Fintech

Fintech

Empowering Financial Services

At COGITAIT, we specialize in developing advanced AI-driven solutions for the financial services industry. Our work spans a variety of areas, including risk modelling, online decision platforms, and algorithmic trading. We excel in creating alternative variables, extensive data engineering, and deploying sophisticated modelling techniques that drive innovation in lending and insurance.

Disruptive Technology in Finance

We help financial services providers harness cutting-edge technologies, offering flexibility, improved services, and access to underserved markets. Our projects incorporate emerging technologies like blockchain, as well as innovative approaches to credit scoring using alternative data sources, particularly in developing economies.

Big Data and Machine Learning Expertise

Our expertise in big data and machine learning allows us to build stable predictive models that meet the formal demands of the finance industry. Whether dealing with structured or unstructured data, we apply proven methodologies that can easily be adapted to various financial datasets and insurance risk.

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Telecoms

Telecoms

Risk Assessment

COGITAIT leverages advanced data engineering, modelling, and alternative data to enhance risk assessment within the telecom industry. Our solutions improve credit risk profiling for customers with established credit histories and enable accurate credit scoring for those with thin or no credit history. Driving innovation in emerging markets, particularly in regions lacking robust credit registries. Success is easy to see in the millions of credit applications our solution processes every month.

Churn Reduction

Customer churn is a significant concern in the telecommunications industry directly impacting profitability. We leveraged a telecoms customer data to manage voluntary churn and reactivate dormant customer accounts. Using techniques such as weights of evidence, logistic regression, and random forests, we identified customers likely to churn. Alerts were then triggered for these accounts, which were sent to a retention queue for proactive retention efforts.

Data Analytics

In the telecoms market, we harness disruptive technologies to provide flexible, faster services that reach underserved segments. By utilizing alternative data sources, such as mobile phone usage, we create innovative scoring solutions and help drive targeted campaigns to retain and grow the subscriber base. This same technology is used to manage cannibalisation of "own market" by new product launches.

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Healthcare

Healthcare

Improving Health with Data

COGITAIT applies predictive analytics and machine learning to transform healthcare data into actionable insights. From oncology to orthopaedics, our data science solutions are helping to prevent, treat, and cure diseases, improving lives worldwide. Our expertise spans epidemiological and business case modelling, burnout and resilience prediction, and beyond.

Our Work in Healthcare

COGITAIT has delivered impactful projects across the healthcare sector. We’ve modelled and visualized cancer data for a US client to recommend optimal treatment regimens and predicted adverse events in orthopaedic surgeries for patients with mineral bone disease. Additionally, we've contributed to COVID-19 modelling for a multi-national company and developed a pipeline for tuberculosis patient monitoring data from a national database of millions of records.

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Loyalty/CRM

Loyalty/CRM

In today’s competitive landscape, where customer loyalty is increasingly challenged by price sensitivity and competition, businesses must engage with their customers on a more personalised level. At COGITAIT, we offer Campaign as a Service to loyalty-driven industries, including quick service restaurants, retail, hospitality, and more.

Our AI-powered solutions transform customer engagement by utilizing advanced analytics and data-driven insights from customer behaviour and product associations, identifying clusters of customers and products. This helps businesses better understand customer preferences, allowing them to create tailored offerings. The results speak for themselves with significant uptake of offers and increased sales revenue.

Our Data-Driven Digital Marketing Optimization, refines campaign effectiveness by enhancing customer targeting, reducing churn, reactivating dormant customers and closely monitoring performance to ensure optimal results.

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Fintech

Fintech

• Debt Collection Analytics
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  Debt Collection Analytics
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  COGITAIT partnered with a major telecom client to enhance their debt collection strategy through advanced analytics. Faced with the dual challenges of improving collection rates and retaining customers, the client collaborated with COGITAIT to leverage intelligent customer insights.
  The COGITAIT data science team conducted a comprehensive collections diagnostic and supported the client’s efforts in managing delinquent accounts. By employing advanced data wrangling, modelling, and alternative data sources, they optimized Right Party Contact (RPC) strategies, improving contact with delinquent customers and addressing issues like network dormancy. Additionally, they adjusted service packages to align with customers' current affordability profiles.
  This innovative approach not only increased collection rates but also significantly improved customer retention.

