Akhil Lodha is the CEO and Founder of StratiFi Technologies, a company that provides an AI-powered platform to streamline investment workflows for wealth managers. With a strong background in quantitative finance, Akhil has over 12 years of experience in managing investment risk, having previously worked at Citigroup and led a $400M asset management firm. His academic credentials include a degree from the Indian Institute of Technology (IIT Bombay) and Carnegie Mellon University (CMU). Akhil’s vision with StratiFi is to unlock financial freedom by helping people secure their future.

Akhil Lodha

Acquisition-driven RIAs rarely struggle with deal flow.

They struggle with integration.

If onboarding a new firm takes days of manual reconciliation, growth eventually stalls.

Creekmur saved 50–200 hours per acquisition transition once risk alignment became systematic instead of manual.

M&A doesn’t break firms. Fragmented infrastructure does.

CEO at StratiFi - AI & Compliance for Wealth Management

M&A is a growth strategy — until onboarding becomes the bottleneck.

Creekmur Wealth Advisors nearly doubled acquisitions and advisors in one year. Their existing risk tools couldn’t keep up.

Before StratiFi:
- Poor interoperability across systems
- Manual portfolio risk reconciliation
- Time-intensive acquisition transitions
- Limited capacity to absorb new firms 
- Hours spent organizing data instead of advising clients

After centralizing risk and compliance with StratiFi, Creekmur now:
✅ Manages 6K accounts and $1B in assets from one dashboard
✅ Supervises 14+ advisors with ongoing risk alignment
✅ Completes client risk assessments in minutes
✅ Saves 50–200 hours per acquisition transition

Risk alignment is no longer a manual event. It’s an embedded workflow.

When acquisition velocity increases, infrastructure has to keep pace.

Read more at the link in the comments 👇

At scale, supervision has to be system-driven, not spreadsheet-driven.

Kingsview hit that inflection point at $8B AUM, 100+ advisors, and 30K+ accounts. With StratiFi Technologies Inc, they moved from manual drift reviews and paper RTQs to real-time oversight and a single dashboard.

Sharing the results below, plus the full case study.

At $8B AUM and 100+ advisors, spreadsheets stop being “good enough.”

Before StratiFi, Kingsview Partners relied on manual drift reviews and paper RTQs to supervise 30K+ accounts.

After implementing StratiFi:
✅ Identify portfolio drift 4x faster
✅ Supervise 100+ advisors from one dashboard
✅ Monitor 30K+ accounts in real time
✅ Eliminate compliance bottlenecks

When growth accelerates, manual oversight breaks.

Full case study at the link in our comments.

The SEC released its 2026 examination priorities on November 17, 2025.

For investment advisers, the focus is unmistakable: fiduciary duty, conflicts of interest, and whether your compliance program actually works.

Not whether it exists. Whether it works.

Here is what examiners will be testing:

→ Whether your investment advice aligns with clients' objectives, risk tolerances, and liquidity needs

→ Whether your firm is identifying and disclosing conflicts of interest that affect the impartiality of your advice

→ Whether trading activity demonstrates best execution

→ Whether your compliance policies are implemented, enforced, and monitored on an ongoing basis

The SEC is also examining how firms use and represent AI capabilities. But the core exam focus has not changed. It is still about fiduciary duty, suitability, and active supervision.

And this is where I see the biggest gap across our industry.

Many compliance teams today are reviewing accounts manually, pulling data from multiple systems, and running periodic reviews that leave gaps between each check. When an examiner asks, "How were you supervising this account between your last two quarterly reviews?", too many firms do not have a good answer.

This is the problem we built StratiFi to solve.

ComplianceIQ continuously monitors every account for Reg BI violations, mutual fund share class issues, cash and position concentration breaches, suitability gaps, and trading activity anomalies. Each flag comes with specific violation details, recommended actions, and the documentation a compliance team needs for regulatory review.

PRISM, our risk analysis engine, scores portfolio risk on a 1-10 scale using institutional-grade methodology, including Value-at-Risk metrics, concentration analysis, and factor exposures. When a portfolio drifts from a client's investment policy or risk tolerance, the system flags it in real time.

The SEC is telling firms that compliance programs need to demonstrate active, ongoing supervision. Not quarterly snapshots. Continuous oversight.

That is what the regulatory environment demands. And that is what we built.

What is the biggest compliance monitoring challenge your firm is facing heading into exam season?

