The digital revolution in mortgages: how technology is changing the Polish loan market?

Main stages of the digital mortgage application process

With the technology available, the mortgage application process can be conducted digitally from start to finish. There are several key stages along the digitisation pathway that significantly contribute to an improvement in the end-user experience:

Preliminary calculation

Customers can use online calculators available on the websites of banks and financial intermediaries to estimate creditworthiness and instalment rates. Some banks offer tools to pre-assess creditworthiness based on the data entered by the customer.

Submission of an online application

Banks enable the submission of a mortgage application via online platforms or mobile apps. Applicants upload digital documents (e.g. income certificate, employment contract, bank statements).

Automated data analysis

Banking systems use algorithms and artificial intelligence for preliminary data verification and risk assessment. Often, data is verified automatically through integration with databases such as BIK (Credit Information Bureau) or ZUS (Social Insurance Institution).

Video verification

Verification of the customer’s identity is done via video conferencing or automated document and facial verification processes.

Signing of the agreement

More and more banks are making it possible to sign a loan agreement using a qualified electronic signature.

Monitoring the status of the application

Customers can keep up to date with the progress of the application process via apps or customer portals.

Instruction for loan activation or tranche release

Customers can conveniently activate the loan or part of it, and upload the necessary documents in the form of scans. After verifying the compliance of the documents, the funds are transferred to the bank account specified in the application.

Key technologies supporting mortgage digitisation

In an era of digital transformation, banks face the challenge of how to combine operational efficiency with high-quality customer service. Mortgage processes, traditionally complex and time-consuming, require a new approach – based on advanced technology. The right selection of tools not only speeds up application processing, but also enhances decision accuracy, minimises the risk of errors and fraud and, most of all, meets the growing expectations of customers.

In the following section of the article, we outline the key technologies that support the digitisation of mortgage processes, highlighting their practical applications and benefits for banks and their customers.

Workflow engine

The workflow engine (process engine) plays a crucial role in the digital mortgage application process. Its implementation enables the automation, standardisation and monitoring of a complex process that involves multiple stages and interactions with different systems and participants.

Low-code platform

Credit products are changing, so it is crucial to provide business employees with tools for easy and fast product configuration. Low-code platforms ensure flexibility to modify the process in response to new regulations or customer needs. It is also possible to personalise the customer experience, for example, by customisation of products or implementation of dynamic forms (e.g. a different layout for different business lines).

The role of AI and machine learning in the digitisation of the mortgage process

As in other business areas, artificial intelligence is widely used in the digital mortgage process. The key areas supported by AI and ML are:

Automation of creditworthiness analysis

• Scoring modelling: ML algorithms analyse a customer’s loan history, income, expenditure and other financial data to quickly assess their creditworthiness.
• Risk prediction: Predictive models assess the risk of loan default using historical and current data.
• Personalisation of offers: AI can tailor loan terms (e.g. interest rate, repayment period) to individual customers’ risk profiles.

Verification of documents

• Text recognition (OCR): AI can automatically read data from documents such as income certificates, employment contracts or bank statements.
• Identity verification: AI technology compares photos from ID cards with the customer’s selfie to confirm identity.
• Automated fraud detection: ML algorithms can identify irregularities in documents, such as forged income certificates.

Improving the decision-making process

• Automated decision-making: AI can analyse customer data in real time and make loan decisions without human intervention.
• Exceptions management: Applications that deviate from the standard rules do not have to be rejected – AI classifies them and passes them on for further review by staff.
• Recommendations: ML algorithms suggest optimal solutions, such as reducing the amount of the loan or extending the repayment period for higher-risk customers.

Improving the customer experience

• Chatbots and virtual assistants: AI handles customer enquiries in real time, assisting with application completion, explaining loan terms and tracking application status.
• Personalisation: Algorithms analyse customer data to provide personalised offers and financial products recommendations.
• Sentiment analysis: AI can analyse the tone and content of customer interactions to better understand their needs and improve service quality.

Optimising operational processes

• Load prediction: AI algorithms anticipate periods of peak submissions, allowing better management of resources.
• Bottleneck reduction: AI’s analysis of processes identifies the steps that cause delays and suggests improvements.
• Operational risk management: AI monitors processes in real time, detecting potential issues before they impact the customer.

Analysis of historical data and trends

• Analysis of market trends: AI analyses macroeconomic data and market trends to adjust the bank’s lending strategies.
• Customer segmentation: ML algorithms categorise customers based on their behaviour, enabling better offer customisation.
• Monitoring the loan portfolio: AI assists in analysing the mortgage loan portfolio by identifying high-risk loans and suggesting remedial actions

Detection and prevention of fraud

• Anomaly analysis: AI algorithms identify suspicious patterns in the data (e.g. unusual transactions, forged documents).
• Behavioural Biometrics: AI analyses how a customer fills in forms (e.g. the time taken to enter data) to detect potential fraud.
• Real-time data verification: AI checks the customer’s data against multiple databases at the same time, such as public and commercial registers.

