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- Demand Forecast
- Price Prediction
- Employee Behavior Forecasting
- Risk Prediction
- Propensity Prediction
- Churn Management
- Chatbot
- Recommendations
- Summary
Demand Forecast
- Our multi-algorithmic, time-series forecasting solutions provide granular forecasts of product demand, quantities, and revenues with an average accuracy of over 90%
- Multiple demand signals are identified as part of the Wide Data framework and analyzed to produce highly accurate forecasts for clients from manufacturing, supply chain, retail, healthcare, hospitality, and financial services.
Success Stories
THE PROBLEM
One of North America’s leading provider of HVAC solutions wanted to optimize inventory planning and predict sales for 250+ geographically dispersed locations.
A vast product portfolio of over 1100 SKUs.
Stock-outs resulted in high warehousing and holding costs.
THE SOLUTION
A custom forecasting solution was developed using machine learning and deep learning algorithms.
They were ensembled to obtain higher accuracy against the traditional time-series forecasting algorithms.
Success Stories
THE PROBLEM
Japan’s leading transportation company wanted to reduce significant costs on transportation fee with accurate demand forecast.
The client wanted to retain only those stores where viable future demand existed.
THE SOLUTION
Using the multi-algorithmic time-series forecasting capabilities of Findability.AI, the following indicators were forecasted:
- 45-day forward forecast for the numbers of packages to be transported between 18 pairs of locations.
- The total count of packages to be transported across Japan.
Price Prediction
- Recommend price points that maximize the likelihood of transaction win rates to optimize revenue without compromising profit margins.
- Machine learning technology from Findability Sciences considers historical revenue, quantity and price points, deal win rates and forecasted demand to recommend ideal price points.
Success Stories
THE PROBLEM
Leading microelectronics component manufacturer wanted to optimize SKU-level price points for selling to trade.
Their price prediction algorithm had unresolved issues (bugs) resulting in long processing times.
THE SOLUTION
We developed a middleware of custom SAP application connectors and SAP BAPI.
Enabled communication between the client’s SAP systems and the Findability.AI layer.
Employee Behavior Forecasting
- Streamline human capital management and develop effective mentorship programs by identifying the key workplace and cognitive factors that influence employee performance.
- Identify employees at the highest risk of churn and implement proactive retention measures.
- Findability Sciences can process unstructured data from emails, social media, and employee feedback forms to identify personality traits and mapping them to churn risk.
Success Stories
THE PROBLEM
Project management is key to meet business challenges with high efficiency.
A leading supplier of mixed signal semiconductors needed help to unify their resources and bridge the gaps between their departments.
THE SOLUTION
Using Findability.AI as the core, we designed an integrated resource planning and forecasting application which was capable of the following:
- Presenting the resource requirement and schedule based on history (without machine learning application/forecast)
- Leveraging machine learning to forecast the resource requirement and the schedule (with historical project completion times)
- Combining user inputs and machine learning to enable scenario planning.
Risk Prediction
- Our AI-powered multi-modeling prediction technology is highly effective for determining the likelihood of risk across industries.
- From predicting the propensity of debtors to default, to identifying fraudulent claims in insurance, to predicting the likelihood of machinery malfunction in manufacturing, our AI technology delivers superior outcomes for risk prediction.
Success Stories
THE PROBLEM
An international airline operating in Western Pacific region and deploying a fleet of 250 aircrafts wanted to reduce costs by now flight engine failure in advance to convert unscheduled maintenance to planned maintenance.
THE SOLUTION
A proprietary self-learning, multi-modeling, predictive AI technology from Findability.AI was used to analyze the sensor data from aircraft.
External variables like meteorological conditions and structural specifications for materials used in aircraft components were factored in to create accurate prediction model.
Propensity Prediction
- Rank and order all the occurrences in a dataset for events such as lead conversion, customer churn, default, or fraud using the AI-powered propensity prediction technology from Findability Sciences.
- Multi-modeling technology accounts for multiple trends within the training datasets to produce highly accurate propensity ranking scores
Success Stories
Findability Sciences’ AI model helped Alliance One achieve a 40% ROI
Alliance one achieved 20-30% year-over-year uplift in collections consistently over a period of two years, resulting in a 40% financial ROI for 2021.Findability Sciences helped them formulate an AI-based propensity score model to prioritize and call the most likely payers first. This partnership resulted in increased revenue for Alliance One and measurable financial impact for their customers.
Success Stories
THE PROBLEM
A global debt collections agency wanted to improve payout rate of overdue invoices for its stores in the US.
The client wanted to improve upon the existing dues collection rate (24%) through a renewed debtor contact strategy.
THE SOLUTION
We proposed an operational strategy of ranking each invoice across a debt prioritization matrix based on the outstanding invoice amount and probability of payout.
A proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI was used for obtaining probability of payout.
Success Stories
THE PROBLEM
Global accounts receivable management company wanted to optimize the collection of overdue balance from loyalty program members.
Around 25000 customers accrue a cumulative debt between 40-45 million USD in overdue payments every year.
THE SOLUTION
A proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI was used to assign a ‘Propensity to Pay’ score to each record in the debt portfolio.
The debt portfolio was divided into 7 ‘age buckets’ defined by the debt collection partner.
Success Stories
THE PROBLEM
Due to increasing competition, it is necessary for telecom carriers to maximize dues recovery as well as expand their subscriber base.
A balance between soft action like sending reminders and hard action like discontinuing the service is important for collection teams.
THE SOLUTION
‘Propensity to Pay’ was calculated using a proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI.
Overdue accounts were divided into deciles based on the decreasing order of ‘Propensity to Pay’. The accounts were also monitored for inter-decile shifts and to detect steep changes in propensity to pay if any.
Success Stories
THE PROBLEM
Defaults in retail loans and resultant charge offs are an important cause of credit costs in banking.
Along with dealing with loan defaults at portfolio level, it is also important to identify the individual loans at higher risk of default to effectively target credit risk mitigation efforts.
THE SOLUTION
A proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI was used to divide the loan records into deciles based on their likelihood to default.
The proprietary algorithm ingested historical data to develop multiple prediction models to account for all possible scenarios in the dataset.
Churn Management
- Develop targeted customer retention strategies by predicting the individual risk of churn.
- Leverage our multi-modeling propensity prediction technology to account for multiple factors such as profile details, satisfaction scores, engagement level, business volume, and industry trends.
- Our powerful, data-driven churn prediction provides the insights needed to re-engage customers based on their risk of churn, and keep them engaged with exact targeting, perfect timing, and redefined messaging.
Success Stories
THE PROBLEM
Canada’s leading provider of protection and wealth products/services wanted to improve its customer engagement strategy.
The company wanted to identify the customers at higher risk of attrition and predict overall customer satisfaction rating for key service parameters across three business units.
THE SOLUTION
A proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI was used to:
- Divide customer records into deciles based on likelihood to churn
- Predict customer satisfaction rating for three measures of customer service quality such as ease of doing business, proactive contact, and problem resolution
Success Stories
THE PROBLEM
In telecom industry, customer behavior is influenced by several external factors like new phone launch, festivals, time of the year etc. making it difficult to predict likelihood of retention.
THE SOLUTION
Findability.AI’s, proprietary self-learning, multi-modeling AI technology predicted customer churn based on CRM information, plan details, usage, and billing.
Findability.AI also analyzed unstructured content for chat bots and emails and accounted for reported malfunctions/defects while predicting churn.
Success Stories
THE PROBLEM
A global multimedia and creativity software company wanted to determine retention propensity for retail consumers who had contacted their call center with intention to cancel subscription.
THE SOLUTION
Customer tenure and product subscription history was analyzed using a self-learning, multi-modeling prediction technology from Findability.AI
The proprietary algorithm ingested historical data to develop multiple prediction models to account for all possible scenarios in the dataset.
Chatbot
- Add interactive lead-generation touchpoints to your digital properties and enable 24X7 customer support with intelligent virtual agents powered by artificial intelligence.
- Our chatbots are capable of true NLP and NLU (Natural Language Processing & Understanding), allowing them to deliver engaging conversation experiences.
- Findability Sciences chatbots can automate up to 30% of query management by handling FAQs and other routine questions. They also process basic service requests and provide multilingual support for better end-customer experiences.
Success Stories
THE PROBLEM
One of the fastest growing insurance firms in India with 121 offices across the country.
The company was losing business opportunities due to growing number of queries and delays in response times.
THE SOLUTION
An interactive AI solution was developed using proprietary cognitive technology from Findability.AI and IBM Watson® Assistant APIs.
An AI powered chatbot ‘Alisha’ runs on natural language processing (NLP) based on conversational AI system.
Recommendations
- Increase upsell, cross-sell, and audience engagement with AI-powered recommender systems from Findability Sciences.
- Stay ahead of the competition by offering personalized customer experiences based on relevant suggestions.
- Leveraging data about past purchases, browsing history and preferences, to generate tailored recommendations which resonate with each customer, increasing the likelihood of a purchase.
Summary
- Our proprietary, AI-powered summarization technology saves significant time and effort on information retrieval from research articles, reports, news, and book chapters.
- Key takeaways are identified by computing the ‘relevance score’ for each sentence based on its contextual relationship with the remaining text.
- Document parsing and keywords analysis are used to extract specific elements such as headers, tables, and diagrams.
