New Tech Prevents Excessive Debt Incursion

Nov 27, 2018 / by Raiha Buchanan

At Instantor we want to contribute to a more inclusive and fair financing market. We do this by making people's financial lives easier and helping organisations to understand their customers’ true financial capacity, using transactional data.

Our client, Lendify – Sweden’s largest marketplace for loans – wrote a great opinion article on how traditional credit assessments need to be updated. How new technology, like our AI credit predictor – Insight – can provide a more accurate and detailed risk analysis for lending organisations and be a force for a healthier lending market. Please enjoy a translated version by us that was originally published in Swedish by Realtid.se in October 2018.

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Topics: Alternative Credit Scoring, Financial Inclusion, Credit scoring, Credit report, Risk

Transforming Lives Through Alternative Credit Scoring

Nov 19, 2018 / by Sarah Kok

For many of the world’s poorest countries, financial inclusion is a big problem. Large numbers of people have trouble just getting a bank account, let alone access to credit – particularly in non-OECD countries like Colombia, Ukraine and Vietnam, just to name a few. 

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Topics: Digitalisation, Finance, Financial Inclusion, Alternative Credit Scoring, Underbanked, Risk

How the SHAP Model can be Used to Answer the Question ‘why’

Nov 5, 2018 / by Helene Stafferöd Westerlund

AI has been gaining popularity in recent years, particularly as it’s been improving in leaps and bounds for a whole range of tasks: from predicting the risk of child abuse in a given family to beating world champion Go players. 

However, one critical problem with using it for decision making in business is that the machine learning models can't explain the predictions they make: a customer might, reasonably, want to know why their cred it card or home loan application was denied. 

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Topics: AI, Risk, Tech, ML, Credit scoring, SHAP values

The Impact of AUC and Gini on Credit Risk Models

Jul 19, 2018 / by Aleksandra Khokhlova

For several years, we at Instantor have helped consumer finance organisations make the most profitable decisions through our digitalised financing processes. We understand that your main challenges are in day-to-day operations: limited loan acceptance, fraud, bad loans, and default, and consequently, a reduced profit. In this article, we will dive into calculating risk to demonstrate how Instantor is helping clients reduce credit losses by a quarter.

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Topics: ML, AI, Credit scoring, Risk

Could your late-night behaviour Impact Your Credit Score?

May 29, 2018 / by Sarah Kok

Using transactional behaviour to calculate your credit score is not a new phenomenon. In fact, in a bid to make credit scoring fairer and more accessible to all, it is one of many alternative methods to traditional credit scores.

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Topics: Credit scoring, Finance, Risk

Ultimate Guide: GDPR Impacts on Credit Ratings

May 11, 2018 / by Raiha Buchanan

The rate of data growth is quite staggering. According to George Lee, CIO at Goldman Sachs, 90% of the world’s data has been created in just the past two years alone. With more and more data available, many agree that stricter regulations are needed to protect the rights of consumers’ personal data. Particularly in light of the recent Facebook data breach, it is important that measures are put in place to protect consumers’ rights as well as clarify how companies can interpret data to ensure these rights are protected.

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Topics: Credit report, Credit scoring, Data, Risk, GDPR

3 Fascinating Alternatives to Traditional Credit Scores

Apr 22, 2018 / by Sarah Kok

Millennials are well known for disrupting the well-established methods of their elders. Are they doing it again with credit ratings?

Assessing creditworthiness through an individual’s credit score has been around for a long time. But for Millennials, this method often doesn’t work because their preference for non-traditional banking solutions, render conventional credit rating methods ineffective.

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Topics: Credit scoring, Lending, Data, Risk