Loan Processing Automation
Use Cases, Capabilities, Costs
Bringing 18-year expertise in financial software development, ScienceSoft helps banks and lending companies implement seamless loan processing automation.
Loan Processing Automation in a Nutshell
Loan processing automation is aimed to streamline all stages of loan cycle, from risk assessment and decision-making to credit reporting and repayment control.
Automated loan processing software relies on artificial intelligence (AI), robotic process automation (RPA), optical character recognition (OCR), and other advanced techs to eliminate time-consuming and error-prone manual lending tasks.
Loan types that can be automated:
Essential integrations: A customer portal, accounting software, payment gateways, and more.
Implementation time: 10–15+ months for a custom automated loan processing solution.
Development costs: $200K–$1M+, depending on the solution’s complexity.
Annual ROI: ~225%.
Main Use Cases and Benefits of Loan Processing Automation
Borrower risk assessment in minutes rather than days and 100% accurate loan approvals due to AI-powered risk analytics, fraud detection, and loan decisioning.
Loan agreement management
Automated loan agreement creation to drive up to 4x faster loan issuance. AI-based suggestions on the optimal loan prices to maximize profitability.
Loan repayment control
Full visibility of open and paid loans and automated debt collection to achieve up to 300% higher productivity of the loan servicing teams.
Automatically processing >50% of omnichannel borrower inquiries and communicating loan-related details to clients using intelligent chatbots.
100% compliance with the required lending standards and 90%+ faster regulatory reporting due to automated compliance checks.
Key Features of an Automated Loan Processing System
For each loan processing automation project, ScienceSoft creates software with unique functionality tailored to the specific needs of a particular customer. Below, we share a list of features that form the core of any automated loan processing solution.
Automated borrower onboarding and pre-qualification
- Configurable registration forms for borrower onboarding.
- Setting borrower eligibility requirements (minimum monthly income, geographical location, credit history, etc.) based on the internal lending policies.
- Automated data extraction from the documents provided by borrowers and data validation.
- AI-enabled borrower pre-qualification against the pre-set requirements based on the data provided by borrowers and the data available in public data sources (e.g., credit rating platforms).
- Automated borrower categorization by user-defined parameters, e.g., borrower type (a business or an individual), requested loan type, region, etc.
- Geography-based KYC/AML verification.
Task management automation
- Automated assignment of loan processing tasks to the loan officers, risk analysts, and other relevant staff members based on employee availability, loan application value, region, etc.
- Scheduled and ad hoc communications with borrowers.
- Instant messaging for the internal communication among the lending teams.
Automated credit risk assessment
- Automated processing of borrower credit documentation in various formats (PDF, digital image, JSON, XML, etc.).
- Automated assessment of a borrower’s credit risk based on user-defined criteria (loan amount, monthly income amount, income sustainability, and other parameters with pre-assigned weights).
- Automated scoring of a business’ credit risk based on default probability and loss given default models (for commercial loans).
- Automated calculation of consolidated and distributed credit ratings for multi-entity borrowers.
- Flagging the loan applications that require additional borrower information for credit risk scoring.
Collateral management automation
- Automated registration of a borrower’s financial and non-financial assets for secured loans.
- Automated valuation of non-financial collaterals (e.g., real estate, cars, equipment) based on the analysis of available data on their condition and market prices for the assets.
- AI-based risk assessment for various collateral types.
Automated loan underwriting
- Template-based creation of loan approval forms containing the loan application and all necessary borrower data and documents.
- Automated multi-department loan approval workflow.
- Configurable approval hierarchies (based on a loan type, loan amount, borrower location, etc.).
- Automated approval or decline of a loan application based on the user-defined rules.
- AI-based suggestions on the alternative loan terms to propose to the borrower in case of declining the initial loan application.
- Instant communication of the loan-related decision to the borrower (via email, messaging apps, or a customer portal).
- Automated generation and submission of funds transfer requests upon loan approval.
Loan agreement management
- Template-based creation of loan agreements.
- Calculating the due principal and interest/APR amounts for each loan agreement.
- Automatically adding to loan agreements the appropriate covenant and penalty terms for late repayments (based on a loan type, loan amount, borrower’s risk score, etc.)
- Configurable agreement approval and signing workflow.
- Loan agreement status tracking (approved, signed, etc.) for loan officers and a borrower.
Loan repayment control
- Automatically generating invoices on due loan repayments and sending them to borrowers.
- Real-time tracking of disbursed loans and loan repayment status (due, partially repaid, fully repaid).
- Customizable loan repayment calendars.
- Instant payment processing via the connected payment gateways.
- Support for multiple loan repayment methods: bank transfer, card, check, etc.
- Scheduled and ad hoc omnichannel notifications to borrowers about debt collection.
- User-defined rules for payment rescheduling and loan prolongation upon the request from a borrower.
- Alerts to loan officers on overdue loan repayments.
- Automatically imposing penalties on a borrower in case of a missed repayment.