Open Banking

With PSD2, banks can access a customer’s transaction history from other banks. Direct access to this financial data enables automated verification of customers’ income and expenditure. This allows for a faster and more precise assessment of creditworthiness and the personalisation of offers customised to individual needs.

Automation of the decision-making process reduces processing time, eliminating the need to provide paper documents and minimising the risk of errors. In addition, Open Banking increases transparency and convenience for customers by enabling seamless data sharing. As a result, the application process becomes more efficient, accurate and user-friendly.

E-signature

E-signature supports the digital mortgage process, allowing contracts and documents to be signed remotely without the need to visit a bank branch. This speeds up the finalisation of the process, saving the customer and the bank time. Through regulatory compliance, e-signature ensures full legality and security of transactions, including protection against fraud. It also enables the automation of verification stages, integrating with the bank’s workflow systems. As a result, the process becomes more convenient, environmentally friendly and customised to the needs of modern customers.

Benefits of mortgage process digitisation

The digitisation of mortgage processes is bringing the banking industry tangible benefits that impact both operational efficiency and customer satisfaction. The implementation of advanced technologies, such as workflow engine, AI or Open Banking, is already delivering results for financial institutions that have opted for digital transformation.

According to a McKinsey report, mortgage process automation can reduce application processing time by up to 50%, and reduce operational costs by 30-40%. In addition, Deloitte research shows that 72% of customers prefer banks that offer fully digital solutions.

Digital mortgage – what can banks gain?

• Faster implementation and adaptation to market changes. Thanks to low-code platforms and workflow engine, banks can implement process and product changes within days or weeks, enabling them to respond instantly to new regulations or changing customer needs.
• Increased operational efficiency. Automation of key process stages, such as creditworthiness analysis and document verification, significantly reduces errors and speeds up the processing of applications. Banks that have implemented automated credit decision-making have reported a reduction in application processing time from several days to just a few hours.
• Improving the customer experience. Customers increasingly expect intuitive, convenient and fast processes. Digital solutions, such as e-signature and chatbots, eliminate the need to visit branches and enable full online service. In the NPS survey for Alior Bank customers, 80% of customers showed satisfaction with the clarity and comprehensibility of this form of contact.
• Reducing operating costs. Automating processes allows banks to reduce the costs associated with manual application processing, document verification and exception management. It is estimated that the total cost of a single application processing can be up to 40% lower thanks to digitisation.

Digital mortgage from a customer perspective

Bank customers appreciate the investment in mortgage process digitisation because of:

• Short waiting time for a decision: Automation of verification and analysis stages reduces the waiting time for a credit decision, often to a few hours or days.
• Convenience: Customers can apply online, without the need to visit a branch, and documents can be sent and signed electronically.
• Transparency: Customers have full visibility into their application status at every stage along with clear information on the requirements and loan terms.
• Personalisation: Algorithms analyse the customer’s financial data to customise the offer to their needs and capabilities.
• Time and cost savings: The elimination of paperwork and a simplified process reduce the formalities and stress associated with applying for a loan.

Remote mortgage – what’s next?

The digitisation of the mortgage application process in Poland is developing rapidly, although fully digital solutions are still rare. Banks are offering increasingly automated processes such as remote identity verification, electronic creditworthiness analysis or e-signature.

Customers expect a fast, convenient and transparent process that can be completed online, without the need to visit branches. Banks are focusing on implementing technologies such as Open Banking, e-signature, workflow engine and AI to reduce processing time, increase personalisation of offers and improve user experience.

The future of this market is moving towards full digitisation, greater automation and the integration of solutions to support the remote and secure management of the entire lending process.

Altkom Software. Your partner in digital transformation

At Altkom Software, we specialise in providing cutting-edge technology solutions that support banks in the digitisation of mortgage processes.

With years of experience working with the financial sector and experts in AI, low-code and automation, we help our customers accelerate processes, reduce operational costs and enhance the customer experience.

If your organisation is facing the challenge of digital transformation, we invite you to start a conversation. Together, we will identify your needs, propose the best solutions and guide you through the entire implementation process – from requirements analysis to full implementation.

Choose a partner that understands the specifics of the financial sector and delivers future-ready technology.

Sources:

• McKinsey & Company Report – “Hand in hand with a robot”
• Deloitte Report – “Digital Banking Maturity 2024”
• Polish Bank Association, Centre for Banking Law and Information – “Chatbots and virtual assistants”