modernization is executed in partnership with our Data Engineering Services and AI Automation Integration practices to ensure future-state readiness and scalable performance.

Predictive Analytics and Machine Learning Enablement for Business Insight

Ataira Predictive Analytics and Machine Learning Enablement for Business Insight

Unlocking Advanced Insights with Predictive Modeling and Machine Intelligence

Organizations that adopt predictive analytics and machine learning gain measurable advantages in forecasting, customer behavior modeling, and operational efficiency. We enable teams with the tools, methods, and strategies needed to safely operationalize ML models within their analytics ecosystem, regardless of technology platform.

Engage with us to:

  • Develop predictive models for sales forecasting, churn detection, and operational planning.
  • Establish repeatable ML pipelines and feature engineering processes.
  • Integrate model outputs into dashboards, workflows, and business decision systems.
  • Build a governance framework for responsible AI and secure model management.

Predictive Analytics Enablement is often combined with our Data Engineering Services, Data Analytics Consulting, and AI Automation Integration offerings to ensure seamless operationalization.

Infographic Development

Visualize your Messaging and Strategy with Custom Infographic Development

Infographic development services transform complex data into visually engaging and easily digestible formats that enhance understanding and decision-making. The attached example, titled "Clinical Practice Gaps in the Delivery of Precision Oncology," illustrates how a well-designed infographic can clearly communicate critical drop-off points in a patient care pathway. By breaking down the journey of NSCLC patients into distinct stages-such as biopsy referral, test ordering, and treatment decision-the infographic highlights where and why patients are lost, using both text and percentage data to emphasize impact.

This approach is especially valuable in healthcare, policy, and research settings where stakeholders must quickly grasp key insights. Infographics like this one use a combination of color, layout, and concise labeling to guide the viewer through a narrative, making it easier to identify bottlenecks or areas for improvement. By visualizing data in a structured and intuitive way, these graphics support more informed discussions and strategic planning among clinicians, administrators, and policymakers.

Unlike static reports or proprietary dashboards, infographics can be embedded directly into web pages, shared across digital platforms, and adapted for presentations or publications. This flexibility ensures that insights are not only accessible but also actionable. Infographic development services help organizations bridge the gap between data and understanding, enabling them to communicate findings with clarity, precision, and visual impact. Would you like help creating a similar infographic for your own data or topic?

Infographic Development is most impactful when it is backed by governed analytics and reliable data models, which is why it is often delivered in tandem with our Data Analytics Consulting, Data Engineering Services, and Cybersecurity and Compliance practices.

Ataira Infographics Development

Frequently Asked Questions

What does a Power BI consulting engagement deliver in the first 30 days?

In the first 30 days you receive five production assets: (1) a documented source-to-report data map, (2) a certified Power BI semantic model with governed measures, (3) 3–5 executive-ready dashboards, (4) workspace and row-level security configuration, (5) a handoff package with DAX patterns and refresh schedules. Your team can publish new reports without re-engineering the model.

How is enterprise data governance implemented for business intelligence?

Governance is implemented through three concrete layers: (1) defined data ownership and stewardship assignments, (2) metadata catalog and lineage documentation, (3) automated data quality and contract checks in pipelines. You receive a governance playbook and audit-ready evidence artifacts.

What ROI should I expect from BI modernization?

ROI is measured using baseline operational metrics: report refresh time, manual reporting hours, query latency, and adoption rates. We deliver an MVP within weeks, publish improvement targets, and provide a tracking dashboard so stakeholders see realized gains over 30–90 days.