  Debt Collection Advanced Analytics

  The COGITAIT data science team undertook a comprehensive collections diagnostic, in addition to supporting the client’s collections team with managing the ‘run down’ book. COGITAIT harnessed the foundational components, Right Party Contact (RPC), gleaned from advanced data wrangling and modelling, as well as the client insights enriched by alternative data sources and application of new variables created from Credit Bureau data. Right Party Contact enables the client to get hold of delinquent customers, overcoming the challenges of contactability and network dormancy, whilst the advanced customer analytics made it possible to adjust the service component of the customer’s package downwards to match their current affordability profile.
  
  This innovative and flexible approach to debt collection analytics simultaneously increases collection, as well as customer retention rates.

• Alternative Data Credit Scoring Expand

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  Traditionally, financial services have relied on credit bureau data to assess credit risk, focusing on past credit activities. In contrast, alternative data, which includes non-credit-related information like habits, preferences, and behavior, offers deeper insights into a customer's character. Importantly, this data must be from sources that cannot be manipulated by the individual. According to Experian, 65% of lenders already use alternative data in their lending decisions.

  Substitute Scorecards

  For a COGITAIT financial services client, traditional credit bureau data proved insufficient, particularly in key portfolios. To address this, COGITAIT developed substitute scorecards using alternative data from purchasing records within the client's data warehouse. By creatively compensating for missing information and analyzing purchasing data, COGITAIT identified attributes with strong predictive power. These insights were used to build new features and predictive models, resulting in scorecards that outperformed those based on traditional credit data.

  Marketing and Compliance

  This alternative data scoring framework will be continually used to inform ethical marketing strategies, mitigate risks like over-indebtedness, and enhance product offerings. Ultimately, the goal is to deepen the understanding of consumers, improve model accuracy, and strengthen compliance efforts.

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Telecoms

Telecoms

• Machine Learning to Predict Churn and Spend Expand

  Machine Learning to Predict Churn and Spend Expand

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  COGITAIT utilized machine learning to develop a predictive model for identifying individuals likely to churn and forecasting customer spending. For a telecom client, COGITAIT leveraged warehoused data to manage voluntary churn by identifying behavioural patterns. Using weights of evidence, logistic regression, and random forests, the team predicted high-risk customers and triggered alerts for proactive retention efforts.

• Spend Prediction Expand

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  Beyond managing churn, the machine learning models enhanced customer profiling, enabling more targeted and relevant product offerings, particularly in the prepaid segment. This approach fosters deeper customer relationships and a better understanding of their needs. The project delivers tangible value from the initial use cases, with plans to further refine and automate the modelling process.

• Cannibalisation in Telecoms Sector Expand

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  The telecommunications industry, while dynamic and competitive, faces the challenge of market cannibalisation, where new products reduce the demand for existing ones, impacting profits. A major telecoms company sought to leverage their extensive data to mitigate this issue.

• Data Wrangling, Analytics, Engineering Expand

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  COGITAIT's data scientists wrangled, analysed, and engineered the client's customer data, scrutinising large volumes of sales data. By examining trends in customer spend, reactivation, and churn behaviour, we developed sophisticated predictive models for targeted campaigns. This approach enables the company to strategically structure product launches to optimize profitability and reduce the impact of market cannibalisation.
  The ongoing project involves operational support for campaign execution, with performance tracking and reporting. COGITAIT has implemented significant system improvements and automated key data pipelines improving efficiency of this function.

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Healthcare

Healthcare

• Health Data Science Expand

  Health Data Science Expand

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  The complexity of Big Data analysis in healthcare arises from integrating diverse data types, such as electronic health records, genomic data, telemedicine, and socio-economic indicators. Traditional analytics tools are often inadequate for this task. Health data science, combining mathematics, statistics, epidemiology, and informatics, addresses these challenges. COGITAIT’s data science team has successfully completed numerous projects in the healthcare sector, from oncology to orthopaedics.

