Vikar Technologies

The models do real work in three places: document intelligence that reads and verifies applicant and business documents the moment they arrive, a scoring model that approves qualifying applications straight through, and a generative layer that drafts credit memos and compliance narratives, answers staff questions and runs a guided application for customers.

The workflows for account opening, treasury enrollment, loan closing and core boarding were sold for years as a rules driven platform and would still run without them, so the AI drives core capabilities on a platform that stands on its own. In the first half of 2026 Vikar extended the AI into automatic financial spreading and application prefill across onboarding, compliance, underwriting and portfolio analysis.

The scoring model approves qualifying applications straight through on the bank's own credit policy, tuned to its risk appetite, product type and market, and escalates complex cases to underwriters with a pre built analysis package; in the small business platform auto decisioning is optional, and applications it does not fit go to lenders through a shared view. The thresholds that separate straight through approval from escalation are set per bank and not published.

Extracted data carries confidence scores, exceptions such as missing documents, expired identity documents and income inconsistencies are flagged in real time, and each decision gets an audit ready rationale.

Two transparency mechanisms are published: extracted data arrives with confidence scores and cross document reconciliation, and every scoring decision carries a plain language explanation and an audit ready rationale. No accuracy figure, validation method or mapping to model risk guidance is published for the scoring model, which Vikar says improves continuously from portfolio outcomes.

In treasury and wealth onboarding, document intelligence cross validates extracted ownership, financial and compliance details against external records to catch discrepancies before they reach a banker.

Vikar's own figures, 70 percent faster loan closing, credit memos that drop from six hours to under thirty minutes and compliance narratives in under two minutes, come without a named bank or method. Named clients carry the rest.

Peapack Private Bank and Trust connects its retail, commercial and wealth business lines through Vikar, its chief risk officer says Vikar's solutions were instrumental in developing its automated KYC program, and Vikar describes Peapack's onboarding falling from days to minutes.

Firstrust Bank chose Vikar to replace its commercial loan origination system, Northfield Bank runs commercial origination, underwriting and review on it, Salem Five Bank uses it for specialty lending, and BCB Bank and First Commerce Bank for account opening. As a business, Vikar reports client growth of 30 percent in 2025 and another 33 percent in the first half of 2026.

Vikar says its generative AI puts large language models to work on the bank's data, inside the bank's workflows, and its privacy policy limits personal information processed for a bank to that bank's directions and no other purpose. Whether client data trains any model is not addressed by a boundary statement, retention term or training commitment.

The open point is the scoring model, which improves continuously from portfolio outcomes, with no statement of whether that learning stays within each bank or draws on outcomes across Vikar's clients; BankIQ, by contrast, answers questions about the bank's own data without staff writing queries.

Vikar's privacy policy covers users of its services and online visitors, and for the data a bank's customers provide it draws a line: where Vikar processes personal information on a bank's behalf as its service provider, it does so only as the bank directs and for no other purpose, and the bank's own privacy notice governs. No data processing terms, retention schedule for client data or subprocessor list are public.

Applicants' identity documents, tax returns and bank statements pass through document intelligence and fraud checks inside a platform offered only to financial institutions and their authorized staff.

Vikar displays System and Organization Controls (SOC) Type 1 and SOC Type 2 badges as its security certifications, without naming the report scope, audit period or auditor, and offers no trust portal for requesting the reports. Alongside the badges, every uploaded document is analyzed for tampering, synthetic identities and suspicious patterns and returns a risk score before the application moves on, and FIS ChexSystems screening runs inside account opening.

Vikar states no license, examination or supervisory relationship of its own and serves banks as a service provider. The platform supports the bank's obligations instead: Bank Secrecy Act, KYB and KYC narratives drafted for audit, Office of Foreign Assets Control screening through third party checks in small business lending, periodic due diligence reviews for treasury and wealth clients, and streamlined Home Mortgage Disclosure Act and Community Reinvestment Act reporting.

The scoring model approves credit applications straight through on bureau data, financial ratios, cash flow trends and behavioral signals, which puts AI inside the credit decision, and the small business platform offers the same auto decisioning for qualifying loans. Vikar publishes no fair lending testing, disparate impact analysis or method for adverse action reasons for that model.

What it does publish is the explanation layer and a stated discipline: each decision comes with plain language reasons written to be examiner ready and enforces the bank's own credit policy, and Vikar argues banks should apply AI to specific tasks where it makes a measurable difference rather than everywhere at once.

An applicant declined by the scoring model has no published route to challenge it, and no accuracy commitment or indemnity stands behind the model, so the adverse action duty and its consequences sit with the bank. Each automated decision does carry an audit ready rationale and a plain language explanation, which gives the bank a record to answer a challenge, and Vikar presents every outcome as documented and defensible.

The generative layer runs on large language models Vikar does not name, and no provider is named for the document intelligence or the scoring model. Data partners are named, from Plaid and Persona to FIS ChexSystems, and the 2025 partner build out added credit scoring and decisioning providers, KYC and anti money laundering data providers and fraud and identity verification services, which tells a bank whose data feeds the checks but not whose models read it.

Approved loans board straight through to Jack Henry, FIS and Fiserv core platforms without rekeying; through Jack Henry's Vendor Integration Program Vikar connects to SilverLake, Yellow Hammer and Synergy over jXchange, and it is listed in the Fiserv AppMarket and Q2's Innovation Studio. Pre built connectors and open application programming interfaces reach identity providers, document services and other systems.

Named partners include Plaid for account funding and identity verification, Persona, FIS ChexSystems, QualiFile and BizChex for account opening risk screening, Deluxe for check orders, SWIVEL for new account funding and Onsetto for moving payroll, receivables and payables into new business accounts.

Hosting is undescribed: no provider, cloud region or data residency commitment is named. The platform serves self service, banker directed, joint and full service channels from one system, with a guided application on web and mobile, and Vikar says implementations take months rather than years, with clients adding phases, products and channels after launch.

Every route to a price runs through a demo request, and no price, tier or unit of charge is published for any product. The platform is modular, built to sit beside a bank's existing software or replace its account opening and loan origination stack outright, and Vikar says banks go live in months rather than years. It can also be found in the Fiserv AppMarket and Q2's Innovation Studio.

Community banks and credit unions are the core market, with regional and national banks also named as buyers, and each product line has its own offer: consumer account opening, commercial account opening including complex and international businesses, treasury services, wealth management and commercial lending across small business, Small Business Administration, commercial real estate, commercial and industrial, construction and specialty loans.

Treasury and wealth onboarding carry their own reviews, from risk ratings, wire limits and service tiers to source of wealth checks and enhanced due diligence. The business is US only, with new clients across the country in 2025.