goscore

We help banks to increase creditworthy customers by as much as 19% while reducing default rates by as much as 49%. Banks can not only see «can» consumers repay a loan, but «will» they do that.
Unlike other credit reference agencies, who rely on outdated tax reports, we leverage up-to-date transactional data to build a real-time comprehensive financial profile.

We help commercial banks to improve loan onboarding process and allow consumers to take control over their finance. Our data collection product increase onboarding conversion rate by 50% by using verified and up-to-date financial insights and data.

We also help banks to make better lending decisions, and our technology helps to say yes to 19% more customers and reduce payment arrears and loan default by 49%. We help to find overlooked customers with no sacrifice.

Our service is available for private customers as well as banks. Private customers (users) get the service through the mobile app for free and can:
- Browse their spendings at a glance
- See their credit score, tips & tricks to manage it
- Mange their loans (pay debt faster feature)
- Refinance loan
- Manage deposits, pension and investments

Our customer is a bank who gets more accurate credit scoring, additional insight users’ financial status and our match with banks’ existed products. We basically say which product user will like and can afford in terms of interest rate, credit limit and risk for particular loan (not general risk).

Banks also pay per each case for refinancing. So, when user sign a deal through the app to pay less fees and interest, we get a one-time agent reward.

Real estate (rental market) and eCommerce are also our potential customer segments. We already use our risk assessment algorithm in sprove - solvency verification platform for landlords.

Summarizing, goscore develops a technology could be utilised in various industries and generate the following revenue:
* credit scoring (per check)
* customer profiling (per bank customer)
* marketing, incl. micro-targeting
* up-sell/cross-sell banking products
* deferred payments (eCommerce)
* solvency verification (Rental)

Problem: traditional credit scoring uses old-fashion technology, statistical and outdated data to perform an analysis.
Data used in current credit scoring models can’t reflect on modern consumer profile and show latest changes in habits, income and expenses. E.g. the only indicator for person’s income is tax report which could be up to 2 years old and can’t represent current financial situation.

We use more data sources and utilise consumer data (with their explicit consent, obviously) incl. PSD2 transactions, Mastercard dataset, Google maps and various local data sources (structured data), such as business and other public registers. The next essential step is to use unstructured data, such as LinkedIn profile to analyse your position on the job market and by that predict your income and its stability

- Traditional CRAs, such as Bisnode, SCHUFA, Experian, Equifax
- CS apps, such as Clearscore, Bonify
- New players, such as KrediTech, Kreditz, Credit Kudos
- Some aggregation API providers, e.g. Instantor and Nordigen
- Banks old-fashioned mindset.

- Traditional CRAs, such as Bisnode, SCHUFA, Experian, Equifax who still rely on the models built and slightly improved from 1980s;
- CS apps, such as Clearscore, Bonify who don’t improve CS but present it to the consumers for free and get money from being banks’ agent and push loans to the users;
- New players, such as KrediTech, Kreditz, Credit Kudos who use transactional data only to provide additional insights for banks but don’t calculate and make credit scoring transparent. They also don’t enrich data from alternative sources, such as MasterCard data, public registers nor google.
- Some aggregation API providers, e.g. Instantor and Nordigen, who also use only transactional data too give the score which can’t be reliable on it’s own without additional data about the customer.
- Banks old-fashioned mindset. There are number of challenges we need to overcome to get more banks on board and pilot projects, e.g. legal uncertainty or «we’ll do everything ourselves».

