Directory of AI back office automation vendors for banks

Advocate Technologies automates the insurance compliance work commercial real estate lenders perform at origination and through servicing, checking that a borrower's policies meet the lender's requirements and the prescriptive terms of agency loan programmes. Its World Insurance Model reads unstructured and nonuniform policy documents and resolves them into a standardised structure, which drives automated non compliance feedback, waiver generation and portfolio reporting, and also produces the pricing and coverage benchmarks it publishes from a base of 70,000 policies and 7.3 billion dollars in premiums.

Infrrd is a San Jose intelligent document processing company founded in 2015 by chief executive Amit Jnagal, built on deep learning, computer vision and natural language processing rather than templates. Its Titan platform and machine learning character recognition handle semi structured and unstructured documents across more than a thousand document types and twenty two languages, with more than a hundred billion pages processed. Financial services is addressed through separately named products rather than an industry page. Infrrd for Mortgage covers origination, quality control, post close and servicing across five hundred document types, pulling borrower income, assets and liabilities from application forms, employment verifications, payslips and bank statements, running tolerance tests and disclosure comparisons at the point of upload, routing exceptions and sending everything else through to investor delivery, with audit trails, version control and tamper resistant logs for regulators and investors. MortgageCheckai is a loan quality control automation product for pre fund and post close audits, launched with a mortgage compliance specialist. Ally is an agentic workforce built specifically for mortgage operations. Infrrd for Insurance handles carrier forms, claims, medical reports and supporting documentation, with patented list splitting for multi policy and multi collateral documents, validating extracted data against business rules without a template per form. Named a Leader in Gartner's 2026 Magic Quadrant for intelligent document processing and in Everest Group's 2026 assessment. Named customer State National, whose intake spans forms from 2,100 insurance companies. The company also sells into invoice processing, construction and manufacturing.

Nammu21 turns syndicated loan and private credit agreements into structured, machine readable data, deconstructing bespoke documents into interoperable digital identifiers through a proprietary loan language index it calls the NEL Protocol. Financial institutions and credit funds use it to extract key provisions, map the connections between them and build programmatic digital security masters, eliminating manual rekeying across legacy loan operating systems. A public database holds more than five thousand syndicated and bilateral loans drawn from filings, and an agent layer is planned on the same protocol.

Ocrolus turns the documents a borrower submits into decision ready data for lenders, reading bank statements, pay stubs, tax forms and roughly a thousand other document types regardless of format or quality, then producing income calculations, cash flow analytics and fraud signals that feed underwriting. Purpose built for lending since 2016, it analyses around 750,000 credit applications a month across mortgage, small business, consumer and auto finance, delivers into loan origination systems rather than a separate console, and insures its data capture accuracy through the Lloyd's market.

Porters automates the regulated back office processes banks and fintechs still run by hand, launching with account seizures and insolvency coordination alongside chargebacks. These are court driven, time sensitive obligations that generate no revenue, absorb significant staff effort and carry fines when handled late, and the company describes its approach as an AI native outsourcing platform running autonomous but human supervised workflows with compliance safeguards and traceability built in. Its founders came from a European investment infrastructure provider and from consulting, with an applied machine learning doctorate on the technical side. The stated ambition is an autonomous back office capable of running entire services end to end.

Proof, formerly Notarize, binds a verified identity to high value transactions and seals the result so it cannot later be repudiated. Mortgage lenders, title agencies, banks, credit unions and insurers use it for full and hybrid electronic closings, remote online notarization through a network of commissioned notaries available around the clock, and identity assured signing where no notarial act is required. Verification combines message authentication, knowledge based challenges, credential analysis, biometric comparison and third party database checks, with a fraud layer adding deepfake detection and network signals.

Proximitty runs autonomous agents across the commercial loan servicing lifecycle for banks, credit unions and fintechs, covering commercial and industrial, commercial real estate and small business administration lending. Agents request, chase and ingest borrower documents including financial statements, rent rolls, tax returns and debt schedules, parse difficult formats down to blurry scans and handwritten notes, reconcile discrepancies with borrowers directly, spread financials using the institution's own business logic and generate credit memos. A unified layer tracks covenants, closing requirements and borrower obligations, escalating breaches before they become defaults. Its Agent Studio captures the servicing rules, assumptions and edge cases staff carry in their heads and automates them. A governance layer observes and logs every agent action with human review configurable at any step and auditability built for model risk management and examiners.

Titan builds what it calls banking native AI for regulated institutions, on the argument that general purpose models were retrofitted for banking rather than built for it. Underneath sits a banking context layer, a proprietary ontology encoding the products, records, policies and regulatory logic of banking into the platform's foundation, which makes any underlying language model materially better at banking work and strengthens as frontier models improve. On top of it run agents that automate repeatable workflows across compliance, underwriting, risk and operations while humans retain final decisions, reasoning through each step as an experienced bank operator, regulator or legal counsel would. Every interaction is logged, explainable and reviewable so an institution can govern, audit and defend it to examiners. Customers are community, regional and super regional banks, credit unions and regulated fintechs.

Uptiq is a no code agent platform built for regulated financial institutions, deploying pre built or custom agents across application intake, client onboarding, commercial and retail underwriting, credit memo drafting, covenant monitoring, loan servicing and compliance documentation. A proprietary Financial Data Gateway connects the agents to more than 100 data sources spanning core banking, custodial, accounting, payroll, credit bureau and tax systems, and the platform is sold as an overlay on existing systems rather than a replacement. Buyers are banks, credit unions, wealth managers, equipment finance firms and non bank lenders.

Vector ML Analytics gives bank and lender finance teams one platform where financial planning sits alongside asset liability management rather than in a separate system, modelling the balance sheet at loan and deposit instrument level across the full trial balance to produce five year projected statements. Its library runs to more than three hundred models across forty asset classes covering budgeting and forecasting, credit models from scorecards through expected loss and stress testing, interest rate risk sensitivity, liquidity planning, capital adequacy and loan pricing, delivered to banks, non bank lenders and debt funds through a platform and a programmatic interface.