- The AI-powered summaries ensure that your content is always accurate, consistent, and of the highest quality. Our technology can be integrated with enterprise software as well as firmware (such as scanners) to create productivity enhancement solutions.
- Our multi-algorithmic, time-series forecasting solutions provide granular forecasts of product demand, quantities, and revenues with an average accuracy of over 90%
- Multiple demand signals are identified as part of the Wide Data framework and analyzed to produce highly accurate forecasts for clients from manufacturing, supply chain, retail, healthcare, hospitality, and financial services.
Success Stories
THE PROBLEM
One of North America’s leading provider of HVAC solutions wanted to optimize inventory planning and predict sales for 250+ geographically dispersed locations.
A vast product portfolio of over 1100 SKUs.
Stock-outs resulted in high warehousing and holding costs.
THE SOLUTION
A custom forecasting solution was developed using machine learning and deep learning algorithms.
They were ensembled to obtain higher accuracy against the traditional time-series forecasting algorithms.
Success Stories
THE PROBLEM
Japan’s leading transportation company wanted to reduce significant costs on transportation fee with accurate demand forecast.
The client wanted to retain only those stores where viable future demand existed.
THE SOLUTION
Using the multi-algorithmic time-series forecasting capabilities of Findability.AI, the following indicators were forecasted:
- 45-day forward forecast for the numbers of packages to be transported between 18 pairs of locations.
- The total count of packages to be transported across Japan.
- Recommend price points that maximize the likelihood of transaction win rates to optimize revenue without compromising profit margins.
- Machine learning technology from Findability Sciences considers historical revenue, quantity and price points, deal win rates and forecasted demand to recommend ideal price points.
Success Stories
THE PROBLEM
Leading microelectronics component manufacturer wanted to optimize SKU-level price points for selling to trade.
Their price prediction algorithm had unresolved issues (bugs) resulting in long processing times.
THE SOLUTION
We developed a middleware of custom SAP application connectors and SAP BAPI.
Enabled communication between the client’s SAP systems and the Findability.AI layer.
- Streamline human capital management and develop effective mentorship programs by identifying the key workplace and cognitive factors that influence employee performance.
- Identify employees at the highest risk of churn and implement proactive retention measures.
- Findability Sciences can process unstructured data from emails, social media, and employee feedback forms to identify personality traits and mapping them to churn risk.
Success Stories
THE PROBLEM
Project management is key to meet business challenges with high efficiency.
A leading supplier of mixed signal semiconductors needed help to unify their resources and bridge the gaps between their departments.
THE SOLUTION
Using Findability.AI as the core, we designed an integrated resource planning and forecasting application which was capable of the following:
- Presenting the resource requirement and schedule based on history (without machine learning application/forecast)
- Leveraging machine learning to forecast the resource requirement and the schedule (with historical project completion times)
- Combining user inputs and machine learning to enable scenario planning.
- Our AI-powered multi-modeling prediction technology is highly effective for determining the likelihood of risk across industries.
- From predicting the propensity of debtors to default, to identifying fraudulent claims in insurance, to predicting the likelihood of machinery malfunction in manufacturing, our AI technology delivers superior outcomes for risk prediction.
Success Stories
THE PROBLEM
An international airline operating in Western Pacific region and deploying a fleet of 250 aircrafts wanted to reduce costs by now flight engine failure in advance to convert unscheduled maintenance to planned maintenance.
THE SOLUTION
A proprietary self-learning, multi-modeling, predictive AI technology from Findability.AI was used to analyze the sensor data from aircraft.
External variables like meteorological conditions and structural specifications for materials used in aircraft components were factored in to create accurate prediction model.
- Rank and order all the occurrences in a dataset for events such as lead conversion, customer churn, default, or fraud using the AI-powered propensity prediction technology from Findability Sciences.
- Multi-modeling technology accounts for multiple trends within the training datasets to produce highly accurate propensity ranking scores
Success Stories
Findability Sciences’ AI model helped Alliance One achieve a 40% ROI
Alliance one achieved 20-30% year-over-year uplift in collections consistently over a period of two years, resulting in a 40% financial ROI for 2021.Findability Sciences helped them formulate an AI-based propensity score model to prioritize and call the most likely payers first. This partnership resulted in increased revenue for Alliance One and measurable financial impact for their customers.
Success Stories
THE PROBLEM
A global debt collections agency wanted to improve payout rate of overdue invoices for its stores in the US.
The client wanted to improve upon the existing dues collection rate (24%) through a renewed debtor contact strategy.
THE SOLUTION
We proposed an operational strategy of ranking each invoice across a debt prioritization matrix based on the outstanding invoice amount and probability of payout.
A proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI was used for obtaining probability of payout.
Success Stories
THE PROBLEM
Global accounts receivable management company wanted to optimize the collection of overdue balance from loyalty program members.
