How AI Is Helping Financial Services Companies in Lincoln Cut Costs and Improve Efficiency

For Lincoln, Nebraska financial services, AI is no longer theoretical - proven pilots show how explainable, human-in-the-loop models can cut manual work, surface the highest‑impact claims and redirect staff to client-facing tasks: Lincoln Financial Group expanded its partnership with EvolutionIQ to analyze claims data and improve outcomes, helping its Group Protection claimants achieve a 91% satisfaction rate in 2023 (Lincoln Financial and EvolutionIQ partnership press release); cloud-first data platforms have delivered richer, faster analytics for decision-makers (Lincoln Financial AWS data platform case study).

Practical upskilling matters here - local teams can learn prompt design, tool selection and workflow integration through a targeted program like Nucamp's AI Essentials for Work bootcamp, turning vendor proofs-of-concept into measurable operational savings and faster claimant resolutions.

Attribute	Information
Description	Gain practical AI skills for any workplace; learn tools, prompt writing, and apply AI across business functions
Length	15 Weeks
Cost	$3,582 early bird; $3,942 afterwards; 18 monthly payments
Syllabus	AI Essentials for Work syllabus and course details
Registration	Register for the AI Essentials for Work bootcamp

“We are focused on investing in innovations and the latest capabilities to drive the best claim outcomes for our customers. Partnering with a technology leader in this space is a part of that investment and has quickly advanced our ability to provide claimants with even better support and resources for their recovery and to return to work. Implementing this new technology helps our claims specialists efficiently focus on the right claims at the right time - all so that we can make the best determinations for our claimants.” - Christen White, SVP, Lincoln Financial Group Protection Claims and Operations

Local banks and credit unions in Lincoln can deploy AI across predictable, high‑value workflows: train Lincoln‑based AI agents to automate exception handling and loan servicing tasks (see AI agent development services in Lincoln at https://mmcgbl.com/ai-agent-development-company-lincoln/), use document‑understanding and report‑Q&A to turn hours of manual review into minutes (index internal reports and client files for on‑demand answers), and layer real‑time transaction monitoring and anomaly detection to strengthen fraud and AML controls while keeping exam trails auditable - a critical point given the Nebraska Department of Banking and Finance guidance on AI‑enabled investment fraud (guidance available at https://makecentsmakesense.nebraska.gov/artificial-intelligence-and-investment-fraud).

Complementing software and vendors, Lincoln's growing AI ecosystem - including the new UNL Scott Data AI makerspace with access to eight NVIDIA H100 GPUs (details at https://news.unl.edu/article/scott-data-nebraska-engineering-partner-on-new-ai-makerspace) - makes local model training, secure testing and workforce upskilling practical for regional institutions that need both speed and explainability.

The result: fewer repetitive errors, faster customer answers, and redeployed staff time to advisory work that builds relationships rather than chases paperwork.

Use case	Immediate benefit
AI agents / automation	Reduce manual exceptions and processing time
Document Q&A & summarization	Prepare reports and meeting briefs in minutes
Fraud/AML monitoring	Faster detection with auditable alerts
Local model training / upskilling	Secure, explainable models and onshore talent

“The intent with our partnership with the College of Engineering is to have a dedicated server of eight GPUs at Scott Data that will provide a powerful level of computing access and expertise,” Moreano said.

Chatbots and virtual assistants can shave minutes or hours off routine banking tasks - balance checks, payments, address changes - and deliver 24/7 responses that cut contact‑center costs, but regulators warn Lincoln financial teams to pair automation with clear escalation paths and language support: the CFPB's June 2023 analysis shows roughly 37% of Americans interacted with bank chatbots in 2022 and highlights failures on complex disputes, limited‑English customers, and inaccurate outputs that can trigger legal risk (CFPB June 2023 report on chatbots in consumer finance).

Local deployments should prioritize auditable decision trails, human‑in‑the‑loop escalation, and testing for dispute handling and accessibility, because large banks already use assistants at scale (Bank of America's Erica handled hundreds of millions of inquiries) and missteps have drawn media and regulator scrutiny (News coverage of CFPB chatbot concerns and bank automation scrutiny), a reminder that automation's “so what?” is preserving trust while cutting cost.