- Automated reconciliation of the received loan repayments.
Loan analytics and reporting
- Calculating essential metrics such as average loan cycle time, average loan value, approval rate, profit per loan, and more.
- Automated reports on the granted loans, borrower risk scores, debt collection progress, loan portfolio performance and risks, revenue and taxes, and more.
- Scheduled submission of loan reports in the compliant format (e.g., Metro2 Format for the US) to the required credit regulators.
- Trend-based forecasting of loan demand and financial gains under lending activities based on the historical data on loan transactions, financial market data projections on exchange and credit rates.
Borrower data management
- Centralized storage of all borrower-related data, such as interaction history and ongoing activities, credit terms.
- Centralized borrower document storage for loan applications, loan agreements, loan repayment invoices, documents proving borrower creditworthiness.
- A search engine with filtering and metadata querying to navigate borrower-related data and documents.
- Compliance with IFRS9, CECL, GLBA, FCRA, FCBA, ECOA, MLA, FDCPA, TILA, Basel III, SOC1 and SOC2, SOX, GDPR and PSD2 (for the EU), other relevant global, country- and industry-specific regulations.
- Comprehensive audit trail for loan-related transactions and user activities.
- AI-powered fraud detection.
- Documents e-signing.
- Data encryption.
- Configurable data retention and deletion policies.
- Multi-factor authentication.
- Role-based access control.
Essential Integrations for Automated Loan Processing Software
Connecting your loan processing solution with the relevant back-office and third-party systems helps speed up loan origination and minimize lending risks. ScienceSoft recommends establishing the following key integrations:
- A customer portal: to process loan applications faster; to instantly communicate loan decisions to borrowers, send invoices and notify them of due repayment dates.
- Credit rating platforms of the selected credit rating bureaus (e.g., Experian, Equifax): for facilitated credit rating checks and credit report submission.
- Payment gateways of banks or independent payment service providers (e.g., Stripe, PayPal): for smooth processing and real-time tracking of loan repayments.
- Bank accounts: for centralized tracking of loan-related transactions, timely transfer of the approved funding amounts to the borrowers, and streamlined reconciliation.
- Accounting software: for accurate recording of loan-related transactions in the general ledger.
- A business intelligence solution: for comprehensive loan analytics and reporting.
How to Achieve High ROI for Loan Processing Automation
Relying on decades-long experience in financial software design and development, ScienceSoft’s consultants defined the main factors that help drive maximum payback from loan processing automation.
To eliminate time-consuming manual workflows and free up the lending teams for high-value tasks.
To ensure accurate decision-making and leverage data-driven forecasting of borrower payment behavior.
Focus on security
To protect your IT system against all types of cyber attacks.
Your loan processing solution needs to stay compliant with the up-to-date financial security standards and legal requirements for credit reporting. To avoid unnecessary headache in the future, make sure your software offers flexibility to smoothly and promptly adopt the newly-emerging regulations.
Costs of Loan Processing Automation
The costs and timelines of implementing custom automated loan processing software vary greatly depending on:
- The number and complexity of functional modules, including AI-powered features.
- The number and complexity of integrations.
- Role-specific requirements for UX and UI.
- Non-functional requirements: security, performance, scalability, availability, etc.
- The sourcing model (full outsourcing, partial outsourcing, or all in-house).
From ScienceSoft’s experience, a custom loan processing automation solution of average complexity requires $200,000–$600,000 in investments, while building a complex system for credit documentation automation and intelligent loan decisioning may cost $1,000,000+.
Want to know the cost of your lending solution?
Financial Outcomes of Loan Processing Automation
Loan processing automation can bring up to 225% ROI in the first year of implementation, driven by:
in operational costs.
in loan origination volume.
When to Choose Custom Loan Processing Automation Software
ScienceSoft recommends building a custom automated loan processing solution in the following cases:
You need a solution to automate specific loan origination workflows, e.g.:
You need software that is compliant with all the required lending regulations, including region-specific standards.
You need a highly secure solution providing advanced capabilities (e.g., intelligent fraud detection).
You need flexible loan processing software that is easy to evolve as your business grows or new legal compliance requirements appear.
You want to avoid costly and effort-consuming integration of the loan automation software and your internal systems.
You want to leverage smart-contract-based loan processing automation.
Loan Processing Automation with ScienceSoft
In financial software development since 2005, ScienceSoft helps established credit services companies and lending startups implement robust loan processing automation.
A Featured Success Story by ScienceSoft
Loan Automation for a US-Based Microfinance Company
ScienceSoft designed and built custom loan management software for a reputable financial services company with 50+ offices across the US. The solution provides robust automation of business-specific lending processes, including:
ScienceSoft is a global IT consulting and software development company headquartered in McKinney, Texas. Since 2005, we design and develop effective lending solutions, including loan processing automation systems. Being ISO 9001- and ISO 27001-certified, we apply a mature quality management system and guarantee that cooperation with us does not pose any risks to our customers’ data security.