• Non-Communicable and Communicable Diseases Expand

  Non-Communicable and Communicable Diseases Expand

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  COGITAIT has leveraged advances in Big Data analytics to tackle major health challenges. For a US client, we modelled, monitored, and visualized cancer data to recommend optimal treatment regimens. We also developed predictive models for adverse events in orthopaedic procedures related to dismineral disease. In mental health, COGITAIT is collaborating with neuroscientists on an ongoing project. On the infectious disease front, COGITAIT participated in advanced modelling of the COVID-19 pandemic for an international mining company and built a pipeline to process and visualize tuberculosis data for a US client using a national database with millions of records.

• Oncology Data Modelling Expand

  Oncology Data Modelling Expand

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  COGITAIT undertook oncology data modelling for an international client as part of a health sector Big Data project.

  In this project, data was extracted from a large, publicly available inpatient healthcare database in the United States. COGITAIT used this data to model outcomes for breast cancer patients, determining the most probable results based on patient attributes and guiding intervention decisions, such as whether to administer neoadjuvant chemotherapy or proceed with surgery. The study also explored predicting tumor downstaging and the level of lymphovascular invasion after chemotherapy, providing critical insights for personalized treatment plans.

• Advanced Analytics for Orthopaedic Procedures Expand

  Advanced Analytics for Orthopaedic Procedures Expand

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  COGITAIT assisted a US healthcare client by applying advanced analytics to data on dismineral disease, orthopaedic procedures, and adverse events.

  Leveraging their expertise in healthcare analytics, COGITAIT investigated outcomes and risk factors for patients with dismineral diseases undergoing procedures like hip and knee arthroplasty and spinal fusion. Analyzing millions of records from a national database (2008–2014), the team used ICD9 codes to filter relevant data and employed SAS software to organize and analyze the dataset.
  The primary focus was on the incidence of mortality, where COGITAIT identified specific combinations of demographics, mineral deficiencies, and procedures that most closely correlated with post-procedural mortality, providing critical insights into patient risk factors and outcomes.

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Loyalty/CRM

Loyalty/CRM

• LOYALTY: Personalized Customer Campaigns Expand

  LOYALTY: Personalized Customer Campaigns Expand

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  Partnering with one of the world’s largest Quick Service Restaurant organizations, we achieved a 48% increase in revenue, a 38% rise in transaction values, and a 43% boost in purchases per customer.
  
  In today’s competitive landscape, where customer loyalty is constantly tested by price sensitivity and competition, businesses need to connect with customers on a personal level. At COGITAIT, we provide Campaign as a Service to loyalty-driven industries, including QSR, retail, and hospitality.
  
  Our global QSR client approached us to enhance their marketing campaigns' effectiveness. We conducted an extensive segmentation exercise, analysing and modelling data using our proprietary AI and machine learning tools. This involved integrating customer behaviour with historical purchase data to develop two symbiotic models.
  
  The first, a Responder Model, predicted customers' likelihood to make a purchase. The second, a Recommender Model, targeted specific customer segments with tailored offers based on product purchase clusters. Additionally, it re-engaged dormant customers with value-driven offers to reduce churn. These models were combined using an AI algorithm that adjusted in real-time.

  The results speak for themselves

  • Revenue increased by 48%
  • Transaction values grew by 38%
  • Loyalty transactions surged by 73%

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Project Name

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• Client: Southwest
• Category: Website Design

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Fintech

Empowering Financial Services

At COGITAIT, we specialize in developing advanced AI-driven solutions for the financial services industry. Our work spans a variety of areas, including risk modelling, online decision platforms, and algorithmic trading. We excel in creating alternative variables, extensive data engineering, and deploying sophisticated modelling techniques that drive innovation in lending and insurance.

Disruptive Technology

We help financial services providers harness cutting-edge technologies, offering flexibility, improved services, and access to underserved markets. Our projects incorporate emerging technologies like blockchain, as well as innovative approaches to credit scoring using alternative data sources, particularly in developing economies.

Big data and machine learning

Our expertise in big data and machine learning allows us to build stable predictive models that meet the formal demands of the finance industry. Whether dealing with structured or unstructured data, we apply proven methodologies that can easily be adapted to various financial datasets and insurance risk.

Close