Metric	Figure (source)
U.S. chatbot interactions (2022)	~98 million users (~37%) - CFPB
Projected users (2026)	110.9 million - CFPB
Bank of America's Erica (2022)	32 million customers; ~1 billion interactions - CFPB

“If firms poorly deploy these services, there's a lot of risk for widespread customer harm.” - Rohit Chopra, CFPB

Lincoln firms can turn slow, paper‑heavy back offices into low‑cost, auditable engines by combining AI‑powered document understanding with RPA‑style workflow automation: intelligent capture and validation (Datamatics' TruCap+ and TruBot) scaled to high volume can process hundreds of thousands of invoices - Datamatics reports automating 140,000 invoices annually with a ~25% efficiency gain - while AP platforms show real examples of >80% reductions in per‑invoice processing time for mid‑market organizations (Datamatics TruCap+ and TruBot invoice automation case study, Ramp accounts payable automation case studies).

Local legal and compliance teams can likewise use searchable, indexed repositories and AI‑assisted review to cut discovery time and ensure audit trails; firms that shifted to cloud document platforms during COVID‑era remote work reported continuous operations and faster approvals (Laserfiche cloud document platform case studies).

So what: automating routine approvals and invoice matching not only trims processing cost but frees small Lincoln finance teams to spend hours each week on cash‑flow forecasting, vendor negotiation and customer service instead of keying data into spreadsheets.

Outcome	Source / Figure
Invoices automated	140,000/year - Datamatics case study
Efficiency gain	~25% improvement - Datamatics
AP processing time reduction	>80% faster in Ramp case study (REVA)

“There's never been an issue with payment. It's 100% perfection. With Ramp, we reconcile every couple of days. By the fourth or fifth of the month, Ramp is reconciled and closed.” - Seth Miller, Controller, REVA (Ramp case study)

Lincoln-area banks and credit unions can tighten fraud detection and AML controls by blending behavioral AI, real‑time transaction scoring, and human review - tools that spot deepfakes, voice‑cloning and hyper‑convincing AI phishing the Nebraska Department of Banking and Finance warns are rising threats (Nebraska Department of Banking and Finance guidance on AI and investment fraud); local lessons are stark: a multi‑year loan‑fraud scheme that prompted a guilty plea in mid‑2025 involved more than $45 million in credit requests across regional lenders, showing how fast losses can cascade when fraud outpaces detection (Marshbanks loan-fraud case guilty plea coverage).

Practical steps for Lincoln teams include deploying anomaly detection tuned to customer baselines, instrumenting explainable alerts so investigators see the “why,” and automating low‑value reviews so compliance officers focus on true positives - an approach the ABA recommends when integrating AI into compliance programs (American Bankers Association guidance on harnessing AI for compliance).

The payoff: faster investigations, fewer false positives, and an auditable trail that speeds exam responses and reduces legal risk for community institutions.

Institution / Case	Measured benefit
HSBC (case)	2×–4× detection increase; ~60% fewer false positives
JPMorgan Chase (case)	Significant decline in fraud; ~20% reduction in false positives
DBS (case)	~90% reduction in false positives; 60% detection improvement; 75% faster investigations

“AI doesn't make the risk decision but helps our team see the more critical and pertinent details while eliminating low value, non-value-added noise that consumes capacity.” - William B. Peek, quoted in ABA coverage

Investment research and portfolio management in Lincoln are becoming faster and more evidence‑driven as generative AI turns long, manual workflows - earnings calls, broker reports, ESG screening - into instant, cited summaries and alerts: purpose‑built platforms like AlphaSense generative AI for investment research index hundreds of millions of documents so analysts spend time on conviction, not document hunting; local academic and infrastructure investments - notably Google's $250,000 gift to the University of Nebraska for AI research and its $930M Nebraska data‑center expansion - create nearer‑term access to talent and cloud capacity for secure model testing; and Lincoln advisors such as the Forbes‑recognized UBS Summit Wealth Management team (office: 8415 Maddox Drive, Lincoln) can combine those AI outputs with client knowledge to speed due diligence, surface ESG and risk anomalies earlier, and free portfolio managers to focus on strategy rather than data collection.

Resource	Local relevance / fact
AlphaSense	Generative AI search & Smart Summaries over 500M+ documents
University of Nebraska / Google	$250,000 gift to UNL AI research; $930M regional data‑center investment
Summit Wealth Management (UBS)	Lincoln office: 8415 Maddox Drive; Forbes‑recognized advisory team

“Their generous gift underscores our shared commitment to harnessing the power of artificial intelligence, ensuring we remain at the forefront of research, teaching and public engagement.” - Dr. Jeffrey P. Gold

Lincoln-area financial institutions should treat AI as both a force-multiplier and a new attack surface: recent industry analysis highlights consolidation in MSSPs/MDR and rapid growth in IAM and zero‑trust controls - areas that deliver scalable, AI‑driven detection and automated triage - while regulators and insurers increasingly demand documented, risk‑based controls to qualify for coverage (Lincoln International Cyber Roadmap 2025 - MSSP, MDR & IAM trends).