#SECExam #ComplianceMonitoring #RIACompliance #WealthManagement #RegBI #ComplianceTech #RegTech

FINCEPTA

Founder

Divvy Homes

Lead a team of 20 associates, analysts & managers covering risk strategy & operations. Laid risk data foundations & upgraded risk policy, tools & models. Overhauled the collections & underwriting processes to improve cost, speed & conversion. Improved risk metrics during a high growth period & made tactical shifts in risk appetite to account for changing market conditions. Managed risk/UW components for new product launches.

VP, Risk & Ops

Fintech Startups

Formally & informally advising few fintech & proptech startups. Brainstorming challenges & solutions with promising founders & providing frameworks to enable growth & prove their product ideas with limited resources & data.

Advisor

Stilt Inc.

Stilt (acquired by JG Wentworth) was a financial services company focused on immigrants. Our main product was personal loan for immigrants with limited or zero credit history. We later launched Onbo in 2021 to help businesses build credit product without a bank sponsor.

Scaled lending business to $170m annualized origination from initiation stages. Responsibilities covered revenue, growth, product, compliance & strategic finance. Setup & scaled data, credit, operation & support teams. Developed & implemented a novel risk score (based on permissioned bank/financial data & credit history data) & underwriting decision engine (including fraud prediction, ability to pay & pricing optimization) to automate UW decisions. Helped in raising debt & equity capital. Managed risk/underwriting components in bank product & credit as a service platform (Onbo). Started employee #7.

GM Lending

Head of Credit, Risk and Data Science

Onbo by Stilt Inc.

 Head of Credit, Risk and Data Science

Merrill Lynch

Led transformation of strategic asset allocation from a one page framework into a hyper-customized product by making it more robust, cost/tax efficient, location specific & goals/term based which covered all major platforms (ML, UST, Edge, OCIO) & thus thousands of schemas. Developed portfolio construction engine to track an allocation through any given set of ETFs (robo advisor in retirement & Edge platforms). Implemented a goals driven retirement income strategy (joint research with EDHEC) to be launched in IRAs. Initially worked with several internal PMs (equity, tax optimization, ALM, ESG & mainly a $2b systematic multi-asset dynamic allocation strategy) as a quant by developing factor/optimization models, backtesting strategies & researching signals to predict factors & asset class returns.

Director, Chief Investment Office - Quantitative Portfolio Management

Bank of America

Developed first of its kind bank relationship data based credit underwriting models (not just behavior based on transactions/savings data but also other loans, assets, investments, retirement, trading data available from existing bank relationships). Models enabled the bank to deepen relationship (increasing credit approvals amongst existing bank customers), grow portfolio & de-risk (better performing newer cohorts) at the same time. Initially part of a team which developed underwriting and portfolio management scorecards and strategies for consumers and small businesses. Worked with internal & external partners to ensure models are fair & compliant.

VP, Credit Cards - Data Science & Analytics

Genpact

Transitioned of Toyota Financial’s data science & analytics projects (~$ 5mm in annual revenue) from Modelytics. Hired & trained a team of 14 analysts & managers to continue ongoing projects. Managed a team of 3 analysts to develop pricing, collection & residual risk models & strategies.

Data Science Manager

Modelytics

Modelytics, a boutique consulting firm, provided advanced analytics solutions & data science project delivery for an impressive client base comprising some of the leading financial services and banking firms based in US, Americas and Europe.
Worked on several challenging consulting projects which includes developing:
- Models & strategies for Toyota Financial's underwriting, collections & residual risk
- Pricing strategy for Discover credit card's introductory offers
- Deep learning model for fraud detection in Chase's debit card transactions (challenger to Falcon score)
- Growth analytics & models for Visa's offline debit card transactions
- Asset value & prepayment models for American Home Mortgage
Actively involved in campus recruiting, employee engagement activities & business development for the consulting firm.

Data Science Consultant

Sterling Commerce an AT&T company (now IBM)

Worked in B2B EDI product's development team.
Owned several messaging protocols & developed their wrappers & relevant features.

taplio

The Battle

Akhil Lodha

Ankit Tanwar

Followers

Posts

Engagements

Likes

Performance ScoreAkhil Lodha's LinkedIn Performance

Ready to grow your LinkedIn presence?

taplio

The Battle

Akhil Lodha

Ankit Tanwar

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Akhil Lodha's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance ScoreAkhil Lodha's LinkedIn Performance