Analytics-based collection models help banks and NBFCs recover loans more efficiently. A collection model helps a bank or an NBFC identify groups of customers where the collection efforts need to be focused on. Many collection systems even now are just rigid rule-based setups, which only take in limited amounts of data to make decisions and do not change with dynamic factors such as markets, client behaviour, their actions, repaying patterns, etc.… Continue reading
✓ Capturing few of the highlights on few of the areas in analytics basis a report by Gartner on 100 Data and Analytics Predictions Through 2024:
- Core Data and Analytics Predictions – By 2021, organizations that provision an augmented data catalog to data consumers will realize three times faster ROI from their data and analytics investments.
- Big Data Analytics Market is forecast to grow 4.5 times, garnering revenues of $68.09 billion by 2025 from $14.85 billion in 2019, according to Frost & Sullivan research done recently. Deployment of big data analytics is priority for enterprises amid the COVID-19 uncertainty as its use will help them remain competitive while accelerating innovation.
Credit Risk Analytics: Macroeconomic modelling for Bank for PD impact
One of the Banks wanted to predict the impact of Covid scenario on futuristic PIT Probability of Defaults (PD) for their portfolio considering the current environment for this year and subsequent years.… Continue reading
- Many countries in the Middle East, majorly including the UAE, Saudi Arabia, Egypt, and Qatar, among others, are taking substantial steps towards embracing such technologies by augmenting their investment across diverse sectors and bringing effective policies and commitment. As per PwC estimations, the Middle East is expected to add 2 percent of the total global benefits of AI in 2030, equivalent to US$320 billion.
Relevant Text Extraction from PDFs
Data extraction for analysis can be as challenging as it is important to an organization with data available in sources of different sizes and formats. For this very purpose, we can use one of many techniques or multiple methods in combination to extract text and clean it, so as to make it as readable as possible to the end user.… Continue reading
Price Optimisation through Machine Learning for Retail Stores
Price optimisation refers to determining the prices of products/services such that the company can achieve its business objectives. In recent times, there have been major technical advancements in this field with more reliable and faster techniques.… Continue reading
- Infoholic’s market research report on Customer Journey Analytics Market business opportunity, and growth predicts that the global customer journey analytics market will grow at a CAGR of 21.6% during the forecast period. The market for customer journey analytics is driven by increasing demand for offering personalized experiences to customers, understanding the journey from the customer perspective, knowing about the conversion rate, and creating a long-term, healthy, & profitable relationship with customers.
- As per a report by Globe news wire, the Fraud Detection and Prevention Market to Reach USD 110.04 Billion by 2026. The global fraud detection and prevention market size is expected to gain momentum owing to rising need to prevent online frauds and monetary loss across the globe.
In the last predictive analysis series on Covid-19, we had tried to predict the likely active cases in US, India and UK basis learning from Spain and Italy. The predictions turned out to be close to what the actual numbers were.… Continue reading
- Inspite of the current scenario, the surge in demand for data science services in various fields with market researches estimating its potential growth in the near future. According to a market report as per analyticsinsight, the big data market is projected to reach US$103 billion by 2027, up from US$49 billion in 2019.
A Transfer Learning Approach
When we predict any time series data we typically use internal data and predict the future for example when we predict the temperature of a city we use historic temperature of the city and predict the future using a model.… Continue reading