Practical steps for Lincoln banks and credit unions include adopting zero‑trust identity controls, instrumenting explainable AI alerting that surfaces “why” an event was flagged, and tightening third‑party oversight for vendors that host customer data; the New York Department of Financial Services guidance underscores this approach and even mandates stronger access controls such as MFA by November 2025, a concrete deadline that should drive contract and patching priorities (NYDFS and AI cybersecurity risk guidance).

Because systemic scenarios can cascade across clearing, payments and cloud providers, stress testing and coordinated public‑private information sharing remain essential - these measures reduce detection time, lower false positives, and can materially improve insurer terms if documented and tested (Carnegie Endowment systemic cyber risk scenarios for the financial system), so the “so what” is clear: implement layered, auditable AI defenses now or face longer investigations, higher premiums, and slower recovery when incidents hit.

Priority	Action
Identity & Zero Trust	Deploy IAM/PAM, least‑privilege access, and MFA
AI-driven Detection & Response	Integrate MDR/MSSP/XDR with explainable alerting and automated triage
Risk-based Governance	Annual AI risk assessments, third‑party oversight, tabletop tests to satisfy regulators/insurers

“Combining market intelligence and ideation of creative solutions, with the nuances of hands-on deal making, inspires my work and allows me to develop close client relationships.” - Fredrik Bolander

Lincoln financial teams should adopt AI as a business transformation program, not a stack of point tools: appoint a dedicated adoption lead (see Lincoln Financial AI Enablement & Adoption Lead job description) to prioritize use cases, manage a demand roadmap, and track investment performance with clear KPIs and ROI dashboards (Lincoln Financial AI Enablement & Adoption Lead job description); start with short, high‑value pilots in a 3–6 month foundation phase, scale proven pilots in sequence, and embed GenAI into transformation efforts as recommended by strategic finance guidance to lift returns above the current median (~10% ROI) reported by industry analysts (BCG report: How finance leaders can get ROI from AI).

A practical roadmap - foundation, expansion, maturation - aligns governance, data readiness and training so teams convert automation into measurable time savings and reinvested capacity (Thomson Reuters estimates AI can save about 5 hours/week per professional).

The “so what”: a small, well‑measured pilot plus an accountable owner turns vendor proofs into recurring efficiency gains and auditable value, making it easier for Lincoln institutions to show exam-ready controls and secure favorable insurer and regulator outcomes (AI roadmap guide for mid-size financial services firms).

Phase	Duration	Primary KPI
Foundation	3–6 months	Pilot ROI, data readiness, governance in place
Expansion	6–12 months	Number of scaled use cases, measurable business impact
Maturation	12–24 months	AI embedded in core workflows, sustained ROI

Lincoln financial institutions must navigate a shifting patchwork of state action, legislative debate and institutional guidance: lawmakers have repeatedly studied AI's risks for elections and political advertising (see the Nebraska Examiner overview of the Legislature's probe: Nebraska Examiner overview of the Legislature's AI probe), while a formally introduced bill to regulate AI in political ads (LB1203) was heard but ultimately marked “indefinitely postponed” on April 18, 2024 (Nebraska Legislature LB1203 bill page).

At the same time, Governor Pillen signed targeted protections - LB 172 (criminalizing AI-generated child sexual abuse material) and LB 371 (civil liability for sharing nonconsensual AI intimate images) - which passed with strong margins and are set to take effect in early September, signaling concrete legal risk for anything that uses or disseminates synthetic likenesses (Coverage of Governor Pillen and Nebraska's recent AI laws).

The practical takeaway for Lincoln banks and credit unions: embed human‑in‑the‑loop review, explicit disclosure and tighter vendor contracts now, because state enforcement and institution-level guidelines (UNL's R&I AI best practices) are converging on privacy, child‑safety and consent requirements that can create immediate compliance and reputational exposures if ignored.

