#FindabilitySolves
With Propensity
To Pay Solutions
Powered By AI
AI Driven Propensity To Pay Solutions from Findability Sciences
Application of AI in the collections industry can solve seemingly insurmountable accrual challenges with a noticeable reduction in charge-offs and operating expenses. With a combination of Machine Learning, Computer Vision and Natural Language Processing, we can help clients build an approach based on optimizing personalization and categorizing collection functions. With our proprietary Findability.ai Platform, we can develop streamlined mechanisms for providing swift diagnoses, smarter customer segmentation, highly effective digital-outreach methods, real-time offer generation and effective customer retention strategies.
USING AI TO IMPORVE FINANCIAL COLLECTIONS
Gain useful insights with Mr. Sanjay Deshmukh as he talks to Emerj about the endless possibilities of transforming debt collection strategies across industries for maximum efficiency and Returns on Investment.
SANJAY DESHMUKH
HEAD – GLOBAL PRESALES, COLLECTIONS EXPERT
Sanjay literally lives the term ‘Applying the power of AI’ when it comes to solving complex and consequential business challenges, which also forms a cornerstone of his digital transformation advocacy mantra, #FindabilitySolves!
Global businesses are getting frustrated dealing with a mountain of overdue debt amounting to quarter of a trillion dollars making it a hugely significant business challenge. As a highly experienced Fintech executive, Sanjay uses the predictive and prescriptive power of Findability.ai solutions to deliver significant financial RoIe to global businesses.
Before Findability Sciences, Sanjay served in global senior executive positions at Citi and Oracle. He is alumnus of IIM Bangalore.
INDUSTRIES WE ARE IMPACTING
Healthcare
Our FP-PropensityTM engine drove a 25% improvement in dues collection yield without any incremental staffing cost for a US-based Pharmacy Chain, dispensing ~ USD 3 million worth of cashless prescriptions each month across 9000+ stores
Financial Services
Our Payment Propensity solution delivered 48% ROI for a major debt collection partner in the US as we showcased a 13.26% uplift in collections and ~17% increase in fee revenue on a complex, loyalty-based credit program of a Fortune 500 retail firm.
BPO services
Our Big-Data Analytics powered multi-channel debtor contact strategy delivered ~25% improvement in collecting overdue telecom & utility debt for a leading Canadian Contact Centre company.
Telecom & Utilities
Our AI-powered prediction solution used propensity prediction analytics to identify customers likely to upgrade their plans with an astounding 88% accuracy driving a massive bump in revenue collections for our Fortune 500 telecom client in Japan.
Manufacturing
Our AI-powered prediction engine automated the resource planning process for a market leader in the semiconductor solutions industry. Our solutions saved them millions of dollars as our solutions delivered a 45% increase in planning accuracy.
Software
Our flagship FP-PropensityTM engine expedited a dramatic increase in the prediction accuracy for subscribers likely to renew their subscription for an American, multinational computer software company with millions of customers across several geographies.
OUR FLAGSHIP OFFERINGS
Trusted By Organizations
We Are Findability Sciences
A leading Enterprise AI Company helping businesses worldwide realise the potential of data and become data superpowers. Our award-winning proprietary platform, Findability.ai, combines Machine Learning, Computer Vision and Natural Language Processing to help enterprises accelerate their Data-to-AI Journey, enabling customers build their own IP and data science capability, besides executing strategically to derive real financial Returns on Investment.
What people say about us
Michael BrookerI had an opportunity to work with the team at Findability Sciences, they have a great understanding of how to bridge the technical necessities and challenges of ML and the business thirst for predictive analytics.
Senior VP and CIO at Synaptics
F.A.Q's About Findability's Propensity To Pay Solutions
Extending credit is essential part of doing business for many industries. Past due debt has to be provisioned for, which may in turn become uncollectible or may need to be sold at deep discount resulting in direct hit to profitability. Collections therefore forms an important activity with large teams dedicated to the job receiving close attention from management, auditors, regulators and investors.
Magnitude of debt outstanding in collections in US is in the region of quarter of a trillion dollars making it a hugely significant problem for businesses. There is an entire industry of debt collection agencies which collectively have revenues of $12Bn, employing 250,000 debt collectors.
Healthcare, Retail Financing, Credit Cards, Student Debt, Mortgages, Telecom and Utilities are impacted
The challenge is really how to minimise cost of operations and maximise collections while complying with regulatory requirements and managing customer experience. This is easier said than done.
AI models learn from vast amounts of historical transactions data of each account holder, payment behaviour, call logs and contact information to develop an accurate predictive score of payment propensity. These AI models are capable of retraining frequently by taking latest data and remain up to date. A prescriptive AI solution considers the propensity score and combines it with ageing and balance amount to recommend personalized contact strategy that is optimized to make best use of finite calling capacity. Application of AI based solutions result in uplift in collection ratios by 15-30%.
An AI partner should have capability of not only predictive (what will happen?) solutions but also prescriptive (what to do?) solutions which when combined with his/her own as well as client’s domain expertise that can drive collections outperformance with regard to historical trends. AI partners having rapid model training and retraining ability through automated ML platforms and prescriptive analytical capability and relevant domain experience are an important consideration.