The core product of goscore is a credit scoring technology/engine. It collects data, generates insights, and analyzes it to estimate creditworthiness, willingness to pay, and probability of default. Currently, the engine has multiple connection and has integrations to access the following data:
Basic profile data fr om public registers;
PSD2 data fr om the PSD2 bank aggregator; and
Merchant data from the Mastercard and Google Maps.
Next up is to build connections to collect data directly from the banks (loan repayment data) and LinkedIn (CV and education information).
Our core technology/engine allows us to make multiple value propositions or add-ons for different consumer segments to:
Improve consumer onboarding. Using basic profile data from public registers, this solution helps lenders to onboard customers with a single click instead of filling in multiple forms, reduces a drop-off rate, and brings them more verified data with a single BankID. It’s currently available solution with 1 bank already signed and integrating, another one in the onboarding process and 4 more in the pipeline.
Next step is to add bank transactions (PSD2 data from the bank aggregator) as an additional data source. This allows us to bring even more insights/indicators to lenders. Using only insights, derived from the consumer’s bank transactions, allow lenders to evaluate customers, who can’t get the traditional credit scoring, approve more applications, and reduce default rate.
Predict invoice payments for debt collection companies. Using data collected using our onboarding solution and/or shared with us by debt collection agencies (invoices, repayment transactions, case status history and communication history) we can predict full case repayment in the first 60 days (calculate probability of the payment).
Build a complete financial profile. With bulk access to the public data (compared to the onboarding solution wh ere access is given by an explicit consent fr om individual customers) and authorization from Datatilsynet, goscore can deliver risk indicators and analysis to the customers considering their creditworthiness and perform assessment. We make a portal and integration options wh ere customers can get a complete financial overview of the consumer’s financial status and risk associated with a particular consumer.
Predict consumer’s affordability and default accurately with a human credit score. The most important KPIs for lenders are: conversion rates, application approval rate, and consumer default rate (% of non-performing loans). Our human credit score combined with the onboarding solution give an incredible boost of all these KPIs, e.g. 19% increase in loan approval rate alongside with default rate reduction of 49%. It also could be applied to the consumer segment wh ere a traditional credit score couldn’t be calculated, e.g. for consumers with payment remarks.

Some of the financial forecasts for the next 5 years:
Onboarding: (EUR) 5,000 + 0.2/per transaction
Invoice prediction: 15,000 + 0.5/transaction
Human credit scoring: 75,000 + 1/transaction

2025:
Total revenue: (EUR) 15,586,400
Expenses: 10,564,500
EBITDA: 5,021,900

UNIQUE SELLING PROPOSITION
Goscore brings fair human credit scoring to support informed credit decisions based on the up-to-date financial information.
PRICING & POSITIONING STRATEGY
Positioning statement: goscore is easy-to-integrate, advanced and comprehensive credit scoring for commercial lenders who want to compete and attract new consumers with new products and tailor-made offers.
DISTRIBUTION & SALES
Direct sales (outbound prospecting): our main approach to acquire customers is to make direct sales to the lenders. We build a sales funnel starting from the direct reach out.

- APIs from partners
- develop new value propositions
- customer PoC
- launch invoice prediction in Norway
- marketing campaigns
- local customer support

We're looking for EUR 400,000 with pre-money evaluation at EUR 2,250,000. We're looking for an active investor with network in banking & finance. We offer board seat, maybe chairman seat.

Our 3 main risks are: 

1. Technological, i.e. not feasable or the tech does not work: This is what we are doing the pre-studies for, and we have already gotten great results.  The results show that the technology works and that we can give up to 24% more customers (approved loan applications) while at the same time reduce the default rate by up to 49%. We have also tested several hypotesis internaly to find the one which works the best.

2. Regulatory: We have already applied for the required licenses, and it's just a matter of time before we get these approved.
Through our cluster membership with NCE Finance Innovation we have access to all the regulatory and legal aid we need, primarily through the cluster member PwC.

3. Commercial: We have already reduced this greatly by having signed contracts with partners and future-customers. The Team also has a proven track-record within sales (both B2B and B2C) with more than 12 years experience. 

VIS, NCE Finance Innovation FinTech HUB, Gründerhub, LHoFT Catapult (Luxembourg), Design Terminal (Hungary)

Most Innovative Credit Scoring Solution (Scandinavia)
FinTech Awards
2021

WINNER
Gründerhub, Norway
2020

FINALIST
SAS, Poland
2020

WINNER
Hack for Crisis, EU
2020

TOP100
Sustainability fast track
UK 2020

WINNER
Gründerhub, Bergen
2020

WINNER
Bearing point @ Slush
Finland 2019

FINALIST
Shift Money, Croatia
2019

TOP100
Slush, Finland
2019

FEATURED
by Horizons Ventures
Acceler8 2019

FINALIST
Money 20/20 Europe
2019

FINALIST
Mastercard Startup
Academy 2019