Action	Status	Effective / Note
LB 172 - prohibit AI‑generated child CSAM	Passed as part of LB 383	Signed; effective early September
LB 371 - civil liability for nonconsensual AI intimate images	Passed 49‑0	Signed; effective early September
LB1203 - regulate AI in political ads	Indefinitely postponed	Hearing held; depends on other states' laws

“I think it runs afoul of the First Amendment,” - State Sen. Danielle Conrad

Measure AI success in Lincoln by tracking a short list of tied-to-the-bottom-line metrics: manager hours reclaimed (many Lincoln retailers report managers spending 5–10 hours weekly on manual scheduling before automation), labor‑cost reduction (smart scheduling typically trims 5–15% of labor spend), speed to ROI (local pilots often pay back in 3–6 months with combined savings of $1,000–$2,500 per employee annually), and higher‑level outcomes like customer satisfaction and schedule adherence; practical calculators and examples - see Lincoln scheduling time‑savings guidance and SMB AI ROI frameworks - help convert hours saved into dollars and percent gains (Lincoln scheduling time savings (MyShyft case study), AI ROI for SMBs (Dialzara analysis)).

Benchmark nationally too: Thomson Reuters forecasts roughly 12 hours/week freed per professional as AI adoption scales, a reminder that local pilots should map time savings to redeployed client‑facing capacity so the “so what?” is clear - fewer admin hours, faster decisions, and staff focused on revenue and risk mitigation (Thomson Reuters AI productivity forecast).

Metric	Value / Local example
Manager time spent on scheduling (baseline)	5–10 hrs/week - MyShyft
Labor cost reduction	5–15% typical - MyShyft
Median annual AI savings (SMBs)	$7,500 median - Dialzara
Projected professional time saved (national)	12 hrs/week by 2029 - Thomson Reuters

“These training algorithms, they use a lot of computational power, they move data around so they need a lot of networking resources. Essentially they are carried out in large data centers, over large-scale computing and networking platforms often spanning the globe.”

Practical first projects for Lincoln teams should be short, measurable pilots that free human time and prove auditability: run a 90–120 day pilot of Microsoft 365 Copilot for Finance to automate data reconciliation and variance analysis (reduce month‑end churn and speed commentary generation), pair that with an advisor-facing AI notetaker pilot to capture meetings, extract action items and push clean summaries into CRM, and start both after a one‑day value‑stream mapping session to prioritize the highest‑impact workflows; guidance and templates help lower startup risk and keep controls exam‑ready (Microsoft 365 Copilot for Finance - automation for finance reconciliation and variance analysis, Guide to the best AI notetakers and assistants for financial advisors).

Measure pilot ROI in 3–6 months, track manager hours reclaimed and compliance accuracy, and remember the local “so what”: many Lincoln pilots pay back in months and can translate to $1,000–$2,500 saved per employee annually when redeployed to revenue or risk work.

Project	Quick win	Timeline
Copilot for Finance (reconciliation)	Faster variance analysis, fewer unmatched transactions	90–120 days
AI notetaker (advisor meetings)	Automated summaries, CRM sync, compliance flags	90 days
Value‑stream mapping + governance	Prioritized backlog, measurable KPIs	1 day mapping; pilots 3–6 months

“What we've done is we started with some value stream analysis, where we got in a room for a day and we went through all of our different processes and identified where there's opportunities for waste.” - Adam Auerbach

AI's future in Lincoln's financial services is practical, not speculative: regional leaders see AI folding into dealmaking and operations to automate routine work, sharpen decision-making and create new, AI‑enabled services (Lincoln International - Entering the Age of the AI Economy (industry perspectives)); Lincoln Financial's EvolutionIQ deployment shows how human‑in‑the‑loop models can speed claims handling and preserve outcomes - Group Protection claimants reported a 91% satisfaction rate in 2023 - demonstrating the “so what”: measured pilots free staff for client work and can pay back in months, often translating to $1,000–$2,500 saved per employee annually when redeployed to revenue or risk tasks.

To move from pilot to scale, combine accountable adoption owners and short, audited pilots with targeted upskilling (prompt design, tool selection and governance) so controls, examability and ROI track together - training such as Nucamp's Nucamp AI Essentials for Work bootcamp (AI skills for the workplace) makes that shift operational, not academic.

Attribute	Information
Bootcamp	AI Essentials for Work
Length	15 Weeks
Cost	$3,582 early bird; $3,942 afterwards; 18 monthly payments

“We are focused on investing in innovations and the latest capabilities to drive the best claim outcomes for our customers. Partnering with a technology leader in this space is a part of that investment and has quickly advanced our ability to provide claimants with even better support and resources for their recovery and to return to work.” - Christen White, SVP, Lincoln Financial Group Protection Claims and Operations