Around 25000 customers accrue a cumulative debt between 40-45 million USD in overdue payments every year.
THE SOLUTION
A proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI was used to assign a ‘Propensity to Pay’ score to each record in the debt portfolio.
The debt portfolio was divided into 7 ‘age buckets’ defined by the debt collection partner.
Success Stories
THE PROBLEM
Due to increasing competition, it is necessary for telecom carriers to maximize dues recovery as well as expand their subscriber base.
A balance between soft action like sending reminders and hard action like discontinuing the service is important for collection teams.
THE SOLUTION
‘Propensity to Pay’ was calculated using a proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI.
Overdue accounts were divided into deciles based on the decreasing order of ‘Propensity to Pay’. The accounts were also monitored for inter-decile shifts and to detect steep changes in propensity to pay if any.
Success Stories
THE PROBLEM
Defaults in retail loans and resultant charge offs are an important cause of credit costs in banking.
Along with dealing with loan defaults at portfolio level, it is also important to identify the individual loans at higher risk of default to effectively target credit risk mitigation efforts.
THE SOLUTION
A proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI was used to divide the loan records into deciles based on their likelihood to default.
The proprietary algorithm ingested historical data to develop multiple prediction models to account for all possible scenarios in the dataset.
- Develop targeted customer retention strategies by predicting the individual risk of churn.
- Leverage our multi-modeling propensity prediction technology to account for multiple factors such as profile details, satisfaction scores, engagement level, business volume, and industry trends.
- Our powerful, data-driven churn prediction provides the insights needed to re-engage customers based on their risk of churn, and keep them engaged with exact targeting, perfect timing, and redefined messaging.
Success Stories
THE PROBLEM
Canada’s leading provider of protection and wealth products/services wanted to improve its customer engagement strategy.
The company wanted to identify the customers at higher risk of attrition and predict overall customer satisfaction rating for key service parameters across three business units.
THE SOLUTION
A proprietary self-learning, multi-modeling automatic predictive technology from FIndability.AI was used to:
- Divide customer records into deciles based on likelihood to churn
- Predict customer satisfaction rating for three measures of customer service quality such as ease of doing business, proactive contact, and problem resolution
Success Stories
THE PROBLEM
In telecom industry, customer behavior is influenced by several external factors like new phone launch, festivals, time of the year etc. making it difficult to predict likelihood of retention.
THE SOLUTION
Findability.AI’s, proprietary self-learning, multi-modeling AI technology predicted customer churn based on CRM information, plan details, usage, and billing.
Findability.AI also analyzed unstructured content for chat bots and emails and accounted for reported malfunctions/defects while predicting churn.
Success Stories
THE PROBLEM
A global multimedia and creativity software company wanted to determine retention propensity for retail consumers who had contacted their call center with intention to cancel subscription.
THE SOLUTION
Customer tenure and product subscription history was analyzed using a self-learning, multi-modeling prediction technology from Findability.AI
The proprietary algorithm ingested historical data to develop multiple prediction models to account for all possible scenarios in the dataset.
- Add interactive lead-generation touchpoints to your digital properties and enable 24X7 customer support with intelligent virtual agents powered by artificial intelligence.
- Our chatbots are capable of true NLP and NLU (Natural Language Processing & Understanding), allowing them to deliver engaging conversation experiences.
- Findability Sciences chatbots can automate up to 30% of query management by handling FAQs and other routine questions. They also process basic service requests and provide multilingual support for better end-customer experiences.
Success Stories
THE PROBLEM
One of the fastest growing insurance firms in India with 121 offices across the country.
The company was losing business opportunities due to growing number of queries and delays in response times.
THE SOLUTION
An interactive AI solution was developed using proprietary cognitive technology from Findability.AI and IBM Watson® Assistant APIs.
An AI powered chatbot ‘Alisha’ runs on natural language processing (NLP) based on conversational AI system.
- Increase upsell, cross-sell, and audience engagement with AI-powered recommender systems from Findability Sciences.
- Stay ahead of the competition by offering personalized customer experiences based on relevant suggestions.
- Leveraging data about past purchases, browsing history and preferences, to generate tailored recommendations which resonate with each customer, increasing the likelihood of a purchase.
- Our proprietary, AI-powered summarization technology saves significant time and effort on information retrieval from research articles, reports, news, and book chapters.
- Key takeaways are identified by computing the ‘relevance score’ for each sentence based on its contextual relationship with the remaining text.
- Document parsing and keywords analysis are used to extract specific elements such as headers, tables, and diagrams.
- The AI-powered summaries ensure that your content is always accurate, consistent, and of the highest quality. Our technology can be integrated with enterprise software as well as firmware (such as scanners) to create productivity enhancement solutions.